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IRRl DISCUSSION PAPER SERIES NO. 15
systems research
Edited by: N.F.C. Ranaweera

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O International Rice Research Institute 1996.
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Ranaweera NFC. 1996. Impact of farming systems research. IRRI Discussion Paper Series No. 15. International Rice Resarch Institute.
P.O. Box 933. Manila. Philippines.

RECEIVED I RECU
.-
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:'.i!~atlon Unit /
S t c!is n de 1'6valuaf~on

Impact of farming
systems research
PROCEEDINGS OF THE FINAL WORKSHOP
ON IMPACT ASSESSMENT OF FARMING
SYSTEMS RESEARCH
Kandy, Sri Lanka
9-13 December 1991
Edited by: N.F.C. Ranaweera
P.O. Box 933, Manila 1099, Philippines

Welcome address
S .P.R. Weerasinghe
(Director of Agriculture, Sri Lanka)
Opening comments
Contents
F. A. Bernardo
(Deputy Director General, International Rice Research Institute)
Introductory address
Hon. R.M. Dharmadasa Banda
(Minister of Agricultural Development and Research, Sri Lanka)
Overview
N.F.C. Ranaweera
(Division of Agricultural Economics and Planning, Department of Agriculture,
Peradeniya)
Farming systems research and its impact on farm families in two selected 1
sites in Bangladesh--M. R. Siddiqui, M. R. Islam, N. P. Magor, N. U. Ahrned,
and A. H. Khan
Impact of farming systems research on selected farmers in Nepal: a case 2 8
study of Pumdi Bhumdi--S.B. Mathema, K.D. Joshi, J. KC.
Assessment of rice-fish farming system in Indonesia--M. 0. Adnyana, 5 9
D. K.S. Swastika, and W. Sudana
The impact of farming system research in Thailand--B. Shinawatara, 9 1
C. Sukapong, P. Woodtikam, P. Deundao, P. Padermchai, and B. Ontuam
Impact assessment of farming systems research-based technologies 129
in the Philippines: the Isabela experience--R. R. Gonzaga, C. V. C. Barba,
N. P. Gordoncillo, and N. F. C. Ranaweera
Institutionalizing the farming systems research approach
in Indochina--A. M. Mandac
Impact assessment of farming systems research and development 165
at the farm level: the case of KABSAKA technology in Iloilo, Philippines--
V. T. Villancio, C. H. Manalo, M. L. V. I. Rebulanan, A. Sotomil,
and N. F. C. Ranaweera
Impact of farming systems research on the research and extension 185
system: the case of the Philippines--V. T. Villancio, A. Punzalan, C. Hina,
and V. R. Carangal
vii
ix
. . .
Xlll

Assessment of the impact of a farming-systems based technology
site in Sri Lanka--N. F. C. Ranaweera, P. A. Samaratunga,
J. M. K. P. Jayasinghe, and G. K. Renuka
Impact assessment of farming systems research and development at
the farm level: the rice-watermelon cropping system in Pangil,
Laguna--V. T. Villancio, C. H. Manalo, M. L. Rebulanan, A. A. Arisgado,
F. L. Matienzo, and N. F. C. Ranaweera
Discussion and recommendations
Participants
Appendix: Acronyms

Welcome Address
S. P. R. Weerasinghe1
This is a historic occasion. It is the first time a serious attempt has been made to
evaluate the benefits accruing to technologies developed within a farming systems
perspective. The presence of the Honorable R. M. Dharmadasa Banda, minister of
Agricultural Development and Research, and his Secretary Mr. Dixon Nilaweera is
a clear recognition of the importance attached to farming systems research. It is also
a sign of appreciation to the efforts of scientists who contribute to the enhancement
of agricultural productivity. Their research has a direct influence on the farmers who
are the providers of food for our people. We are also privileged to have with us
Dr. F. A. Bernardo, deputy director general of International Programs, International
Rice Research Institute (IRRI), Dr. V. R. Carangal, coordinator of the Asian
Farming Systems Research Network at IRRI, and Dr. John Graham and Dr. John
Hardie from the International Development Research Centre (IDRC), which
provided the necessary funds to make this farming system activity a reality.
These studies would not have come to fruition were it not for the concerted
effort and dedication of scientists from the national programs in South and
Southeast Asia and from the international centers. This workshop is an opportunity
to critically review the impact of farming systems research, to identify the advances
and weaknesses, if any, and to make recommendations to enable national
agriculturil research systems to reorient future programs.
Within the context of diminishing arable land per capita and declining
incomes from farming, especially from rice, this workshop is most timely. Although
science and technology have made rapid advances in the past few decades, the
application of new technologies in different farming situations has not had the
desired effects on agricultural production and farm income.
Asian farmers have adopted a farming system that has gone through a
process of evolution. The goals of these farmers were subsistence for their families
and preverltion of land degradation. Scientists have taken time to comprehend the
aspirations of farmers, but questions must be asked about the ways that advances in
science and technology have been translated to farmers.
Farming systems research should not be confined to the development of
technology packages to increase production. Trade, postharvest handling and
processing, input supply and marketing, and many other factors are integral to
farming systems research and can be adopted by farmers to increase the production
potential of their resource base. These areas have not been included in systems
research to the desired extent, but they are of paramount importance to the farmer.
'~irector of Agriculture, Sri Lanka.

A farmer can increase production, but if the farmer does not have the capacity to
handle this production and cannot obtain reasonable prices for the outputs,
frustration with the new technology will result, and the farmer will revert to the
traditional system.
Agricultural scientists have a tremendous task ahead of them. They must
orient farming systems research to ensure that its application by farmers will result
in a sustainable increase in production and incomes. At the same time, however,
they must ensure that these technologies are in harmony with the environment and
that they do not contribute to its degradation.

Opening Comments
After 15 yr of farming systems research, what has been achieved? Has there been an
impact? Should governments as well as national programs and international
agricultural research centers continue to support farming systems research? An
impact on family incomes is overdue.
These impact studies on farming systems research take a hard look at
technologies and their impact on the productivity of farmers. We also need to
understand their impact on farm income and on the level of nutrition of farm
families. Farming systems research must also address sustainability issues. The role
of women, and gender issues in general, also have implications on sustainability.
After all, farming systems in many developin countries involve the husband, the
wife, and the children. Farming is actually a amily activity, a family concern.
We must, as well, have a hard look at the institutionalization of the farming
systems approach to research. Have national agricultural research institutes adopted
the farming systems approach in most of their research projects? Many institutions
now automatically adopt an interdisciplinary approach to the analysis of crop
problems and conduct of on-farm trials. We know that some countries have
established farming systems research institutes. This is good because it is a form of
institutionalization. But it is not good enough. The farming systems research
approach must become an integral part of agricultural research in most agricultural
research programs.
' ~ e ~ Director u t ~ General, International Rice Research Institute.
B
- vii -

Introductory Address
Hon. R. M. Dharrnadasa ~ andal
The Ministry of Agricultural Development and Research has collaborated with the
International Rice Research Institute for over 30 yr on a number of research
programs and exchanges of scientists. As a result of this collaboration, Sri Lanka has
developed a number of rice technologies that, in no small way, have contributed to
increased rice production and near self-sufficiency in rice. In addition, we have
collaborated to develop technologies for crop diversification through the farming
systems program.
In a similar manner, the Department of Agriculture in Sri Lanka has been
closely associated with the International Development Research Centre (IDRC) of
Canada. IDRC has made major contributions to the development of our farming
systems program for well over two decades. This study on the impact of farming
systems research was funded by IDRC. IDRC has also provided leadership to
develop technologies to improve grain legumes, develop oil seeds, and improve our
library facilities.
This workshop discusses the results of a 3-yr program and assesses the impact
of some new technologies used by farmers. Asia has the largest number of people
associated with agriculture. This agrarian population in Asia faces many problems,
both in dealing with the availability of land per unit of household and in the
availabiljty of labor for cultivating the land.
The increase in population in most Asian countries combined with the
decrease in land available for agriculture has resulted in a decrease in the ratio of
land to people. In 1987, this ratio was 0.1 1 in Sri Lanka; it is expected to decrease to
0.09 by the year 2000. In Pakistan, during this same period, the ratio will decrease
from 0.19 to 0.14, in the Philippines from 0.14 to 0.10, in Thailand from 0.38 to 0.31,
and in Bangladesh from 0.09 to 0.06.
This reduction in the ratio of land to people results in a larger number of
smallholders having small parcels of land. Therefore, the potential income-earning
capacity of a farmer is reduced because of the limited productive capacity of the
land. Consequently, it is more difficult for the farmer to move ahead economically.
It is in this context that current strategies and technologies must be assessed.
Nevertheless, overall perforinance in the agricultural sector in Asia has been
good. For example, during the past 15 yr, Sri Lanka has made remarkable
achievements in food crop production. Rice production has increased from about
1.5 million t in 1975 to 2.5 million t in 1990--an increase of 67% in 15 yr. This was
mainly due to a 59% increase in yield (from 2.3 to 3.4 t/ha). The area under rice
'~inister of Agricultural Development and Research, Sri Lanka.
-h-

increased as well, but only nlarginally. As a result of this significant increase, Sri
Lanka was able to reduce imports of rice and wheat flour from about 500,000 tlyr to
below 300,000 tlyr. Imports of wheat flour were kept constant, while average per
capita calorie consumption was maintained at the recommended level of 2,200
calories per person. Credit for this achievement must go to our farmers and
researchers.
During the last decade, advances have also been made in other field crops.
Average yields of maize have risen from less than 1 to 1.4 tlha, and total annual
production has increased from 30,000 to 40,000 t. Yields of cowpea and green gram
have improved from 0.6 tlha to more than 0.8 tlha, average yields of sweet potato
from 2.5 to 7 tlha, and yields of cassava from 3 to 10 tlha. These increases have
provided the population with Inore food at a relatively low price. Research in both
rice and other crops has enabled farmers to obtain these higher yields. An
associated phenomenon has been the increased use of fertilizer and other inputs,
which has provided the basis for increased intensities of cultivation. This
phenomenon is seen around tlie world.
This workshop looks at tlie jmpact of technology development from the point
of view of its effects on the farrner. Despite all the production success, something
still appears to be lacking. The farming population today is by and large poor, debt
ridden, and malnourished. The incidence of poverty is very high to the point of
being politically unsatisfactory. Farmers have always complained about their lack of
access to inputs and, as a result, their inability to realize the potential of the new
technologies. This is a serious problem. Some of the difficulties faced by the farmers
are water availability, input supply, and adequate market facilities at reasonable
prices. Some of these issues may be beyond the purview of this workshop, but they
affect farmers in most Asian countries. Farmers are also aware that some of the
services that are provided are poor, [hat the timeliness and availability of inputs are
unreliable, and that service is not continuous. It is not infrequent for farmers to be
associated with development programs that generate new technology that is
abandoned after some time either because of termination of funding or transfer of
personnel. Such situations must be looked at carefully.
Sri Lanka has given the highest priority to programs that invest in human
resources. The people are provided with direct access to resources with the aim of
transforming the passive, the inert, and the excluded population into productive
creators and owners of assets. 'The aim of this basic policy is growth with equity.
Over the past decade, the agricult~~ral policy of Sri Lanka was directed toward
achieving self-reliance in the basic requirements of food and increasing farmer
income. This two-pronged strategy focused on developing large-scale irrigated
settlements and commodity-oriented development programs that emphasized rice
and a few other crops. The realization that farm incomes are needed to be enhanced
has led to new policies [o diversify rural activities arid to provide farmers with Inore
opportunities to optimize the use of their resources arid thereby maximize incomes.
Our national policies have been focused primarily on increasing the supply of
food and improving the standard of living, particularly of the rural population,
through agricultural and rural develop~nent. Developing and transferring technology
on regionally appropriate crops and cropping and farming systems and the provision

of production inputs at reasonable prices, were aspects that received attention. This
enabled the farmers to increase productivity per unit area of land. To support and
sustain this process, the government continued to strengthen the irrigation system of
the country. Additional water resources were developed; the existing large- and
small-tank irrigation systems were renovated, rehabilitated, and maintained; shallow
and deep groundwater resources were harnessed through agro-wells and tube wells;
farmers and farmer organizations were trained in water management; and the
irrigation infrastructure was maintained to maximize the use of this scarce resource.
Creation of an institutional base to build a vibrant and well-articulated people's
organization was followed by strong policy.
Although marketing and prices for agricultural produce have been left
largely to market forces, the government has ensured a reasonable price to farmers
through a floor-price scheme. The government also facilitates the marketing of
agricultural produce to ensure that farmers are protected.
To attain sustainable growth with equity through a contin~~ous process of
development, a conscious effort has been niade by the government to decentralize
administrative power to the lowest possible operational level and to blend political
leadership and administration to make decisions on resource allocation, monitoring
programs, and implementation. Programs have also been aimed at environmental
protection and poverty alleviation. For example, in our lead project (the
Janasaviya), the poverty-alleviation program seeks to invest in the poor and equip
them to move away from the poverty trap and to become partners in development.
We have recognized that any program designed for those groups must necessarily be
environmentally sustainable.
Despite these efforts, the pace of development, particularly in the agrarian
sector, has been below expectations. Is this because some of the technologies that
have been provided to the farmers are not appropriate to the social, economic, and
cultural environment? Often, researchers, policymakers, and administrators claim
that the technologies that have been developed are successful and that the farmers
have benefited. However, if the effects are carefully analyzed, reality is far from this
situation.
Tn view of the mixed results of past policies, Sri Lanka is embarking on an
innovative, forward-looking, aggressive policy in agricultural development. The
overriding goal of agricultural development will continue to be directed toward
achieving self-sufficiency in food (particularly rice). The principal aim of :igricultural
development progriims will be to contribute to increase rural household incomes to
levels comparable with those of families in other sectors of the economy. The main
instruments will be the use of modern production and marketing techniques,
diversification of the portfolio of crops, and expansion of off-farm sources of
income.
The challenges of providing adequate food and an improved living standard
for the farming population must be considered seriously. A conflict in the
agricultural sector is the difficulty of providing food to the people at a reasonable
price while ensuring a high quality of life for the farmers. High consumer prices may

esult in high incomes for farmers, but this is not always an acceptable option for
consumers. However, cheap food, unless accompanied by very high production
levels, cannot increase farmer income.

Overview
Agricultural research in the past had the luxury that accountability to the majority
clientele, namely the farmers, was not a high priority in the research agenda. More
recently, because of the greater demand for technologies that are relevant to the
immediate ecological and socioeconomic environments, programs have focused
their attention on the needs of farmers. This has been particularly true in the case of
technologies developed within the framework of farming systems research (FSR), in
which the concept of the whole farm and a systems perspective to the research has
been adopted.
Present-day agricultural research seeks to develop technologies that are
sustainable over time, environmentally safe, and allow farmers to increase their
incomes to achieve a better quality of life, whichever way it may be measured.
During the last decade, pressures were placed on national programs to conduct
agricultural research and development programs identified with FSR. International
donor agencies tended to provide finances for research only if it was considered
within such a perspective.
The adoption of FSR and the resulting technologies have resulted in
significant increases of food production and in benefits to the research community.
It has provided knowledge on effective methodologies and approaches to research,
provided opportunities for more qualified human resources, through both formal
and on-the-job trainings, and developed improved technologies.
WHY STUDY IMPACT?
With the maturing of these programs and increased emphasis on strengthening
farming systems research in developing countries, a valid question is whether the
new technology has had the desired effects in terms of overall food production and,
more significantly, real benefits to farmers. The question is then asked: why study
the impact of any program? This could be done for a number of reasons.
Pure inquisitiveness
There are researchers who look at the impact of any program purely from the point
of view of inquisitive~less. They want to know, in general, the effects of the new
technology.
'~ivision of Agricultural Economics and Planning, Department of Agriculture,
Peradeniya.

Investor concerns
Usually investors are interested in the outcome of a new technology and its impact
on various parameters that range from productivity to incomes. This is particularly
true in the case of large-scale development programs that make significant
investments in the agriculture sector. In these instances not only the direct benefits
are of interest, but also the indirect social and other multiplier benefits.
Donor requirements
Doilors that fund research and development programs are often interested in the
final impact of their investments. This is reflected in periodic reviews by project
evaluation teams that go to the field to understand the benefits that farmers have
obtained from the new technology. However, these cursory visits do not adequately
provide the information. An assessment of the benefits that the larger group of
farmers have obtained from a particular program is of interest to donors.
Feedback to researchers
Within a research complex, the greatest beneficiary of an impact study will be the
researchers themselves. They benefit by obtaining a better appreciation of the
benefits, or lack of benefits, from the perspective of the farmers. This is not usually
done because, in most instances, researchers are satisfied with the knowledge that
their research efforts are being practiced by farmers. Macrostatistics that indicate
overall increases in production do not reflect the real picture in terms of differential
impacts across different environments, or across different farmer groups and
farming systems. This information can be obtained only from an in-depth impact
study that analyzes the causes and effects of the use of a technology in a particular
environment.
IMPACT ON WHAT?
Generally, economists involved in agricultural research tend to look at benefits from
new technologies that reflect components of economic development. The issues can
be categorized into micro and macro issues.
Micro issues
These issues are related more to direct effects in terms of increases in productivity,
real incomes, and purchasing power of the farmers. These benefits are reflected in
terms of a greater and more efficient use of inputs that further increase productivity.
Increases in the accumulation of capital assets, both farm and nonfarm, and, from a

nutritional aspect, changes in food intake that are reflected in better nutrition of the
farm family are also examined.
Macro issues
These issues generally relate to whether, during the process of adoption of the new
technology, there has been an effect on employment, education, and capital flows.
Associated questions are whether supporting institutions, such as extension, credit,
marketing, and input supplies, have responded to the demands of the new
technology, and to what extent, if any, have agricultural policies (particularly
pricing) been affected. In other words, have the adverse social and economic
environments facing the farmer been reduced or eliminated through the provision of
the support services that are normally needed for successful farm production?
The influence of agricultural research on the overall development process is
usually limited to providing only the technology. Other support services and
agricultural policies do not necessarily go in tandem with the technology
requirements. This often leads to a large degree of nonadoption of the new
technology.
Although researchers portray FSR as a strategy for agricultural development,
does it really provide the necessary answers to the multifaceted questions that are
being faced at the level of national agricultural development? Research is
concerned with exploring the uncertain. If the problem is successfully solved, the
probabilitj, of disseminating the research results in their exact form is low and the
chances of providing a positive effect on development with the equity goals
identified is uncertain.
Has the FSR approach provided adequate justification to be used to
spearhead agricultural development programs that will provide farmers with
adequate incomes to improve their quality of life? What this essentially asks is: what
impact has the FSR approach had on the way of life of farmers from a development
perspective? The ultimate aim of any improved agricultural system is to increase the
quality of life and improve the well-being of the farming community.
An impact study of FSR technology could identify the strong and weak
components of the technology itself, help make better resource-allocation decisions
(particularly for research managers), provide alternate choices for the research
planning process, and identify the support services and policy measures that are
needed to obtain real benefits from the technology. An analysis of the interplay of
farm resources with consumption and other activities can provide insights to the real
impact the new technology has had on farmers.

WORKSHOP OBJECTIVES
This workshop is the culmination of a 3-year study in six Asian countries
(Bangladesh, Indonesia, Nepal, Philippines, Sri Lanka, and Thailand) that
investigated the impact of FSR on their national programs. The purpose of the
workshop was to present individual country experiences, understand the extent to
perspectives have been incorporated into FSR activities, and provide
future impact studies.

FARMING SYSTEMS RESEARCH AND ITS IhIPACT ON FARM FAMILIES
IN W'O SELECTED SITES IN BANGLADESH
M. R. Siddiqui, M. R. Islam, N. P. Magor, N. U. Ahmed, and A. H. ~han'
The study was conducted to determine the extent of adoption of rice
cropping systems technologies suitable to lowland rainfed areas, its
impact on resource use, productivity, and income-expenditure
patterns of selected farmers in two sites in Bangladesh. The sites are
Kamalganj in the northeast and Sitakund in the southeast. The
Kamalganj site which has rice surplus produces infrastructural
facilities. Although Sitakund has access to major markets and off-farm
employment, it is deficit in rice. Ninety farm families were randomly
drawn from 6-7 villages in each site. Crop production per season and
weekly income expenditure data were collected. Critical crop
production factors such as planting time, varietal sequence, intensity
of cropping, and fertilizer dosage were used in determining
technology adoption. Aggregated scores of all these factors were
divided into three class intervals and the farmers were divided into
low, medium, and high adopters. Results showed that the farmers
adopted the technology. The productivity of the land and other
resources varied positively in relation to the extent of adoption. Poor
farmers (on the basis of farm size) were high adopters of the cropping
systems technology and have invested more on required inputs. The
extent of resource use in the production process was almost the same
at both sites. But the yield was lower at Sitakund compared with that
in Yamalganj due to variations in natural factors. The adoption of
cropping systems technologies has generated more employment
opportunities. The study suggests that infrastructural development at
the initial stage and diversity in sources of income are essential in
maintaining and improving the standard of living of the farming
communities in the study areas.
Bangladesh is primarily an agricultural country. More than 90% of its population is
rural and about 75% of its total labor force is engaged in agriculture. Agriculture
contributes approsim:ttely 56% of the gross domestic product (GDP) and provides a
number of the raw materials required by the industrial sector. Altho~~gh agriculture
is the most important economic activity in the country, Bangladesh does not produce
enough food for its large population nor earn sufficient fore~gn exchange to allow
importation of the needed food. Productivity per unit area of cultivated land is low
because of the use of traditional production systems (e.g., use of local cultivars).
This is a major constr;iint to attaining food self-sufficiency (Hoque 1978).
'~an~ladesh Rice Research Institute, Gazipur, Joydehpur, Dhaka.

Rice is the major food crop and dietary staple in Bangladesh. Of the
13.5 million ha of cultivated area, rice covers about 10.6 million ha and is the only
source of cash for many farmers (BRRI 1989). Research and development of
appropriate rice technologies are needed to fit the existing farming systems, improve
the nutritional status of the population, provide economic welfare to farm families,
and meet the national food demand. To achieve these objectives, the Bangladesh
Rice Research Institute (BRRI) was established on 1 Oct 1970 as a semi-
autonomous body.
CROPPING SYSTEMS RESEARCH AND DEVELOPMENT AT BRRI
The BRRI Cropping Systems Program focuses on increasing agricultural production
in major agroecological environments through the efficient use of available farm
resources and the adoption of improved cropping systems technologies. Farmer-
participatory research in the villages has been the main approach of the program.
The-program has addressed the following agroecological environments:
rainfed upland, rainfed lowland, upland, irrigated lowland, dryland farming, and
deepwater rice area. Attempts have been made to evaluate existing cropping
patterns in terms of productivity, stability, and profitability. Consequently, improved
cropping patterns and components of technologies have been designed and tested,
and recommendations have been made for greater adoption.
TECHNOLOGY FOR THE RAINFED LOWLAND ENVIRONMENT
In Bangladesh, rice is cultivated under irrigated, rainfed, and deepwater conditions
in four distinct rice seasons. These are aus, transplanted aman, broadcast or
deepwater aman, and boro. Aus followed by transplanted aman rice is a major
cropping system in the rainfed lowland environment, covering an estimated 3
million ha. Rainfall and topography are important factors that influence the
adoption and productivity of this cropping system in the rainfed lowland
environment. Aus rice is photoperiod-insensitive and generally grows under rainfed
conditions either as broadcast or transplanted crops from March to September.
Aman rice is transplanted from July to September in areas where water depth does
not exceed 0.5 m.
Based on its extensive multilocation trials (MLT), the BRRI Rice Farming
Systems Division has demarcated the land that can be used for this cropping system
(aus followed by transplanted rice in aman) into three major target areas (Fig. 1).
The onset and the duralion of wet (200 mm rain per month) and cool seasons, soil
texture, suitability of the crop for the winter season, and socioecono~nic factors
influence the choice of varietal combinations within a target area. The field duration
and the establishment date of the aus crop, and the period between aus and aman,
determine the date on which the aman rice crop can be transplanted. Within any
single year, the establishment of the aus crop may be spread over a period of 4 -8
wk. If rain starts late, the establishment of the aus crop will be delayed, which forces
the aman crop to be planted in September. Socioeconomic factors, insufficient

labor, capital, and draft power spread the harvesting of aus and transplanting of
aman over several weeks.
The socioeconomic constraints limit the adoption of the BR1 - BR1 1
cropping pattern by farmers. The aman crop is very sensitive to the date of
establishment and to moisture stress. If the BR1 variety is not transplanted by 25
May (either because of the delayed onset of wet season or socioeconomic factors),
the cropping pattern BR1 - BR11 may not be adopted in the central and eastern
parts of Bangladesh. This feedback provided scope for further refinement of the
technology and led to the establishment of cut-off dates for the various target areas.
Accordingly, cut-off dates were suggested for the northeast area (target area 1)
based on a predictive model (Magor et a1 1990) and for the southeast area based on
observations (Fig. 1). Alternative cropping patterns were offered to farmers who
failed to establish their aus crop by the cut-off date (Table 1).
THE PROBLEM
BRRI has recommended 26 high-yielding rice varieties suitable all over Bangladesh
for specific seasons. The technologies generated by the Rice Farming Systems
Division have been tested and proven to be productive and have been adopted in
many target areas. For example, in Jamalpur, 100% and 85% of the farmers
adopted modern rice varieties in the boro and transplanted aman seasons,
respectively (Hoque et a1 1985). Farmers of Bhogra Village in the Gazipur District
adopted recommended cropping systems technologies in more than 60% of their
land and obtained 1 t/ha more per year than the nonadopters. Similar adoption
studies were reported by Asaduzzaman (1979), Herdt and Garcia (1982), Hossain et
a1 (1984), Dalrymple (1986), and Hossain (1987). All these studies investigated only
the rate of adoption of agricultural technologies and the factors that contributed to
the adoption process. None attempted to determine the impact of adoption on
income, consumption, and other expenditure patterns.
This study attempted to determine the extent of adoption of the farming
systems technology and its impact on income, consumption, and other expenditure
patterns related to production in the farming community. The results were expected
to provide basic information that would guide researchers and policymakers in the
efficient allocation of research resources.
OBJECTIVES
The specific objectives of the study are to determine the extent of adoption of
improved cropping systems by farmers; to evaluate the impact of improved cropping
systems on resource use and productivity; and to assess the impact of improved
cropping systems on farm income, consumption, and other expenditure patterns.
In view of the problems and objectives of the study, the following hypotheses
were tested: most farmers are adopters of improved cropping systems; the extent of

esource use and productivity varies according to the level of adoption; and income,
consumption, and other expenditure patterns vary according to the extent of
adoption.
Approach
METHODOLOGY
This was an ex post evaluation of cropping systems research in Bangladesh. It was
designed to compare farmers with different levels of adoption and to measure the
impact of cropping systems technology on productivity of resources, farmers'
income, and expenditure patterns.
Site selection
Two sites (Kamalganj and Sitakund) were selected for the study. At Kamalganj,
cropping systems research was conducted; while at Sitakund, multilocation testing
was conducted. At both sites, small-scale pilot production programs had been
launched and were productive. Both sites have 200 mm or more rainfall per month
from May to September, sandy loam to clay loam soil, flood-free zone (i.e., a
maximum level of 30 cm of water after heaw rainfall), and double-rice cropping
system previously dominated by local varieties.
Selection of villages and farmers
Kamalgutij site. A survey was conducted in 13 villages within a radius of 5 km from
the Kamalganj bazaar, to collect information on flooding, land holdings, and
occupational structure of all households. Villriges prone to flooding were omitted.
The remaining seven villages had similar land types. Households whose major
source of income was agriculture were included in the sample. Proportionate
random samples were drawn from each of the seven villages io obtain 90
respondents.
Sirctkzrtzti Sire. A household survey was concluctetl in 16 villages. The villages
where agriculture was not the major occupation were excluded. Six villages were
selected for the study. From these six villages, 90 I~ouseholds were selected based on
proportionate random sampling.
Criteria to rate the extent of adoption
Several factors affect the recommendations for rainfed lowland rice cropping
systems. Factors such as timing, varietal sequence, intensity (single or double

cropping), and nitrogen and phosphorus application levels each constitute a part of
the recommendation. For this reason, a scoring system that incorporated these
parameters was developed on a plot basis and then cumulated for each farmer.
Timing. In normal years (200 mm or more rain in May), farmers are advised
to grow modern varieties on heavy textured soils in both the aus and aman seasons.
Delays in the onset of the wet season and constraints in labor or draft power mean
this recommendation must be adjusted to include a combination of modern and
local varieties and single cropping. Alternative varietal sequences have been
recommended to adjust to these constraints (Table 1). The recommended sequence
for a given transplanting date for a particular plot was given a score of 100. Whole-
farm scores were weighted by area and expressed as a percentage.
Vurietal seqrielzce. Irrespective of timing, a weighted score was gi~len to the
combination of varieties (Table 2). A farmer who grew a modern variety in aus
followed by a modern variety in aman on a particular plot received a score of 100.
Itrtetzsity. A double-crop sequence was given a score of 100; a single crop, 50.
Fertilizer rute. Based on an intensive study of farm variety and fertilizer
response, the NPK fertilizer recommendation is 60:40:20 for a nlodern rice variety
and 40:20:0 for a local variety. Only N fertilizer was scored ancl calculated on the
basis of plot'percentage according to the varietal sequence. Recommended levels of
N fertilizer are shown in Table 2. For example, a farmer who grew a modern rice
variety in aus follo\sred by a modern variety in aman and used a total of 120 kg N/ha
would receive a score of 100 for level of N fertilizer. Similarly, for the fallow - local
rice variety pattern in aman, a farmer who used 50 kg N/ha would receive a score of
100 for N level. However, a farmer could receive a score of more than 100 for a
given plot by using more than the recommended level of input. Scores \seere then
cumulated on a whole-farm basis and weighted according to extent.
dgr-eg'(~te scow.^. Different st~idies showed that varietal secluence, cropping
intensity, and fertilizer rate are the most important factors responsil~le for annual
crop yield per hectare (Hoque and Hobbs 1981). The correl;ltion matrices in Tables
3 and 4 show similar relationships between total production and other factors suc.:~
as varietal sequence, cropping intensity, and N fertilizer. However, the relatior:ship
between total production and N fertilizer was not significant. This might be due to
the low rate of fertilizer used by fdrmers. To calculate the adoption score, equal
weights were given to these three factors and the data were aggregated on a per year
as well as per farm basis. Two crop years were included in the study and an average
score over 2 yr was used to group the farmers according to the extent of adoption.
At Kamalganj, the highest average score for 2 yr was 285 and the lowest was 156.
Individuals having an aggregate score of 5 200, > 200 to 5 244, and > 244 were
defined as low, medium, and high adopters, respectively. The same scoring
technique was applied at Sitakund.

Determination of ado,)tion factors
Regression analysis was done on the household survey data to identify the extent to
which socioeconomic factors affected the decision to adopt modern rice
technologies. The model used was:
ADSC = F (FSIZE, POWER, AGE, EDUC, EXFA, POLND, ECONOMIC)
where ADSC = aggre ated adoption score (9%); FSIZE = farm size (ha);
POWER = number o f: animals used for power per household or pzr hectare; AGE
= age of the respondent (years); EDUC = educational level of respondent (years of
schooling); EXFA = experience in farming (years); POLND = percentage of rent
in land; and ECONOMIC = number of effective family members per household or
per hectare. The ordinary least square (OLS) technique was used and the best-fit
model was selected on the basis of the sign and significance of the coefficients.
Extent of resource use and productivity
The enterprise budgeting technique was used to analyze the extent of resource use
and productivity. Aus, aman, and aus and aman were considered as individual
enterprises according to thc extent of adoption. The budgeting technique was used
because it is relatively easy to ~lnderstand. A farm layout of the individual
households was drawn and the size of the plots, tenurial status, and types of land
were recorded. Crop production data on varietal sequences, dates of all operations,
labor, animal power, and other inputs (e.g., fertilizers and insecticides) were
recorded for each plot. Data on the use of family and hired labor were classified
under niale, female, and children. Crop production data were collected mostly from
a male adult (preferably the head of the household). Daily wage rate and weekly
niarket prices of inputs and outputs within the project area were also recorded. Data
on physical p;irameters such as rainfall and temperature were also recorded. Data
on crop yield were collected from farmers and validated using crop-cut estimates.
Different efficiency criteri:~ ivere calculated on a per hectare basi4 using current
prices.
Income sources and patterns of expenditure
Because rural ho~iseliolds do not keep records of their activities, it is difficult to
estimate activities done o11 a self-employment basis and expenditures that do not
require cash transactions. Income and expenditure data were collected on a weekly
basis to reduce the degrep, of inaccuracy. In kind transactions were valued using the
prevailing market price. Gifts received in cash or in kind were considered as income.
Donations were considered as expenditures. Consumption from production was
regarded as cash inflow (illcome) as well as cash outflow (expendi~ore). Validated
income and expenditure data were aggregated on a yearly basis. Comparisons were
made on a per farm as well as on a per hectare basis to standardize for land area
and family members, respectively.

Management of the sites
A site coordinator supervised each site and two local interviewers (male and
female) collected the data. Employment of local female interviewers is essential for
this type of data collection. It facilitated access to female members of the household.
The coordinators visited the sites regularly and supervised the work of the field staff
to ensure accurate collection and coding of data.
RESULTS
Socioeconomic characteristics of the households
None of the households were landless. The average farm size was 0.95 ha in
Kamalganj and 0.70 ha in Sitakund. At Kamalganj, average farm size was higher
than the national average of 0.70 ha (BBS 1980). At both sites, high adopters are
smallholders. On average, a household had six members at Kamalganj and seven at
Sitakund. The average age of the respondent was 47 years at Kamalganj and 50
years at Sitakund. At both sites, the education level of the respondents was the
primary level. Animal draft power was a major constraint in both sites. An average
household at Sitakund had one animal and at Kamalganj two.
The functional relationship between adoption of modern rice technologies
and the so~ioeconomic characteristics of the respondents was also investigated.
Extent of adoption
Originally, 90 farmers from each site were selected for the study but some farmers
refused to cooperate. In Kamalganj, 88 farmers participated in the study, while
there were 54 respondents in Sitakund. Most of the selected farmers at both sites
adopted the rice production technologies. At Kamalganj, 18 farmers were low
adopters, 47 were medium adopters, and 23 were high adopters. At Sitakund, 10
were low adopters, 30 were medium adopters, and 14 were high adopters (Table 5).
Low adopters owned fewer draft animals than the medium and high adopters at
Kamalganj (Table 6). At Kamalganj, either one buffalo or a pair of cattle were used
for plowing. Therefore, one buffalo was considered equivalent to one pair of cattle.
Factors of adoption: an econometric analysis
Regression analvsis was used to determine which of the socioeconomic factors
affected the decision to adopt niodern rice technologies (Table 7). The estimated
model explains only 13% of the total variation in the adoption decision in
Kamalganj and 38% in Sitakund. The relationship between adoption and the
explanatory variables (F ratio) was significant at the 1% level of probability. The

number of active family members per family and the number of animals per family
were significantly and positively associated with the adoption of modern rice
technologies at both sites. However, there was an inverse relationship between farm
size and ado tion of modern rice varieties. This was also found out in the studies of
Lionberger (960)~ Juliano (1967), Copp and Sill (1968), Feliciano (1968), Madigan
(1968), Guzman (1973), Islam (1986), and Hossain (1987).
Yield, input use, and productivity according to adoption
Enterprise budgeting places information about production and inputs in a common
framework. It provides insights into the efficiency of input use and its impact on
productivity. At both sites, aus followed by aman was the major cropping system.
In 1989, the average rice yield in Kamalganj was 2, 396 kg/ha in aus, 2,561 in
aman, and 4,957 in aus and aman (Table 8). Group comparisons showed that the
difference in yi-eld between low and high adopters was significant. High adopters
obtained 1,127 kg more rice/ha per year than low adopters (Table 9). In 1990, the
average rice yield was 2,623 kg/ha in aus, 2,947 in aman, and 5,570 in aus and aman.
Results of the group comparisons showed that the yield difference between low and
high adopters was significant. High adopters obtained 1,105 kg more rice/ha than
low adopters (Table 9). Increase in yield might be due to adoption of the rice
technology and favorable weather conditions in both years.
Average rice yields in 1989 at Sitakund were 1,625 kg/ha in aus, 2,639 in
aman, and 2,639 in aus and aman (Table 8). Yield difference between low and high
adopters was significant. High adopters obtained 1,440 kg more rice/ha per year
than low adopters (Table 9).
In 1990, average rice yield in aus season was 1,816 kg/ha, 1,435 in aman, and
3,251 in aus and aman (Table 8). Group comparisons showed that yield difference
between low and high adopters was significant. High adopters obtained
1,293 kg more rice/ha than low adopters.
At Sitakund, 1989 rice yield was low compared with yield in 1990 because of
the drought at the beginning of the aus season and insect infestation during the
aman season.
In the aus and aman seasons in 1989, thd intensity of using human labor,
animal draft power, and fertilizers were highest for the high adopters followed by
medium and low adopters (Table 10). Most of the high and medium adopters were
smallholders who cultivated their land more intensively using family labor. Sitakund
farmers used more hired labor and animal power compared with Kamalganj farmers
because the opportunity for off-farm employment is higher at Sitakund. Sitakund
farmers may have substituted family labor with hired labor and engaged in nonfarm
activities. Farmers at t~oth sites used less fertilizer than the recommended rate

ecause of financial difficulties and lack of awareness. At both sites, high adopters
used the highest fertilizer input, followed by medium and low adopters.
A similar trend was observed in 1990 (Table 11). At both sites, total annual
cost per hectare was highest in the case of hi h adopters followed by medium and
low adopters. Returns to family labor, hired k abor, animal draft power, and material
inputs were higher at Kamalganj. But the cost of rice production per kilogram was
lower at Kamalganj; therefore, Kamalganj farmers were more cost-effective than
Sitakund farmers. At Kamalganj, group comparisons showed no significant
differences in net returns between low and medium adopters or between medium
and high adopters. However, there were significant differences in gross return
between low and medium and between medium and high adopters (Table 12).
At Sitakund, group comparisons showed significant differences in gross
return and total cost between low and medium and low and high adopters. But the
net return was not significant.
Adoption and its impact on income and expenditure
The 1989 farm income of low adopters in Kamalganj was 58% of their total income,
medium adopters was 54%, and high adopters 63%. In 1990, low adopters' farm
income was 51%, medium adopters 59%, and high adopters 60%. While in
Sitakund, the 1989 farm income of low adopters was 34% of their total income, 59%
for medium.adopters and 50% for high adopters. The 1990 farm income of low
adopters was 4396, medium adopters 59%, and high adopters 45%.
The primary source of income for low and high ado~ters of rice technologies
in Kamalganj was farming. In Sitakund, nonfarming activities were the major source
of income and low adopters. While high adopters' dominant source of income were
both farming and nonfarming activities (Table 13).
At Kamalganj, the 1989 income from rice production was 78%, 82%, and
85% of the total farm income for low, medium, and high adopters, respectively (data
not shown). This increase in income was directly related to the adoption of the
technology. Similar results were obtained in 1990. The highest income from the sale
of rice was obtained by high adopters. Income from livestock was the second most
important source of farm income (about 10 % of the total farm income). Nonfarm
income was about 40% of the total income. This decreased with the rate of adoption
of rice technology. Service, business, and labor were the major sources of nonfarm
income. At Sitakund, income from rice production was not directly related to
adoption of technology. In 1989, the income from rice production was 65%, 32%,
and 38% of the total farm income for low, medium, and high adopters, respectively.
Again, high adopters gained the highest income from the sale of rice. Vegetable
cultivation and livestock were the two most important sources of farm income at
Sitakund. Nonfarm income at Sitakund was higher than in Kamalganj. Service,
business, and overseas employment were the most important sources of nonfarm
income.

At both sites, more than 73% of the total expenditure was spent on
household requirements and the rest was spent on farm resources (Table 14).
Farmers incurred the highest farm expenditure on hired labor and inputs.
Expenditure on input use was directly related to the adoption of technology.
Sitakund farmers spent more on hired labor because the wage rate was higher due
to partial industrialization of the site. The highest household expenditure was for
purchasing rice. This was inversely related to the adoption of technology (data not
shown). At both sites, adoption of rice technology helped the farmers attain partial
self-sufficiency in rice. In Kamalganj, less emphasis was given to education,
medicine, and animal protein. But at Sitakund, high adopters spent more on
education, medicine, and animal protein, followed by medium and low adopters.
Similar patterns of income and expenditure were observed in 1990.
Annual incomes and expenditures are presented in Table 14. Average results
over 2 years indicated that cash balance at both sites was directly related to the
adoption of technology escept in the case of medium adopters at Kamalganj. In
general, this indicates that farming is a profitable activity.
POLICY IMPLICATIONS OF THE FINDINGS
Adoption of cropping systems technologies had a substantial impact on the economy
of the villages. Smallholders were high adopters of the cro ping systems technology.
The high adopters did not apply the recommended dose o P fertilizer. The household
survey indicated that small landholders had low purchasing power. The provision of
credit facilities would enable further adoption of modern rice technologies.
Although the extent of resource use in the production process was almost the
same at both sites, the yield was lower at Sitakund because of variations in natural
factors. Even under unfavorable conditions during 1989-90 in Sitakund, the
recommended technology outperformed the traditional practices. The study showed
that high adopters used more hired labar as well as family lahor in the production
process. Hired laborers are the landless or the small landholders. Therefore, an
attempt should be made to improve the adoption of modern rice technologies
through the extension services. This will generate more employment opportunities
and increase the purchasing power of the landless and the sn~allholders.
Although the farming systems included crops, livestock, homestead-forestry,
and off-farm activities, the rice sector was the dominant component in the study
areas. The rice cropplng system is subject t0 natural hazards. Therefore, attention
must be give11 to other sources of income (e.g., intensive srnall-scale vegetable
cultivation, goat rearing, and pond culture of fish) that could stabilize and increase
income. The potential for nonagricultural income must :ilso be explored.
At Kamalganj, there were no rice processing centers. Farmers were forced to
sell their grain to dealers at lower prices at the time of harvest to meet urgent cash
needs. The development of small-scale local processing centers may strengthen the
position of the farmer.

REFERENCES CITED
Asaduzzaman M (1979) Adoption of HYV rice in Bangladesh. Bangladesh Dev.
Stud. 7(3): 23-49.
BBS--Bangladesh Bureau of Statistics (1980) Bangladesh statistical year book.
Dhaka, Bangladesh.
BRRI--Bangladesh Rice Research Institute (1989) About BRRI. Gazipur,
Bangladesh.
Copp J H, Sill M L (1968) The function of information sources ir, the farm practices
adoption proci.ss. Rural Sociol. J. 23: 146-147.
Dalrymple, D G (19%) Development and spread of high-yielding rice varieties in
developing countries. United States Agency for International Development,
Washington, D. C.
De Guzman A M (1973). Corolan rice farmers' response to change in cropping
patterns: a case study. (mimeogr.)
~eliciano'~ D (1968) Corrclates of productivity among tobacco f~rmzrs in Isabela.
Ph D dissertation, University of the Philippines, Los Bafios, College, Laguna,
Philippines.
Herdt R W, Garcia L (1952) Adoption of modern rice technology: the impact of size
and tenure in Sangladesh. International Rice Research Institute, P.O. Box
933, Manila, Philippines. (mimeogr.)
Hoque M Z (1978) A proposal for the extension of the Bangladesh Rice Research
Cropping Systems Projects. Project proposal submitted to the International
Developinent Centre, Canada.
Hoque M Z, Hobbs P R (1981) Rainfed cropping systems report of research
findings at Bhogra village, 1975-79. Bangladesh Rice Research Institute,
Gazipur, Bangladesh.
Hoque M Z, Nasiruddin M, Chowdhury N H, Hossain h4 (1985). Adoption and
impact of modern varieties on rice production in Bangladesh. Proceedings of
the workshop on experiences with modern rice cultivation in Bangladesh,
Bangladesh Rice Research Institute, Bangladesh.

Hossain A M, Nur-E-Elahi, Nazrul I M M (1984) Farmer adoption study of
recommended rainfed modern double rice cropping pattern technology
under existing farming systems. Bangladesh Rice Research Institute,
Joydebpur, Gazipur.
Hossain M (1987) Farm size, tenancy, and land productivity: an analysis of farm
level data in Bangladesh agriculture. Bangladesh Dev. Stud. 5(3):285-348.
Islam M R (1986) Efficacy of deep-well pump irrigation system in improving
rice-based farniing in Nueva Ecija. MS thesis, Central Luzon State
University, Philippines.
Juliano C P, Jr. (1967) The relationship between some characteristics of rice farm
operators and adoption of some recommended practices in rice production in
seventeen barrios of Laguna. MS thesis, University of the Philippines College
of Agriculture, College, Laguna, Philippines.
Lionberger H F (1960). Adoption of new ideas and practices. Iowa State University
Press, Arnes, IA.
Madigan F G (1968) The farmers said no. UP CRDC.
Magor N P, Siddiqiii M K, Ahmed N U, h4iah N I, Amin R (1990) Creating
computerized farm plans. Paper presented at the 1990 Asian Farming
Systems Research and Extension Symposium, 19-22 Nov 1990, Bangkok,
Thai1:ind.
Magor N P (1986) Proceedings of high-yielding variety workshop. Bangladesh Rice
Research Institute, Gazipur, Bangladesh.
Miah S A, Mannan h1 A (1989) modern rice technology and its contribution to
Bangladesh economy. Bangladesh Rice Research Institute, Gazipur,
Bangladesh.

Table 1. Cropping pattern recommendations for rainfed lowland environments with heavy
textured soils based on the aus transplanting cut-off dates.
Aus transplanting Cropping pattern
cut-off date Aus T. aman Remarks
30 May BR1 BRllIBR10 Refined original
recommended pattern
20 May-
30 Jun
(1) short-
duration
local variety
(2) short-
duration
modern variety
After 20 Jun (1) fallow
(2) modern
Aus
BRllIBR10 Aman transplanting to
be completed within
August
Local Aman transplanting is
expected to take place
in September
BR1 11BR10 Transplanting to be
completed within July
Fallow

Table 2. Crop varietal sequence score with recommended total N and P for
each sequence.
Varietal sequence Recommended
fertilizer levela Intensity
Aus Aman Score (kg NJha) score
Modern
Modern
Local
Fallow
Modern
Local
Local
Fallow
Modern
Local
Modern
Modern
Fallow
Local
Fallow
Local
aIf at recommended fertilizer level, NFERT (nitrogen fertilizer) percentage
score for the individual plot is 100.

Table 3. Correlation matrix used to score adoption at Kainalganj study site,
Bangladesh (1989-90).
Parameter Timing Varietal Intensity Fertilizer
sequence (NI
Varietal sequence 0.1922
Intensity -0.0007 0.6515**
N fertilizer -0.0878 0.0718 0.0552
Total
production -0.0287 0.4749** 0.5543** 0.1872
per hectare
Varietal sequence 0.2942"
Intensity -0.0957 0.8028**
N fertilizer -0.0129 0.1131 0.1154
Total
production -0.1036 0.4776** 0.5543"" 0.1886
per hectare
**significant at < 1 % level. "significant at l % level.

Table 4. Correlation illatsix used to score adoption at Sitakund study site,
Bangladesh (1 989-90).
Parameter Timing Varietal Intensity Fertilizer
sequence (N)
Varietal
Intensity
N fertilizer
Total
production
per hectare
Varietal
Intensity
N fertilizer
Total
production
per hectare
**significant at < 1 % level. '"significant at 1 R level.

Table 5. Distribution of households according to extent of adoption in two rainfed
sites, Bangladesh (1 989-90).
Extent of Kamalganj Sitakund
adoption
No. of % of total No. of % of total
households households households households
Low 18 20 10 18
Medium 47 54 3 0 56
High 23 26 14 26
Total 8 8 100 54 100

-
Table 6. Socioeconomic characteristics of households according to extent of adoption in two rainfed sites, Bangladesh
(1 989-90).
Socioeconomic
characteristic
PP-
Family size (no.)
Consuming unit (no.)
Economic unit (no.)
Age of respondent (yr)
m
l Farm size (ha)
Marginal farms (%)
Small farms (%)
Medium farms (%)
Large farms (%)
Animal power (no. )
Education level
Kamalganj Sitakund
Low Medium High All Low Medium High All
6
5
4
4 8
1.10
2
8
10
-
0.90
Primary
6
5
4
46
0.95
3
3 0
19
1
1 .oo
Primary
6
5
5
4 8
0.83
6
13
8
-
1.10
Primary
6
5
4
47
0.95
11
5 1
3 7
1
1 .oo
Primary
9
8
6
53
1.03
4
6
9
-
1.80
Primary
7
6
4
49
0.70
16
2 8
l l
-
1.90
Primary
6
5
3
50
0.49
13
9
4
-
1.50
Primary
7
6
4
50
0.70
3 3
43
24
-
1.78
Primary

Table 7. Ordinary least squares estimates of factors influencing the decision
to adopt modern rice technologies in two rainfed sites, Bangladesh (1989-
90).
Variable
Constant
Farm size (ha)
Economic unitlha
Animal powerlha
Age of the owner (yr)
Experience in farming (yr)
Education of respondents
% sharedlrented land
Loan receivedlha
~2
F ratio
D.F.
Estimates with standard errors
Kamalganj Sitakund
***significant at < 1 % probability level. **significant at < 5 % probability
level. *significant at 10% probability level. ns=not significant. Figures in
the parentheses indicate standard errors.

Table 8. Extent of adoption and average rice yield (kglha) in two rainfed sites,
Bangladesh (1989-90).
Kamalganj Sitakund
Extent of
adoption Aus Aman Total Aus Aman Total
Low
Medium
High
Low
All
Medium
High
AI l

Table 9. Extent of adoption and comparison of yield differences at two rainfed sites,
Bangladesh (1989-90).
Extent of Kamalganj Sitakund
adop tionl
comparison Aus Aman Total Aus Aman Total
Between
low and medium
Between
medium and high
Between
low and high
Between
low and medium
Between
medium and high
Between
low and high
**significant at < 1 % level. "significant at 5 % level. ns=not significant.

Table 10. Resource use and productivity according to extent of adoption in two rainfed
sites, Bangladesh, aus + aman (1989).
Resource use/ Kamalganj Sitakund
productivity
measure Low Medium High Low Medium High
Labor (h) 1,330 1,417 2,072 1,285 1,980 2,207
Family 1,048 1,139 1,748 1,041 1,642 1,625
Hired 282 278 3 24 244 338 582
Animal (h) 538 525 623 193 306 292
Family 524 504 606 136 3 65 189
Hired 14 2 1 17 5 7 4 1 103
Fertilizer (kg)
N 29 54 76 38 72 94
P2°5 14 23 3 1 4 6 9
Yield (kg) 4,410 4,882 5,537 1,814 2,627 3,254
Gross return (taka) 25,018 27,692 31,206 13,269 18,209 20,548
Total cost (taka)
Full cost 10,671 12,000 15,572 10,477 16,201 18,114
Cash cost 2,287 3,281 3,196 2,688 3,552 6,152
Production cost (takalkg)
Full cost 2.41 2.45 2.81 5.77 6.16 5.56
Cash cost 0.5 1 0.67 0.57 1.48 1.35 0.89
Net return (taka)
Full cost 14,347 15,692 15,634 2,792 2,008 2,134
Cash cost 22,731 24,411 28,010 10,581 14,647 14,096
Returns to (taka)
Family labor 3.74 3.75 2.79 1.70 1.67 1.5:
Hired labor 11.18 12.29 10.65 5 .OO 3.24 2.2:
Animal draft labor 5.44 5.98 5.18 21.79 16.35 3.2
Material inputs 19.09 9.89 11.60 11.08 6.14 4.3

Table 11. Resource use and productivity according to extent of adoptiofi in two rainfed
sites, Bangladesh, aus + aman (1990).
Resource use1 Kamalganj Sitakund
productivity
measure Low Medium High Low Medium High
Labor (h)
Family
Hired
Animal (h)
Family
Hired
Fertilizer (kg)
N
p205
Yield (kg)
Gross return (taka)
Total cost (taka)
Full cost
Cash cost
Prod cost (takalkg)
Full cost
Cash cost
Net return (taka)
Full cost
Cash cost
Returns to (taka)
Family labor
Hired labor
Animal draft labor
Material inputs

Table 12. Extent of adoption and differences in economic factors in two rainfed sites, Bangladesh (1989-90).
Economic
factor
Aus 1989
Gross return (takalha)
Total cost (taka/ha)
Net return (takalha)
Aman 1989
Gross return (takalha)
Total cost (takalha)
Net return (takalha)
Aus + aman 1989
Gross return (takalha per yr)
Total cost (takalha per yr)
Net return (takalha per yr)
Aus 1990
Gross return (takalha)
Total cost (takalha)
Net return (cakaiha)
Aman 1990
Gross return (takalha)
Total cost (takalha)
Net return (takatha)
Aus + aillan 1990
Annual gross return (takalha)
Annual total cost (takalha)
Annual net return (takalha)
Kamalganj Sitakund
Low and Medium Low and Low and Medium Low and
medium and high high medium and high high
"** si~nificant at < I '% level. ** sigiificant at 5% level. * siznificant at 10% level. ns = not significant.

Table 13. Summary of whole-farm cash flow according to extent of adoption in two rainfed
sites, Bangladesh (1989-90).
Income1
expenses
Total income (taka) 45,056
Farm income 26,207
Nonfarm income 18,849
Total expenses (taka) 44,609
Farm expenses 4,627
Household expenses 39,982
Cash balance (taka) 447
Total income (taka) 42,668
Farm income 21,666
Nonfarm indome 21,002
Total expenses (taka) 41,951
Farm expenses 7,221
Household expenses 34,730
Cash balance (taka) 7 17
Cash balance (1989 + 1990) 1,164
Kamalganj Sitakund
Low Medium High Low Medium High

Table 14. Summary of per hectare cash flow according to extent of adoption in two
rainfed sites, Bangladesh (1989-90).
Income1
expenses
Total income (taka) 40,959
Farm income 23,824
(58 %)
Nonfarm income 17,135
(42 %)
Total expenses (taka) 40,553
Farm expenses 4,206
(10%)
Household expenses 36,347
(90%)
Cash balance (taka) 406
Total income (taka)
Farm income
Nonfarm income
Total expenses (taka)
Farm expenses
Household expenses
Cash balance (taka)
Cash balance (1 989 + 1990)
Kamalganj Sitakund
Low Medium High Low Medium High

1. Target area delineation of rainfed lowlands for two rice cropping systems (aus-t.
aman), Bangladesh.

IRlPACT OF FARMING SYSTEMS RESEARCH ON SELECTED FARMERS IN
MIDHILLS OF NEPAL: A CASE STUDY OF PURlDI BHUMDI
S. B. h.lathemal, K. D. ~oshi~, and J. KC'
The Phumdi Bhumdi farming systems research site has been in
operation for a number of years and has developed significant
technologies for the farmers in the area. Extensive use of the
technology has been documented during the last 15 yr. The study to
measure the impact of the farming systems program on the
productivity of different farm enterprises and farmers' income at the
site revealed that intervening farmers adopted recommendations both
in the upland as well as the lowland areas and overall there has been a
positive impact, particularly in relation to nutrition aspects. The
educational profile of the children at the site is also encouraging.
To implement a systems approach, the Department of Agriculture (DOA) initiated
a cropping systems program (CSP) in 1977 with support from the Integrated Cereals
Project (ICP) funded by the United States Agency for International Development
(USAID). The objective of the CSP was to evaluate station-generated technologies
in terms of agronomic and socioeconomic performance and to develop
modifications under specific production systems used by fdarmers in the hills and
terai.
To integrate different components of Nepalese farming systems into on-farm
research, the Farming Systems Research and Development Division (FSRDD) was
established in 1985 under the National Agricultural Research and Services Centre
(NARSC). To give emphasis to hill agriculture, hill CSP sites (including Pumdi
Bhumdi) were retained by the FSRDD and farming systems research (FSR) was
carried out at these sites. In 1990, the FSRDD was renamed the Central Farming
Systems and Outreach Research Division (CFSORD) and given the mandate to
coordinate station-managed outreach research.
Little attention had previously been given to measuring the in~pact of
research programs (including FSR) on agricultural development. This study
attempted to determine the impact of FSR on selected hill farmers. The research
was conducted at the Pumdi Bhumdi FSR site by the Central Socio-Economic
Research Division (CSERD) in collaboratiol~ with the CFSORD.
'central Socio-Economic Research Division, Nepal.
2~entral Farming Systems and Outreach Research Division, Nepal.

OBJECTIVES
The objective of this study was to measure the impact of the farming systems
program (FSP) on the productivity of different farm enterprises and on farm
incomes in Pumdi Bhumdi. The specific objectives were to describe the ethnohistory
and the existing situation at the Pumdi Bhumdi FSR site; evaluate the adoption of
the recommended FSR technologies by farmers; assess the impact of the FSR
recommended practices on crop yields, forage and fodder production, and milk
production; evaluate the changes in nutritional and educational aspects of the
monitored farm families; study the role of agricultural support services in the
transfer of FSR recommended technology to farmers; determine the links between
the agricultural support services, farmers, and the FSR site coordinator; and identify
constraints to adoption of recommended FSR technologies.
JUSTIFICATION
Many researchers, administrators, and policymakers argue that in spite of heavy
investment in agriculture, there has been little impact on farmers. A few researchers
have attempted to measure the impact of the FSR program, but they have
concentrated only in the Terai region.
Technology transfer from one site to another in the hills is a challenge
because of the enormous variability in agroecological and socioeconomic conditions
of the farmers. Because of the heterogeneity of the farming systems in the hills,
technologfi has had an impact only in some areas. However, assessment of the
impact of technology on hill farmers has been virtually neglected. This study
attempted to determine the degree of adoption of recommended FSR technologies
by the hill farmers of Pumdi Bhumdi.
METHODOLOGY
To achieve these objectives, the study conducted a before and after survey and
monitored six intervened and six control farmers. The criteria for selection of these
farms included representativeness within the farm-size class, but with the provision
that milking buffalo shoulcl be present on the farm.
Site selection
Extensive farm monitoring on a whole-farm basis was carried out In 1984 at the
Pumdi Bhumdi FSR site. This site was proposed for the impact study for several
reasons. First, when the CSP began in 1977, cropping systems research (CSR) was
initiated at this site. The CSP was followed by the FSR approach in 1985. Therefore,
on-farm research had been conducted continuously at this site for the last 13 yr.
Second, Pumdi Bhumdi was representative of the western midhills of Nepal. Third,
secondary data were available for the site from the previous work of the CSP and

new information collected during FSR work. Fourth, Pumdi Bhumdi was accessible
by road at all times of the year.
Farmer selection
Before monitoring, 18 representative farmers were selected principally on the basis
of their landholding (from 0.5 ha to 2.5 ha). The smallest farms (< 0.5 ha) and the
largest (>2.5 ha) were excluded to ensure that the farms best represented
conditions at Pumdi Bhumdi. Of the 18 farmers, 12 farmers were selected to
optimize resource use and focus on the crop-livestock activities on the farm. These
farmers were divided into two groups. The FSR activities were concentrated in six
farms and included detailed monitoring of existing farming activities. The remaining
six farms were only monitored for their existing farming activities and included no
intervention. The group of farms with FSR activities was the intervened group and
the group with no farming intervention was the control group.
The main criteria used to select representative farmers in each group were
representativeness of the farm-size class; representative percentage of lowlands and
uplands to be able to select farms with mixed land types (at least 20% of each land
type); presence of kllarbur-i (pasture land) on which to plant fodder trees;
representative number of milking animals (female buffaloes or cows);
representative number of family members involved in full-time agriculture; and
representative number of those willing to cooperate with the FSR program.
The differences between the intervened and control farmers were as follows:
B The intervened farmers participated and collaborated in the on-farm trials of
the FSR program at the site; whereas, the control farmers neither
participated nor collaborated in the on-farm trials;
B ?'he intervened farmers were provided with free inputs (e.g., improved seeds,
chemical fertilizers, insecticides, and pesticides) for the trials conducted by
the FSR program. The performance of these trials was closely monitored and
supervised by the FSR staff. These trials were mainly managed by the
researchers with the assistance of the intervened farmers. The control
farmers did not have access to free inputs from the FSR program and their
existing farming activities were monitored without any intervention.
B The intervened farmers were provided with technical services, training, and
advice on improved farming practices. The control farmers did not have
access to these inputs. They learned about improved methods of cultivation
and other FSR reco~nmended components (i.e., seeds and technical services)
from their neighbors.

B
The intervened farmers were approached frequently by the FSR staff;
whereas, the control farmers were approached occasionally by the FSR staff
merely to monitor their existing farm~ng activities.
Data collection
Although some data and information were taken from previous studies of the CSP,
most of the data were collected from farm surveys and monitoring activities. Six
intervened farmers and six control farmers were interviewed in detail to determine
the degree of adoption of FSR recommended technologies. Site descriptions were
based on secondary data collected from various sources.
Analytical techniques
A number of variables were used to measure the impact of FSR at Pumdi Bhumdi.
To compare the before and after situations, cropping patterns, crop production,
livestock enterprises, fodder and forage production, vegetable-based cropping
patterns, and nutritional aspects were considered. However, no specific analytical
technique was used because of the limited sample size. The collected data were
compiled, and averages and percentages were computed.
Site description
lsir~lntion. Pumdi Bhumdi is located in the western midhills about 208 km
Exist west it'b o Kathmandu (Fig. 1). It lies on the side of a hill whose elevation varies from
750 to 1270 m. Average annual rainfall at the site is 4,000 mm. Crops are damaged
by hail during both spring and fall. The total area of Pumdi Bhumdi is
approximately 2,500 ha, and the cultivated area is about 1,012 ha. The total
population in 1990 was 5,610. There are approximately 1,047 families and an
average household has 5-6 family members who subsist on about 0.87 ha of
cultivated land. A family has an average of three members available for farm labor.
The existing farming systems and the interactions between different farm
enterprises are shown in Figure 2. This figure shows that crops and livestock are an
integral part of farming and that off-farm factors play an important role in
supporting farming activities. The major cropping patterns during 1979 are also
shown. In the lowland area, rice-based cropping patterns were the most common;
whereas, in the upland area, maize-based cropping patterns were predominant.
The survey resu!ts showed that the fertile upland areas have this
predominant cropping pattern: maize intercropped with soybean followed by a relay
crop of finger millet and a winter crop of wheat, mustard, or barley. The survey also
showed that 51% of the upland area was devoted to triple cropping, 43% to double
cropping, and only 2% to single cropping. In contrast, 55% of the lowland areas are
devoted to a single crop of rice and 24% to maize - rice - wheat (DOA 1980). An

average family owns seven heads of livestock. The average number of livestock per
family was 1.7 buffaloes, 0.6 bullocks, 0.1 cows, 0.8 calves, 1.6 sheep and goats, 2.4
poultry, and 0.1 pigs (DOA 1980). A significant characteristic of Pumdi Bhumdi is
the high percentage of farmers who do not own bullocks, which explains the power
constraint faced by farmers during land preparation.
Etllnollistoty of rlle sire. The settlement site was originally a dense forest. The
site was inhabited by different ethnic groups. The Brahmins were numerically the
dominant caste. Other castes who resided in the area were the Gurungs, Damaies,
and Kamis. These castes migrated to this area many years ago. Agriculture was the
main occupation and livelihood of the people. The primary objectives of farming
were to provide adequate food for subsistence and to save some seed for the next
season.
Farmers at the site faced various problems. It was reported that there were
hailstorms in 1948, 1949, 1979, and 1991. The hailstones were as big as pears. As a
result, famine and diseases spread during these years. Farmers were compelled to
borrow money at high rates of interest.
The migration rate seemed to be higher than the immigration rate. Few
people, especially those of lower castes from the districts of Syangja and Baglung,
immigrated to the village in search of employment. Because of various internal
reasons (e.g., land problems and the exhaustion of natural resources), most of the
villagers migrated to the terai (mainly in the districts of Chitwan, Ranke, and
Nawalparasi). The external factors that influenced migration from the villages were
better employment opportunities available in terai, cheaper land, and better
facilities for education, communication, transportation, and other infrastructure.
Before the FSR program was initiated, the CSR program was launched in
1977-78 to improve the socioeconomic conditions of the farmers. The main role of
the CSP was to increase the yield of various crops by introducing improved varieties
and new technologies at the local level. The CSR introduced some improved crop
varieties (e.g., the Taichung-176, CH-4.5, and Khumal-3 varieties of rice; the Arun-2
and Khumal Yellow varieties of maize; the RR-21 and UP 262 varieties of wheat;
and the Kufri Jyoti varieties of potato). The cultural practices introduced were
mainly improved methods of making ridges, efficient ways of weeding, line planting,
application of chemical fertilizer, and mulching.
During the CSP period, triple-cropping of rice - wheat - maize (R-W-M) was
introduced in lowland areas where farmers'practiced rice - fallow - fallow (R-F-F).
Most farmers in both groups reported that they started to use chemical fertilizers
only after CSP was introduced. After CSP was terminated, FSK began in 1985. In
addition to crop varieties, the FSR program introduced new technologies for other
components of the farming systems (e.g., vegetables, forage, and fodder).
The introduced varieties included Khumal-3 (1985), Khumal-4 (1985),
Khumal-5 (1986), Khumal-7 (1987), and Khumal-9 (1987) varieties of rice; Arun-4
(1985), Manakamana- l and 2 (1987) varieties of maize; HS-94 (1985) and

Annapurna-l (1986) varieties of wheat; and Cardinal, a potato variety. In addition,
the kitchen gardening program was initiated and farmers were convinced to
establish year-round kitchen gardens near their houses. Other activities introduced
by FSP were improved methods of composting, application of pesticides, storage of
seeds in improved metal bins, and storage of potato in locally made bamboo
baskets.
Description of fanners. The personal characteristics of the intervened and
control farmers are given in Tables 1 and 2. The age of intervened farmers ranged
from 35 to 63 yr. Two of the farmers had attended school for 6 and 10 yr. Average
family size was 8, and the number of adults was between 1 and 5 per household. Of
the 6 farmers, 2 were owners-cum-tenants and 4 were owners.
The ages of the control farmers were between 36 and 50 yr, and one had 8 yr
of schooling. Family size ranged from 5 to 8 with an average of 7 members. The
number of adults was between 1 and 3 per household. Of the 6 farmers, 2 were
owners-cum-tenants and 4 were owners.
Frtrtlz clzaructeri.~tics. The farm characteristics of intervened and control farms
are presented in 'Tables 3 and 4. The average size of land owned by both groups of
farmers was nearly the same (0.96 ha intervened; 1.05 ha control). However, the
average area of cultivated land owned by the control farmers was slightly higher
(0.90 ha compared with 0.77 ha). The average size of lowland area owned and
cultivated hy both groups of farmers was higher than that of the upland area. A
limited area of pasture land was owned by both groups. The average number of
parcels per farm for both groups was similar (9.67 and 9.17). The average parcel size
of intervened farmers was higher than that for control farmers (0.39 ha compared
with 0.12 ha).
FSR activities itztt-odlrced in the area. The following recommendations made
by the FSR program at Pulr~di Bhumdi were based mainly on the results of activities
carried out in the fields of intervened farmers from 1985 to 1990.
¤ Crops. On the basis of problems identified by researchers, farmers, and
extension workers at the site, component-based trials were conducted. These
included varietal trials, fertilizer trials, and other management studies of
various crops in farm fields. Components that gave promising results were
recommended for use by farmers. These promising components were
monitored on the basis of biological and socioeconomic factors (e.g.,
improvements in variety, fertilizer rate, and cultural practices).
H Livestock. Oats, Napier forage grasses, and ipil-ipil fodder trees were
introduced and studied for their adaptability in the area. Similarly, the
performance of some other indigenous fodder tree species was studied.

H Horticulture. To have a more regular supply of vegetables throughout the
year, a study of vegetable production in a kitchen garden was conducted at
the FSR site.
m Training program. To familiarize farmers with FSR technologies and
research methodologies, regular training was conducted at the FSR site.
Cropping patterns
IMPACT OF FARMING SYSTEMS RESEARCH
In 1984-85, the predominant cropping patterns in the lowlands were rice - fallow -
fallow (61 and 50% of the aggregated total area of the intervened and control farms,
respectively), rice - wheat - maize (13 and 21%), rice - fallow - maize (10 and 1470),
and other patterns (less than 1070) (Hawkins et al 1987). In 1988-89, after the
implementation of the FSR program at Pumdi Bhumdi, the cropping patterns used
were different.
In the lowland area, the predominant cropping patterns of the intervened
farmers were rice - wheat - maize, rice - fallow - fallow, and rice - barley - fallow. On
the control farms, the predominant cropping patterns were rice - wheat - maize, rice
- fallow - fallow, and rice - mustard - maize (Table 5). In the upland areas, the
predominant cropping patterns were maize/finger millet - wheat (71 and 73%),
maize/finger millet - mustard (20 and S%), and maize/finger millet - potato (5 and
16%) in 1984-85. These patterns were chan ed into maize/finger millet - wheat,
maize + vegetables - vegetables and maize7finger millet - mustard for both the
intervened and control farms.
FSR has played a positive role in changing the cropping patterns from rice -
fallow - fallow to rice - wheat - maize in the lowland areas and from maize/finger
millet - potato to maize + vegetables - vegetables in the upland areas. Changes in
the cropping patterns for the intervened and control farmers were identical both in
the upland areas and the lowland areas. This is because the changes used by the
intervened farmers were followed later by the control farmers.
Production
Table 6 presents the farm practices and annual production of the different crops in
the lowland and upland areas in 1984, and the productivity of the FSR-recom-
mended technologies in 1985-90. Table 7 presents the crop yields obtained by the
farmers in 1988-89. A comparison of the average crop yields of intervened and
control farmers shows a substantial increase in yield for rice and maize as a result of
the recommended practices. The increase in rice yield of intervened farmers was
43% more, and that of control farmers was 59% more. The yield was only 30%
more than the rice yield in 1984. In the case of maize, the increase in yield was 55%

more for intervened farmers and 4.6% more for control farmers. The yield was 54%
more than the yield of maize in the lowland areas in 1984. The yield potential of
improved maize varieties under well-managed conditions exceeds 5 t/ha . Given this
potential, the average yield of improved maize varieties obtained by the control
farmers (4.8 t/ha) was acceptable. In the case of wheat, there was no difference. In
mustard, the difference in productivity was very small. A comparison between the
two groups was not possible for the other crops because each group was growing
either the recommended varieties or local varieties.
In the upland area, improved varieties performed better than local varieties.
The average yield of the local variety of maize was higher than that of the
recommended variety. The yield difference between the two varieties of mustard
was not substantial.
The differences in productivity were not reflected in the overall productivity
of intervened farms compared with control farms. The reasons for this lack of
difference appeared to be the partial adoption of improved practices by control
farmers and the natural variation between the farms in each category.
Adoption of crop varieties
Both intervened and control farmers adopted improved crop varieties (Table 8).
Intervened farmers adopted three different improved rice varieties (Khumal-3,
Khumal-4, and Khumal-2); whereas, control farmers adopted two improved
varieties of rice (Khumal-3 and Khumal-2). Intervened farmers cultivated Khumal-2
on a 0.38 ha land, Khumal-3 on a 0.13 ha, and Khumal4 on 0.20 ha. The control
farmers planted Khumal-2 on 0170 ha and Khumal-3 on 0.40 ha.
The dominant improved maize varieties the farmers used were Khumal
Panhelo, Manakamana-1, and Arun-2. Intervened farmers planted Khumal Panhelo
on a 0.25 ha land, Manakamana-1 on 0.30 ha, and Arun-2 on 0.10 11a. The control
farmers planted Khumal Panhelo on 0.23 ha, Manakamana-l on 0.13 ha, Arun-2 on
0.03 ha, and Ganesh-2 on 0.03 ha. In the case of wheat, both intervened and control
farmers adopted only RR 21, which was cultivated on 0.7 ha and 0.4 ha, respectively.
Two varieties of improved mustard, Thulo Tori and Chitwan local, were each
planted on 0.13 ha by intervened farmers; whereas, only Chitwan local was planted
by the control farmers on 0.03 ha. The intervened farmers obtained seeds of
different crop varieties from the Pumdi Bhumdi FSR site while the control farmers
obtained improved seed varieties from their neighbors (intervened farmers), friends,
and relatives.
Despite the better performance of improved varieties under well-managed
conditions, the farmers in Pumdi Bhumdi did not extend their areas under improved
varieties for two main reasons: the higher risk of crop loss because of hailstorms
(improved varieties require more inputs, therefore losses would be higher); and

improved varieties require higher levels of inputs, \vIiich all farmers could not
afford. Both inputs and credit were not accessible to local farmers.
Livestock enterprises and milk production
The number of livestock owned by the monitored farniers is shown in Table 9. Both
intervened and control farms owned a higher number of female buffalo than other
animal species. These buffalo were often sold, exchanged, or lent when they were
pregnant or had young calves. Between 1984-85 and 1988-89, the number of buffalo
calves, sheep and goats, and bullocks increased. The average number of female
buffrllo, male buffalo, and co\vs were about the same, and all farmers raised local
breeds.
Milk production in Pumdi Bhumdi farms is an important source of income.
Between 1984-85 and 1988-89, the average amount of milk sold per year of
intervened farmers increased from 781 to 927 liters, while control farmers from 809
to 845 liters (Table 10). Because of this increase in milk sales, the average income of
intervened farmers increased by 74% and control farmers by 28%.
Fodder and forage production and livestock feeding
To reduce the deficit of animal feeds during the dry season, FSP introduced several
types of forage and fodder (e.g., oats, Napier grass, and ipil-ipil trees) at Pumdi
Bhumdi. Oats were tested in the cropping pattern in the lowland area, and Napier
grass and ipil-ipil fodder trees were planted on terrace edges and pasture lands.
Table l1 sho~~s that oats were not planted in the area before 1985. In 1988-
89, intervened farmers planted oats on a 0.03 ha land while control farmers to a
0.11 ha. FSR staff conducted the study on oat cultivation only in the fields of
intervened farniers. However, the control farmers observed the better performance
of oats and approached the Livestock Farm in Lamepatan, Pokhara, and intervened
farmers for oat seeds. Oats have been reported to yield 7-8 t green fodder/ha and
0.8-1.0 t seeds/ha, and feecling trials have indic:ited th:it milk production can be
increased by 0.35-0.5 liter/d if 6-8 kg fresh oat grass/d is added to the diet (Si~lgh
and Gautam 1980).
Farmers in Pumdi Bhumdi grow many varieties of fod(lsr. A numher uf
fodder saplings were distributed after the implementation of FSP. Table 13,
compares the number of trees and saplings before FSP and n~~ml~cr of trees and
saplings after FSP. There was an increase in the n~!rnber of fuddcr trees after the
implementation of FSP.

Ipil-ipil seedlings were distributed to both groups of farmers at the Pumdi
~humdi FSR site by the Livestock Farm in Lamepatan, Pokhara with the help of
FSR staff on-site. These seedlings were distributed to both groups not for trials but
as a service to the farmers. Technologies for ipil-ipil cultivation were provided by
the FSR staff to the intervened fariners only and performance was closely
monitored.
Plantations of ipil-ipil seedling gave mixed results in Pumdi Bhumdi. Ipil-ipil
planted in pasture land showed minimal growth, although its performance on
terrace edges was encouraging. Leucaena Ieucocephala could not be grown
successfully in the area. Leucaena diversifolia was tested in 1987 and found to give
good results. The general problems faced by farmers who grew ipil-ipil and Napier
grass along the terrace edges were shading of crops and reduced soil fertility (Table
13).
Vegetable-based cropping pattern
Before FSP, fariners usually grew vegetables in small areas during the winter season
and a few cucurbits in the inaize crops. After FSP was introduced, kitchen gardening
became well established and the farlners had a regular supply of vegetables
throughout the year. The most cominon vegetables were sponge gourd, beans,
pumpkin, bottle gourd, chilly, cauliflower, mustard, radish, cowpeas, snake gourd,
potato, carrot, brinjal , cucumber, garlic, and peas. The most common vegetablebased
patterns were maize/vegetables - vegetables and maize + vegetables -
vegetables (Table 14). Since the introduction of FSP, the area under vegetables had
also increased. The town of Pokhara is close to Pu~ndi Bhurndi; therefore, some
far~ners started to sell green vegetables in the inarket to generate cash income.
All intervened and control farmers grew vegetables mainly for home consumption.
Because of the consumption of vegetables, most far~ners had nutritious diets.
Furthermore, a few of the farmers had increased the number of buffalo, which
increased the quantity of milk and ghee. Those farmers who had more milk and
ghee, consumed milk and milk products, which further improved their nutritional
status.
Education and training
'I'he educational picture of Pumdi Bh~~mdi is encouraging. Although farmers had no
schooling, many of thein give priority to education. Most children of these farmers
are finishing secondary school and many are attending college. However, most
far~ners with higher education migrate to the towns and cities for other employment
(Foster 1990).

The types of the training provided to the farmers and their reactions to the
training are shown in Table 15. The intervened group of farmers attended more
training programs conducted by the FSP than the control farmers.
Effectiveness of other FSR activities
Most farmers in both groups said that they had replaced the traditional technology
with the improved technology introduced by the FSP. According to the farmers,
knowledge about the adoption of chemical fertilizers, improved seeds, im roved
fodder trees, and forage grasses took place only after the establishment o F the FSR
in their site. Participation of both groups in various FSR activities (e.g., pro ram
planning and decision making, selection of participant farmers, and training ", were
reported to be highly satisfactory. Farmers In both groups felt that their suggestions
and opinions in'solving the problems encountered during implementation of work
plans and selection of the recommended technologies were well considered by the
FSP.
However, both groups of farmers were not satisfied with the supply of inputs.
Three of the six intervened farmers and two of the six control farmers reported that
supplies of inputs by the concerned agency were insufficient and untimely.
ROLE OF OTHER SUPPORT-SERVICE INSTITUTIONS IN THE TRANSFER
OF FSR-IDENTIFIED TECHNOLOGY
Extension service in the area
The FSR and the Agriculture Development Office (ADO) have separate mandates
and targets. From 1985 to 1990 there was no extension agent assigned by the ADO
in the Pumdi Bhumdi area. The linkage between research and extension was good
but limited to training programs, participation in Samuhik Bhramnn
(multidisciplinary team visits), and working group meetings.
Credit supply
Cash was a limiting factor for inputs (e.g., seed, fertilizers, and pesticides) required
to adopt improved technology. However, credit to farmers was limited, and the
process was so complicated that farmers could not take advantage of this facility.
The Agriculture Development Bank (ADB) at Pokhara provided loans for
agricultural activities according to recommendations made by the ADO, Pokhara.

Input supply
The Agricultural Input Corporation (AIC) was responsible for supplying inputs to
the district headquarters while the cooperative societies and AIC dealers were
responsible for the villages. However, timely supply of the required amount and
types of seeds, fertilizers, and pesticides was always difficult. Pumdi Bhumdi was no
exception. There was one AIC dealer to sell the inputs for cash, but irregular and
insufficient supply of inputs was common.
Marketing
There was no established marketing system for agricultural products in the area.
However, the government-owned Dairy Develop~nent Corporation has a milk
collection center at Puindi Bhumdi. Therefore, farmers can sell their fresh milk
directly to this center for cash. The farmers have to find their own markets for other
commodities.
Links among farmers, the site coordinator, and other related institnt ions
The FSP at Pulndi Bhumdi sought to develop strong links with its line agencies at
the district level to provide FSR-based technical support. Table 16 su~nmarizes the
links between the Pumdi Bhumdi FSR site and the ADO, the Livestock Research
Farm, the Horticulture Research Farm, the District Forest Office (DFO), ADB,
AIC, the Lumle Agriculture Research Center (LARC) , and the cooperative.
The ADO provided resource persons to train the farmers, participated in
working group meetings and the Salnuhik Bhraman (multidisciplinary team visits),
and shared the responsibility of disseminating FSR-based technologies to other
areas of the district. The livestock and horticulture research farms had strong
coordination with the FSR program at Pumdi Bhu~ndi in the area of technical
support. They provided test materials for on-farm research in livestock, fodder,
forages, and vegetables.
The DFO, ADB, and the cooperatives had weak links with the Pumdi
Bhulndi FSR site. The involvement of AIC in the FSR was limited to the supply of
inputs through a dealer in the area. Coordination with LARC was n~aintained by the
exchange of ~nformation on research findings, meetings, and visits.
The FSR site office was active in identifying farm problems and in solving
these through close coordination with the different institutions in the district (Table
17). Among the institutions, ADO acted as the extension catalyst between farmers
and the FSR program. The linkage between the ADO and the farmers was close
because the ADO is responsible for dissemination of FSR-based technologies. AS an

extension agency in the district, the ADO played a vital role in strengthening the
FSR program and was aware of the importance of on-farm research.
The livestock services center at Pumdi Bhumdi was responsible for the
supply of fodder saplings, forage seeds, and primary health care for the animals. In
these areas, there was good understanding among the farmers, the livestock service
center, and the FSR site coordinator.
Finally, the FSR site coordinator and the farmers developed a close working
relationship and effective links and collaboration. These factors contributed to the
positive impact of the FSR-recommended technologies on farmers in Pumdi
Bhumdi.
Constraints to adoption of FSR-recommended technologies
The major problems in the adoption of FSR-recommended technologies were the
unavailability and untimely supply of inputs and lack of money to purchase the
inputs (Table 18). Other problems included were: more labor was required to adopt
the recommended cropping patterns and cultural practices; the late maturity and
low palatability of the recommended varieties (especially maize); more seed was
required for the improved varieties than for the local varieties; and there were more
diseases and insect problems during storage (especially maize and potatoes).
The majority of the control farmers reported that they did not have enough
technical knowledge of the recommended practices because they had no ready
access to the information. To acquire more knowledge on the recommended
technology, they had to visit the FSR site office. However, because of inadequate
time during the peak periods, they did not have the time to visit the FSR site office.
Some other constraints identified at the site were:
m The main climatic constraints to increased cropping intensity were occasional
drought and frequent hail storms.
H Limited technology was available for most of the crops (e.g., hill crops, grain
legumes, fruits, and vegetables) for on-farm testing which limited the
alternatives available to the farmers.
¤ Climatic constraints (hail and drought) have rnade agricult~lre
risky in this
region; therefore, farmers were hesitant to make larger investments in crops
(e.g., use chemical fertilizers or pesticides).

¤
Weak research-extension linkages and poor support services (availability of
credit and inputs, and marketing facility for agricultural products) have
limited the transfer of technology and its adoption by farmers.
Inadequate facilities (e.g., labor and physical facilities) for the FSR program
was a constraint in disseminating the technology to the farmers in the area.
CONCLUSION AND RECOMMENDATIONS
The results of this study are encouraging because they indicate that intervened
farmers adopted FSR-recommended cropping patterns both in the upland and
lowland areas. Most farmers adopted improved varieties of major crops and their
cultural practices. Vegetable cultivation became very popular among intervened
farmers, and they devoted land to grow various types of vegetables. Farmers
improved their nutritional status by consuming vegetables and generated cash
income from vegetable sale. Farmers also adopted FSR-recommended species of
fodder trees and grasses. The production and sale of milk increased substantially
because of the increase in the number of animals due to the availability of suitable
livestock fodder. Some control farmers have also adopted improved varieties of
crops and fodder trees. These farmers have adopted the maize + vegetable -
vegetables cropping pattern. These findings imply the suitability of the FSR
approach in similar environments in the country.
Based on the results of this study, the following recommendations are
proposed to improve the economic conditions of hill farmers:
¤ An FSR approach should be stressed in the development of all the major
components of farming systems (e.g., crops, livestock, horticulture, and off-
farm employment). A focus on only one component will cause imbalances.
¤ There is a need to develop intercommodity and interdisciplinary links within
the research system to integrate different components within FSR.
II Research and extension should have joint responsibility to achieve the targets
of FSP to make the impact of FSR more effective.
¤ Agricultural inputs (e.g., improved seed, chemical fertilizer, credit, and
extension services) must be made available on time, at the proper locations,
and in sufficient quantities to ensure the adoption of improved technology.
6 Close linkages among research, extension, and other related institutions
should be established for effective transfer of FSR-recommended technology
to the farmers.

m Extension and other production-support services (e.g., inputs and credit)
should be oriented toward the promotion of a farming systems approach to
agricultural development.
m Production programs with FSR-based technology should be encouraged and
implemented. They should be started in hilly areas where the dissemination
of recommended technology is both feasible and acceptable to farmers.
m An integrated package of practices for planting, harvesting, and marketing is
also needed for major fruits and vegetables identified for cultivation in the
hills.
Increases in livestock production and productivity depend primarily on the
enhancement of feed and fodder supply. Large-scale plantrng and proper
maintenance of fodder trees and good pasture management are needed.
Stall-feeding should be encouraged and free-grazing should be controlled.
Farm manure is required in large quantities to increase the productivity of
cereal and horticultural crops, but ~ts supply depends on increased
production of fodder in hill areas.
m Some constraints identified at the site (e.g., limited technology for hill crops,
lack of infrastructure, a poor input-supply system, and lack of irrigation) must
be overcome if FSR programs are to be fully adopted and their irnpact
magnified.
REFERENCES ClTED
DOA--Department of Agriculture (1980) Cropping systems and livestock surve .
Division of Agronomy, Department of Agriculture, Nepal. (unpublished{.
Foster J H (1990) Evaluation of FSR/Nepal Impact Study. (unpublished).
Hawkins R C et a1 (1987) Farm monitoring in Pumdi Bhumdi: summary and
conclusions of a farming systems research strategy. Farming Systems
Research and Development Division, Nepal.
Singh B K, Gautam Y P (1986) Oat cultivation and its use as a green fodder for
increasing buffalo milk production. Pages 463-477 ill Proceedings of the 2nd
Monitoring Tour of Crop-Livestock Systems Research, Nepal and Indonesia,
International Rice Research Institute, Manila, Philippines.

Table 1. Personal characteristics of the intervened group of farmers, Pumdi Bhumdi, Kaski District, Nepal (1988-89).
Characteristics Farm A Farm B Farm C Farm D Farm E Farm F
Age of the
respondent (years)
Education (grade)
Family size (No.)
Male adults (No.)
Female adults (No.)
Children (No.)
Tenure status Ownercumtenant
*
Data not available.
Owner- Owner Owner Owner Owner
cum-
tenant
Table 2. Personal characteristics of the controlled group of farmers, Pumdi Bhumdi, Kaski District, Nepal (1988-89).
Characteristics Farm G Farm H Farm I Farm J Farm K Farm L
Age of the
respondent (years) 50 48 36 46 44 3 8
Education (grade) * * 8 * * *
Male adults (No.) 1 3 2 1 1 1
Female adults (No.) 2 3 3 2 2 1
Children (No.) 4 1 1 4 5 3
Tenure status Owner- Owner- Owner Owner Owner Owner
cum- cum-
tenant tenant
*Data not available.

Table 3. Farm characteristics of the intervened group of farmers, Pumdi Bhumdi, Kaski District, Nepal (1988-89)
Characteristics Farm Farm Farm Farm Farm Farm Average
A B C D E F
- - P
Owned area (ha) 0.85 0.48 1.11 0.74 1.23 1.35 0.96
Lowland (ha) 0.57 0.14 0.58 0.34 1.07 0.62 0.55
Upland (ha) 0.23 0.09 0.31 0.19 l. l0 0.23 0.36
Pasture land (ha) 0.05 0.25 0.22 0.2 1 0.06 0.50 0.22
Cultivated land (ha) 1.10 0.23 0.89 0.53 1.17 0.82 0.77
Lowland (ha) 0.91 0.14 0.58 0.34 1.07 0.59 0.61
Upland (ha) 0.19 0.09 0.3 1 0.19 0.10 0.23 0.18
No. of parcels 8.00 5.00 13.00 7.00 10.00 15.00 9.67
Average parcel size (ha) 0.12 0.09 0.08 0.10 0.12 1.81 0.39
Table 4. Farm characteristics of the controlled group of farmers, Pumdi Bhumdi, Kaski District, Nepal (1988-89).
- -
Characteristics Farm G Farm H Farm I Farm J Farm K Farm L Average
Owned area (ha)
Lowland (ha)
Upland (ha)
Pasture 1m.d (ha)
Cultivated land (ha)
Lowland (ha)
Upland (ha)
No. of parcels
P

~ .-
*Data not available.
. .- , ..~ -. .. . -
Table 5. Cropping patterns practiced by the farmers in Pumdi Bhumdi in 1984-85 (before FSR) and 1989 (after FSR).
Intervened group
(1984-85)
Lowlands
Rice - F - F (61%)
R - wheat - maize (13%)
Rice - F - maize (10 %)
Uplands
MaizeIFM - wheat
MaizeIFM - mustard
MaizeIFM - potato
Controlled group Intervened group
(1984-85) (1989)
Controlled group
(1989)
Rice - F - F (50%) R - wheat - maize Rice - wheat - maize
R - wheat - maize Rice - F - maize
(2 1 %)
Note: F = fallow; FM = finger millet; and Veg. = vegetables.
Rice - F - F
Rice - F - maize Rice - barley - fallow Rice - mustard - maize
(14%)
MIFM - wheat (73 %) MaizeIFM - wheat
(71 %)
MaizeIFM - wheat
MIFM - mustard (8%) Maize + vegetables + veg. Maize + vegetables
(20 %) + veg.
MIFM - potato (16%) MaizeIFM - mustard MaizeIFM - mustard
(5 %)

Table 6. Farm practices and production levels before FSR (1984) and potential of FSR recommended technology at Pumdi Bhumdi (1985-90).
-
Cropping patterns
Lowlands
Rice - wheat - maize
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
Rice - fallow - maize
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
Rice - wheat - fallow
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
Rice - fallow - fallow
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
Uplands
MaizeIF. millet - wheat
Grain yield (tlha)
Variety
Fertilizer (NP kglhaj
MaizeIF. millet - potato
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
MaizeIF. millet-mustard
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
Maize + vegctablc - vegetable
Grain yield (tlha)
Variety
Fertilizer (NP kglha)
Farm practices and average FSR recommended technology and potential
grain yield (tlha) in 1984 grain yield (tlha) in 1985-90
Crop 1 Crop 2 Crop 3 Total Crop l Crop 2 Crop 3 Total
4.7
Arun 4
40:20
3.5
Mana- l
40:20
3.4
Mana- l
40:20
1.1 2
Local RR 21
0 40:20
1.1 15 19.6
Local Cardinal
60:30
1.2 0.5 5.1
Local Chitwan L.
20:20

Table 7. Average productivity of different crops in different land types at Pumdi Bhumdi. Nepal (1988-89).
Lowland Upland
Improved varieties Local varieties Improved varieties Local varieties
Description Intervened Controlled Intervened Controlled Intervened Controlled Intervened Controlled
farmers farmers farmers farmers farmers farmers farmers farmers
Rice
Grain yield (tha) 2.7 3.3 1.9
Straw yield (tha) 3.1 2.7 3.3
Wheat
Grain yield (tha)
Straw yield (tha)
Maize
Grain yield (tha) 1.5 4.9 1 .O 1.2 1.6 1.3 2.9 1.6
Straw yield (tha) 3.3 10.5 3 .O 2.7 4.4 3.8 4.7 4.9
Oat
Fodder yield (tha) * 5.6 *
Mustard
Grain yield (th) 0.1 * 0.2 *
Straw yield (tlha) 1.4 * 1.4 *
Barley
Grain yield (tha)
Straw yield (tha)
Potato
Tuber yield (tha)
Lentil
Grain yield (tha) * 0.29 *
Straw yield (tha) * 0.28 *
Finger millet
Grain yield (tha) * * 2.0 2.2
Straw yield (tha) * * 6.9 7.0
* Farmers growing either recommended varieties or local varieties.

Table 8. Major crops, crop varieties, and area grown by intervened and controlled farmers at Pumdi Bhumdi, Nepal (1990-91).
Improved variety Local variety
Crops Name of variety Area No. of Variety Name of No. of Total
(ha) grower introduced variety grower area
farmers by (ha)
Intervened
Ricc FSP
CSP
FSP
Maize Khumal yellow
Manakamana- l
Arun-2
Wheat
Mustard
Finger millet
Controlled
Rice
Chitwan local
Thulo Tori
Maize Khumal yellow
Manakamana- l
.4run-2
Ganesh-2
Wheat
Mustard
F. millet
CSP
FSP
FSP
Marshi pahelo
Gurdi pahclo
Sano pahelo
Sano Seto
CSP Sano Seto
FSP
FSP
Sano Seto
Sano Tori
Okhale CSP Khalso ,md Dallc
KR-2 1
Chitwan Local
Okhale
FSP'
CSP
FSP
CSP
FSP
FSP
L ARC
CSP
FSP
CSP
Marshi pahelo
Gurdi pahelo
Sano pahelo
Sano seto
- ' --. Pm - C-,-nnino ~\,~trmq nroicct: LARC = Lumle Agricultural Research Center.
Sano Seto
Sano Tori
Kl~also & Dalle

Table 9. Number and types of livestock owned by the monitored farmers, Pumdi Bhumdi, Kaski District (1988-89).
Types of
Livestock
Male buffalo
Female buffalo
Cows
Bullocks
Buffalo calves
Sheep and goats
Chickens
Others
Average
number/
farm
Intervened farm Controlled farm
Types of
breeds
Local
Local
*
Local
Local
Local
Local
*
a~ses:
1 = for home consumption, 2= for exchange, 3 = for sale.
*Data not available.
Average
breeds
Types of
brceds
Local
Local
Local
Local
Local
Local
Local
*
Breeding
1+2+3
1
1+2+3
1
1 +3
1
*

Table 10. Production and use of milk by monitored farms, Pumdi Bhumdi, Kaski District, Nepal
(1984-85 and 1988-89).
Milk production and
activities
Intervened Controlled
farm farm
1984-85 1988-89 1984-85 1988-89
Average milk sale (liter) 78 1 927 809 845
per farm
Average income (NPR)/farm 4,725 8,215 5,153 6,560
Table 11. Fodder and forage production at Pumdi Bhumdi, Kaski District, Nepal (1988-89).
Name of the fodder/ Average farm area Average farm area
Types of farms forage grass before FSP (ha) after FSP (ha)
Intervened Napier grass
Oats
Controlled Napier grass * 0.06
Oats * 0.11
* Data not available.

Table 12. Number and types of fodder trees grown by the farmers at Pumdi Bhumdi, Kaski District, Nepal
(1988-89).
Types of farms Name of
before FSP
Number added during -
FSP
fodder tree Tree Sapling Tree Sapling
Intervened
Controlled
* Data not available.
Badhar
Pakhuri
Birulo
Kabro
Chuletro
Ipil-ipil
Kutmiro
Others
Badhar
Pakhuri
Birulo
Kabro
Chuletro
Ipil-ipil
Kutmiro
Others

Table 13. Major problems and constraints to growing fodder trees and forage grasses, Pumdi Bhumdi, Nepal
(1990-91).
Fodder trees Forage grasses
Serial Typesa Intervened Controlled TypesC ' Intervened Controlled
No. of farmy farmer of farmer farmer
problems (FH) (FH) problems (FH) (FH)
1 3,4 4 3 2,3 5 4
3 1,4 0 2 173 0 1
al- except for grass and firewood, little use for other purposes; 2- quantity of rass from trees is less than local trees;
3- shadow effect on crops; and 4- difficult to protect from grazing animals. bg~~-frequency of households. '1-lack
of market for surplus production; 2-low crop yieIds due to shadow effect; and 3-low crop yields because it exploits
fertilizer.

Table 14. Impact of FSR on vegetable production in kitchen gardens, Pumdi Bhumdi, Kaski District, Nepal, 1988-89.
Types of farms Vegetable species Cropping pattern Area (ha) Cropping pattern Technology adopted
before FSP after FSP
Intervened A sponge gourd, bean, Change in vegetable
pumpkin, bottle gourd
chilly,
MIFM-Veg. 0.04 M +Veg. -Veg. production technique
B Cauliflower, mustard,
radish, chilly. * 0.013 M +Veg.-Veg.
Improved seed
Compost use
C cauliflower, radish,
bean, cowpea. MIFM-Veg . 0.06 M/Veg.-Veg.
Improved varieties
D sponge gourd, snake- Establishment of
E
gourd, pumpkin.
winter vegetables +
MIFM -Veg. 0.04 M +Veg. -Veg. kitchen garden
More varieties
potato, summer veg. MIFM -Veg. 0.06 M+Veg.-Veg.
,
VI
W
F Cauliflower, carrot,
radish, mustard leaf MIFM-Veg. 0.025 MIFM-Veg .
Improved variety,
nursery
I
Controlled G radish, mustard, ' Application
brinjal MIFM-Veg. 0.01 MIFM-Veg. of compost
H sponge gourd, cucum- Improved variety,
ber, pumpkin, radish. MIFM -Veg. 0.026 MIVeg . -Veg. nursery
I cauliflower, pumpkin, Use of compost and
mustard leaf, garlic. MIFM -Veg. 0.019 MIVeg. -Veg. improved practices
J leafy mustard, pea, Increased vegetable
potato MIFM -Veg. 0.023 M +Veg. -Veg. growing area
K leafy mustard, bean, Improved varieties
sponge gourd, potato. MIFM -Veg. 0.06 M+Veg.-Veg.
L summer vegetables, Increased cropping
winter vegetables. MIFM -Veg. 0.014 M +Veg. -Veg. intensity
Note: M = maize; FM = finger millet; and Veg. = vegetables.
- - -

Table 15. Training undergone by the farmers and their rating of its usefulness, Pumdi Bhumdi,
Nepal (1990).
Intervened Controlled
Types of farmers usefulnessb farmers usefulnessb
traininga (FH) (FH)
al- kitchen gardening; 2- crop management; 3- livestock fee lng, fodder, and health management;
4- mushroom cultivation; and 5- poultry bird management.' 1- very useful; 2- useful; and
3- not useful. Note: FH - frequency of households.

Table 16. Links of the farming system research program to different organizations.
Kinds of links/ Technical Provincial Supply of inputs Participation Extension
organizations resource and materials in WGM and activities
person Group treck
ADO
Livestock
Research Farm
Horticulture
DFO
ADB
AIC
LARC
Cooperative
Review (2)
research (2)
Review -
research results
Farmer
Trainors (2)
Fodder and
forage
(2)
Seeds
Tree saplings
(1)
Loan to
needy farmers
(1)
Seeds, inputs
(2)
Seeds (1)
Seeds (1)
Participating
(2)
Participating
(2)
Participating
-
Extrapolate
FSR findings
Note: (1) indicates weak linkage; (2) indicates strong linkage; WGM = Working Group Meeting; Group treck is a
multidisciplinary team visit in which the future course of action is discussed and decided; ADO = Agricultural Development
Office; DFO; ADB = Agricultural Development Bank; AIC ; and LARC = Lumle Agricultural Research Center.

Table 17. Links between farmers and different institutions, hmdi Bhumdi, Nepal (1990-91).
Role to Effectiveness of Participation
Institution Relationship strengthen linkage and
FSR communication
- --
Agriculture Development Yes Yes Strong Effective
Office (ADO)
Cooperative Yes Yes Weak No
Livestock Service Center Yes Yes Strong Effective
FSR Site Coordinator Yes Yes Strong Very
Table 18. Problems faced by intervened and controlled farmers
in the adoption of the improved technology recommended by the
FSR program, Pumdi Bhumdi, Nepal (1990-91).a
Intervened
farmers
Controlled
farmers
2, 3 2, 3, 4
al = lack of irrigation facility; 2 = unavailability and untimely supply
of agricultural inputs; 3 = lack of money to purchase agricultural
inputs; 4 = lack of technical knowledge; 5 = more labor required;
6 = decline in soil fertility; 7 = disease and insect problems if stored
for a long time; 8 = improved varieties destroyed by wild animals
because of late maturity; 9 = less straw and poor taste; and 10 =
requires more seed than local varieties.
-

Capitol city
1. Map of Nepal showing Pumdi Bhumdi FSR site.

----l
CROP SUBSYSlLM
rnurt
L
OTT tbRH
'6
Hourthold
l !oOdl
Lkbor
u;~~;ltottd
nanurt 1 1
FRSIURE LAND
( Wlirrbarl )
I l
I 1 m
2. Existing farming systems and interactions between different farm
enterprises at Pumdi Bhumdi.

ASSESSRIENT OF RICE-FISH FARMING SYSTEM IN INDONESIA
h1.O. Adnyana, D. K. S. Swastika, and W. sudanal
With the changing strategy of the Government of Indonesia to
diversify the agricultural development program from a single
commodity of rice, the technology of rice-fish was introduced
primarily in West Java. Sobong District took the leadership in this
technology with large numbers of farmers adopting this new farming
system. A study of the impact of this technology indicated greater
efficiency in input use, increased rice yields and farm incomes,
increased consumption of fish as well as increased capital
accumulation among the farmers. Based on the potential of this new
technolo~, strong operational actions must be taken at the national
level and research effort to further improve the technology must be
continued.
The Government of Indonesia has changed the strategy of future agricultural
development from a single-commodity approach to a more diversified approach to
sustain rice self-sufficiency and increase farm income. Rice-fish farming system is an
improved practice that makes more efficient use of agricultural resources in lowland
rice areas.
The rice-fish farming system (RFFS) has been traditionally practiced in
IndonesiB since the middle of the 19th century. It was started with some trials
conducted by students in the Cianjur and Singaparna Districts of West Java. The
students tried to use the remaining water in the ricefields by rearing fish after the
wet season (WS) rice was harvested. They improved the farming system from rice -
fallow to rice - fish. After they graduated, they introduced the rice-fish farming
system and the rice + fish farming system (rice-cum-fish) to their respective villages.
Fish production from ricefields rose from 19,082 t in 1968 to 29,120 t in 1979,
and to 87,414 t in 1987 (CBS 1976-89). As shown in Table 1, the contribution of rice
- fish to total fish production has increased annually. In 1987, RFFS accounted for
47.3% of total freshwater fish production.
The RFFS is considered relevant to future agricultural development
programs of Indonesia because it sustains land productivity, increases incomes,
and improves the quality of food of rural people (Fagi et a1 1989). An impact study
on RFFS was conducted at Binong Sub-District, West Java. This study examined the
efficiency of use of inputs in rice production, labor allocation, rice yields, farm
income, food and nonfood expenditures, and productive and nonproductive
accumulation of assets.
l ~ ~ efor n Agricultural c ~ Research and Development (BORIF), Bogor, Indonesia.
- 59 -

West Java provincial le~el
BACKGROUND
Fish production in the RFFS decreased from 1974 to 1980, but increased from 1981
to 1990. This was mainly due to the development of floating nets at the Saguling,
Cirata, and Jatiluhur Dams for the growth of large-sized fingerlings. These
fingerlings can be reared in ricefields, either together with rice or after rice harvest.
Table 2 shows the production of freshwater fish and the share of fish produced from
ricefields in West Java from 1974 to 1989.
In 1990, the Provincial Government of West Java targeted 20,000 ha of
irrigated land for RFFS. Credit of IRP50,000/ha, in addition to the amount
allocated for rice cultivation, \tras provided to farmers who were willing to develop
RFFS. In 1991, the targeted area was increased to 22,000 ha. Forty-eight percent of
the total targeted area was concentrated in West Java. The success of the rice - fish
farming intensification program in West Java encouraged the government to make
RFFS a Bimas program at the national level. The targeted area of rice - fish farming
in the dry season (DS) of 1991 and the WS of 1991-92 was 46,000 ha and covered 14
provinces.
In West Java alone, this program required about 1 million fingerlings over
two seasons in 14 districts. Tasikmalaya required about 225,000 fingerlings and
Cianjur 200,000. These are about 50% of the total number of fingerlings needed for
the RFFS development program. West Java is targeted to have about 22,000 ha of
wet land or 48% of the total area of RFFS in Indonesia.
Subang District level
Binong Subdistrict has a population of 97,658. and more than 8896 of it work in the
agricultural sector. The lo\vland area is the most productive agricultural land in
West Java. It is located in the coastal area of Subang District. There are about
12,929 ha of agricultural land and the majority (10,297 ha) is irrigated. Subang
District is one of the main rice-producing regions in West Java.
In 1978-79, the cultivation of fish in ricefields was introduced. This farming
system consisted of three subsystems: fish grown with rice (rice-cum-fish), fish
between rice crops, and fish grown after the rice (rotational fish). The most widely
developed subsystem was rotational fish. The practice of running-water aquaculture
also gradually increased. However, the s~lpply of fingerlings from the rotational fish
farming system was inadequate and there was a constant gap between demand and
supply of fingerlings.
To support the development of the RFFS, particularly fingerlings, a village
extension model was developed in 1981-52 at Cicadas, Binong Sub-District.
Running-water aquaculture was practiced simultaneously, which also required large-

sized fingerling (50-100 glfish). Therefore, the fingerlin~s produced in the RFFS
had many optional market channels. Farmers who practiced floating-net fish culture
often came to Binong to purchase fingerlings during the harvest season. This
encouraged the farmers at Binong to practice the RFFS. By 1989, the RFFS had
rapidly increased in Subang (Table 3).
The Sukamandi Research Institute for Food Crops (SURIF) and the
Research Institute for Freshwater Fish (RIFF) in Bogor conducted experiments on
the RFFS technology components and conducted on-farm research to improve the
technology. This research demonstrated that rice-fish culture had increased rice
yields. The RFFS also reduced triple superphosphate (TSP), use of herbicides and
insecticides, and labor for hand weeding, Results were consistent in experimental
stations and on-farm trials.
Three components of the RFFS practiced in the study area are as follows:
H Rice-cum-fish or rice + fish: fry or fingerlings are raised together with rice
for about 40-45 d depending on the use of fish.
H Sequential fish or fish in between: fish are cultivated after the harvest of WS
rice and harvested before the DS rice is planted. This system is usually used
to fatten the fingerlings before they are cultivated in the rice-cum-fish system
during the first DS.
H Rotational fish culture (fish as palawija): after the harvest of DS rice, the
field is submerged to make a fish pond. This is usually done as an alternative
to third-season crops (palawija crops), fish are raised for about 2-3 mo.
If farmers who grow two crops of rice are considered, four farming system
models are practiced over a period of one year in the study area. These farming
systems are rice - rice - fallow, rice - rice - fish, rice + fish - rice + fish - fish, and
rice t fish - fish - rice t fish - fish.
The most commonly practiced rice - fish farming models are rice - rice - fish
and rice + fish - fish - rice + fish - fish. The choice of farming model depends on the
availability of irrigation water. Rice - rice - fallow is still the major cropping pattern.
The rice - cum - fish system offers better prospects in terms of water availability.
Rotational fish culture depends on the water conserved by the Jatiluhur Reservoir
and the Cimacam Dam. In this study, three farming models are evaluated to
determine the impact of the RFFS: rice t fish - rice t fish - fish (FS 1); rice - rice -
fish (FS 11); and rice - rice - fallow (FS 111).

OBJECTIVES
The specific objectives of the study were to evaluate the historical profile of RFFS
and to present ~ ts status in Indonesia and West Java; to determine the role of certain
institutions in the development of RFFS; to identify the new technology developed
within the farming system framework and the extent to which the technology had
been adopted; to determine the degree to which the adoption of the RFFS had
increased the efficiency of input use, rice production, net income of the farm
households, and their purchasing power; to measure the degree to which the
purchasing power had improved the quality of the consumption pattern and the
accumulation of productive assets by the farm households; and to identify the
potential for, and constraints to, future development.
Sampling
METHODOLOGY
Stratified random sampling was used to identify 20 farmer-cooperators from each of
the three farming system models ( FS I, FS 11, and FS 111). Sixty farmers were
intensively monitored for 2 yr.
Data collection
Rapid rural appraisal (RRA) was used to gather information on the institutional
impact of FSR. Interviews were conducted with related key informants [i.e.,
researchers from SURIF and the Freshwater Fishery Research Institute, Regional
Office of Agricultural Ministry, Provincial Fishery Extension Service, Provincial
Intensification Coordinator (Bimas), and District Fishery Extension Service, and a
few farmers and traders at Binong, West Java]. Relevant secondary data were also
gathered from these institutions. In addition, secondary data were collected from the
Central Bureau of Statistics (CBS) and Institut Pertanian Bogor (IPB).
Data were collected on the history of RFFS, the progress and present status
of RFFS, share of RFFS to freshwater fish production, the marketing system, the
su port system, constraints, the role of institutions in RFFS, and other related
f
in ormation. On-farm data were collected each day using an intensive record-
keeping technique for a period of 2 yr. Data recorded during the first year included:
input-output, food-consumption pattern, nonfood expenditures (e.g., education,
health, recreation, and clothes), productive assets (e.g., livestock, agricultural
equipment, and bicycles), and nonproductive assets (e.g., radios and television). In
the second year, a periodic record-keeping method (four times per season) was used
for production activities.

Data analysis
Financial analysis and econometric procedures were used to measure the impact of
the RFFS.
IMPACT ON FARMER WELFARE
To evaluate the impact of the development of RFFS in the study area, the
technology used in each farming system was evaluated. This discussion focused on
the inputs used and the outputs achieved (i.e., production of rice and fish, net
income earned by the farmer, and food and nonfood expenditure patterns).
Inputs
The inputs (other than labor) used in each farming system model are presented in
Table 4. There were significant differences in the levels of inputs used (TSP
fertilizer, herbicides, and insecticides) in both the DS and WS. Lesser amounts of
TSP were used in FS I and FS I1 than in FS 111. This indicated that the incorporation
of fish, particularly in intercropping, significantly reduced the amount of TSP
applied.
The fingerling density and rate of TSP a plication recommended by the
Sukamandi Research Institute for Food Crops [SURIF) for RFFS were 2,000 fry/ha
(weight of 10 g/fry) and 75 kg TSP/ha. The TSP application rate recommended by
the extension service was 150 kg/ha. Although the technique of trench construction
was adopted, farmers did not adopt the amount of TSP or the fingerling density
recommended by SURIF. However, they had adopted the rate of TSP recom-
mended by the extension service, which was twice the rate recommended by the
research institute. In the case of fingerlings, the density ranged from 569 to 1,128
fry/ha or about 28.4-56.4% of the recommended rate.
The production of fish ranged from 321 to 464 kg/ha (equivalent rice)
whereas, the production of fish at the on-farm research site averaged 1,500 kg/ha.
Therefore, the transfer of technology from the research institute to the farmers
needs to be intensified.
The RFFS also reduced the amount of liquid insecticide and herbicide used
in FS I and FS I1 in both wet and dry seasons (Table 4). For instance, in 1989-90,
RFFS reduced the application of herbicide almost to zero in FS I and FS I1
compared with FS 111, in which about 0.5 liter/ha were applied during the WS and
DS. This indicates that the incorporation of fish in rice-based farming systems
reduced insect infestation and weed growth. However, further research is required
to evaluate the real impact of fish culture on rice production, particularly in relation
to chemical inputs.

Labor requirement
Labor requirements (men and women) for each activity within the 3 farming system
models are presented in Tables 5 and 6. In general, the total number of hours
required per hectare in FS I during the WS and DS was relatively higher than that
required by FS I1 and FS 111.
Men worked in almost all activities, particularly in land preparation, rat
hunting, chemical spraying, weeding, and harvesting. Women performed rice
planting, weeding, and harvesting. They spent more time in these activities than
men.
Land preparation for rice farming and rice-fish farming was mostly done
using hand tractors, which cost IRP49,000/ha in 1989-90 and IRP63,000/ha in 1990-
91. However, manual labor was also used, particularly to hoe the corner plots of rice
and to repair dikes and canals.
In 1989-90, the use of labor for land pre aration was reduced. This indicated
that cultivation of fish during the third season after two rice seasons) made land
preparation easier.
Rice and equivalent rice yields
The average land size per family in FS I and FS I1 was 0.7 ha, while in FS I11 was
1.1 ha. All yields and incomes were converted into hectares except in the case of fish
in the second DS. The formula used was
Price of fish Rp/kg of fish equiv kg
Equivalent rice = X quantity of fish = X kg fish =
Price of rice Rp/kg rice Price
The rice yield and total equivalent rice yield in FS I were higher than the
yields in FS I1 and FS 111. This result was consistent in 1989-90 and 1990-91. The
additional yield from rice - fish farming resulted from both fish production and
cultivation of rice. Production figures for FS I, FS 11, and FS 111 are given in Table 7.
The increase in rice yield in FS I and FS 11 in the WS may be due to the
residual effect of third-season fish cultivated in both farming systems. Furthermore,
the high yield of rice in FS I may be due to the biological control of weed and insect
infestation. Most of the RFFS areas were relatively less vulnerable to insect
infestation and weed problems during the crop years 1989-91 and 1990-91. This was
evident from the lower levels of insecticide, herbicide, and labor used for weeding
and chemical application, compared with FS 111. In the DS, FS I also produced the
highest rice yield. However, the increase of 32% compared with FS 111 in 1989-90
was reduced to 23% in 1990-91.
P

In terms of yield equivalent to rice, in 1989-90, the total annual yield in FS I
was 13,910 kg/ha and in FS I1 was 11,704. About 51% and 27% higher than the
annual yield of FS I11 (9,213 kg/ha). A similar situation was observed in 1990-91.
The additional yield produced in FS I and FS I1 was contributed by fish production,
particularly in FS I, in which fish culture was practiced three times a year. Fish
cultivation may also have an indirect impact on soil fertility.
Farm income
The adoption of intensive RFFS affected the level of farm income by reducing the
level of inputs (e.g., insecticide, herbicide, TSP, and labor for weeding), increasing
rice yields, and generating additional income from fish culture. The low level of
input use reduced production costs, whereas, the increase in the production of rice
and fish increased gross return and subsequently net income. The incomes of the
three farming system models are presented in Table 8.
Food and nonfood expenditure pattern
Data on food and nonfood expenditure patterns were collected during the first year
of this study (1989-90) using an intensive record-keeping technique. Food and
nonfood expenditure patterns per month and the monthly expenditures on fresh fish
are presented in Tables 9, 10, and 11. The food and nonfood expenditure patterns
were closely related to total income per farm family. On-farm income is one of the
sources of income that determines total income. On-farm income is not only
determined by farming intensity but by land size.
Farmers in FS III per capita expenditure on food (IRP18,877) was the
highest among the three farming system models although they practiced a less
intensive farming system (rice - rice - fallow). About 43.3% (IRP6,484) of the per
capita expenditure on food is allocated to purchase rice, 15.3% (IRP2,893) for dry
fish, and 15.2% (IRP2,877) for vegetables. Similarly, the per capita expenditure on
nonfood items (IRP18,026) by families in FS I11 was also the highest among the
three farming models.
Farming intensity increased per capita food and nonfood expenditures per
month. For example, the average monthly per capita expenditure of the farm
families belonging to FS I (IRP18,179) was higher than that of FS I1 (IRP14,123). A
similar situation was observed in the nonfood expenditure pattern. The average
monthly per capita expenditure on nonfood items in FS I (IRP14,OOl) was higher
than the expenditures by families in FS I1 (IRP10,374). In other words, the
introduction of fish culture in FS I (rice+ fish - rice+ fish - fish) increased the
purchasing power of its farm families in relation to farm families belonging to FS I1
(rice - rice - fish).
In relation to consumption of fresh fish, the average monthly per capita
expenditure of families in FS 1 (IRP1,220) was the highest among the three farming

system models. This indicated that the higher yield of fish in FS 1 (cultivated three
times a year) increasecl mor~thly per capita fish consumption (Table 11).
Asset accumulation
Asset accumulation is the value of all goods owned by farmers. Assets are
categorized as agricultural equipment (e.g., tractors, hoes, and motcicycles),
livestock, nonproductive assets (radios, televisions, and furniture), and savings
(jewelry and cash).
Table 12 shows the value of the assets owned by farmers belonging to the
three farmin models. The total value of all assets owned by the farmers In FS I11
during 1989- 8 0 and 1990-91 is hi her than the value of assets owned by farmers in
FS I and FS 11. .Therefore, rice - f ish farming had little impact on the accumulation
of assets, except in the case of FS 111. Accumulation of assets, total income of the
farm family, and farm size are closely interrelated. The average farm size in FS I11 is
higher than in the other two models. In general, farmers belonging to FS I11 are
better off than farmer: in FS 1 and FS 11; therefore, it is logical that these FS 111
farmers have more accumulated assets. However, farmers in FS I have more assets
than FS I1 farmers. This indicated that rice - fish farming systems had made a
positive impact on the accumulation of assets.
BUDGETING STAGES
The proposed model assumes that consumers follow a multistage budgeting process.
Consumers are assumed to first allocate their income between savings and current
expenditures (consumption). This stage is not rnodeled in this study. In the second
stage, consumers are assumed to allocate their total current expenditure to two
categories: food and nonfood commodities. The third stage involvzs the allocation
of the total food expenditure to nine subgroups. The fourth stage involves the
allocation of nonfood expenditure to nine subgroups.
Functional form
The Linear Approximate Almost Ideal Demand System (LA/AIDS) was used to
model budget allocation. Following Deaton (1988), the Marshallian demand
equations, in share form, fcr the LA/AIDS demand system are
Wi = ai + aij In (Pj) + Bi In (Y/P) for i, j = 1, 2 ,..., r [l]
where Wi is the budget share of the ith commodity, Pj is the unit price of the
jth commodity, Y is the total expenditure, and P is Stone's price index, i.e.,
In (P) = dk wli In (Pk) PI

A demographic variable (family size) was introduced into equation [l] by
translating the intercept term. It was assumed that
ai = aio + Ct ait Dt for i = 1, 2, ..., r
where D denotes demographic variables. The resulting model was
wi = aio + Ct ait Dt + Eij In (Pj) + Bi In (XIP) [41
The relevant theoretical restrictions that can be imposed on this demand system
are (Heien and Pompelli 1989)
Data sourqe
Symmetry: aij = aji; (i + j; i, j = 1, 2,. . . , r)
Homogeneity: aij = 0; (i = 1, 2, . . ., r)
Adding-up: Ci aio = 1 ; Ei bi = 0; Ci aij = 0; (t = 1, 2, . . . , v)
The data on food and nonfood consun~ption from the impact study on FSR in Binong
during the crop year 1989-90 were used in this analysis. Data were maintained for two
rice seasons and a third season of crops and fish production within a year. Data were
collected directly from the selected households. Information on individual household
consumption was converted into per capita consumption per month. The aggregated
data were divided by family size to obtain per capita consumption.
All expenditures were classified into two major groups (food and nonfood
items). Because economic theory provides no guidance on the composition of food
groups, the decision is usually made on an ad hoc basis by the researcher. In this study,
the proposed list of food groups and nonfood groups depended on the ability of farmers
and consumers to recall the items they had consumed.
With regard to per capita expenditure of the selected households, food items
were classified into nine subgroups: rice; meat; fresh fish; dry fish; eggs; vegetables;
spices; cooking oil; and sugar, tea, and coffee. There were also nine subgroups of
nonfood items: firewood and kerosene; soap and tooth paste; electricity; education;
clothes; taxes and other obligations; health; social activities and cultural ceremony; and
asset accumulation.

Unit prices for all items were obtained by dividing the reported expenditure
by the number of units. Some of the unit prices were computed as weighted prices.
Following Heien and Pompelli (1989), a set of auxiliary regressions, which linked
available prices to a set of dummy variables and to expenditure, was used to impute
missing prices.
To express all unit prices in the same matrix, both food and nonfood prices
were scaled by dividing each by its corresponding mean value. In addition, all scaled
unit prices were transformed into logarithms to obtain the linear form of the
demand model.
EMPIRICAL RESULTS
This discussion emphasizes the results of the economic analysis of the rice-fish
farming systems and its impact on consumption patterns, the budget allocated for
each item, and the magnitude of elasticities.
Consumption pattern and budget share
In general, FS I farmers had higher levels of per capita consumption than FS 11
farmers. However, per capita consunlption by FS I farmers was lower than
consumption by FS I11 farmers. This difference is evidently due to the fact that the
average land holding of the farmers in FS I11 was 1.1 ha compared with an average
of 0.7 ha in the other two groups. The total per capita expenditure of the farmers in
FS I was about 33.6% higher than farmers in FS 11, but about 12.5% lower than for
farmers in FS 111.
The budget share for food items in FS I (54.6%) is a little lower than in FS I1
(56.770). However, the lowest share was in FS 111 (49.2%). The highest budget share
for nonfood items was in FS I11 (50.8 96) followed by FS I (35.4%) and FS I1
(43.3 %) (Table 13).
Therefore, the poorer farmers in FS I and FS I1 spent more than 50% of
their income on food items. On the contrary, farmers in FS 111, who had higher
incomes, spent less than 50% of their income on food consumption. Therefore, the
impact of rice-fish farming systems will be most effective if it is developed among
small-scale farmers under existing conditions.
Food expenditure
A summary of the expenditure pattern for food and the budget share of each food
item are presented in 'Table 15. In all farming system groups, the largest part of the
expenditure on food was spent on rice. The second ancl third highest shares were for

dry fish and vegetables, respectively. The consumption of meat was relatively low in
all three farming groups.
With regard to the direct impact of the rice-fish farming systems on
consumption of fresh fish, farmers in FS I consumed more fish (7%) than farmers in
FS I1 (6%) and FS I11 (4%). Other food items showed varied budget shares among
the three farming system groups.
Nonfood expenditures
A summary of the nonfood expenditures and the budget share of each nonfood item
are presented in Table 15. Within the nonfood category, the highest amount was
spent on education. The impact of fish culture on quality of life was that farmers
spent more on education. For example, farmers in FS I and FS I1 spent about 26%
and 39% of their total nonfood expenditures on education compared with FS 111
farmers who spent 1270. However, FS 111 farmers spent more on taxes and assets
than farmers in FS I and FS 11.
In relation to expenditures on social activities (e.g., cultural ceremony,
recreation, and donations), there is a remarkable difference between farmers in FS I
and FS I1 although they have the same social status. With the increased income
from fish, FS I (fish cultivated three times a year), farmers spent more on social
activities than FS I1 farmers. However, FS 111 farmers spent the highest budget share
on social activities.
Significant differences were also observed in expenditures on health services
(e.g., visiting rural heklth services and family planning) between farmers in FS I and
FS 11. Farmers in FS 111 spent the highest budget share on health services.
Demand elasticities
A summary of price and income elasticities for all budget categories is given in
Tables 16, 17, and 18. These figures were compared using the estimated parameters
of the LA/AIDS model. There was variability in the elasticities in all groups of
consumers.
The demand for food and nonfood groups appears to be unit price inelastic
in all farming groups (Table 16). However, farmers in FS I11 are relatively more
responsive (i.e., a coefficierlt of -0.664 for food and -0.748 for nonfood). Meanwhile,
the demand for food and nonfood groups appears to be income elastic in all farming
groups except for food in FS I (0.999 and 1.001).

Price elasticity. The demand for all food items appears to be price inelastic in
all farming groups. The demand for rice is the most important in terms of food
policy in the study area. Among all food items, the demand for rice is relatively
more responsive to price variability in all farming groups (-0.390 in FS I, -0.403 in
FS 11, and -0.306 in FS 111). Furthermore, the demand for fresh fish in FS I is the
most price inelastic among the three farming groups (-0.059 compared with -0.87 for
FS I1 and -0.89 for FS 111). This may be due to the high degree of subsistence on
their own production of fresh fish.
Incot~ze elasticities. The demand for food items among all farming groups is
mostly income elastic (coefficients of elasticities almost 1.0 except for some food
items for which elasticity is oreater than 1.0). For example, the demand for meat in
FS I is income elastic (1.8267. The demand for food commodity bundles (e.g., eggs
and sugar, tea, and coffee in FS 111 and sugar, tea, and coffee in FS 11) are income
elastic. In other words, the demand for those food iterns is likely to be determined
by the farmers' income.
Nonfood sector
There is significant variability in the elasticities among nonfood items.
Price elusticity. Demand in the nonfood sector is mostly price inelastic in all
farming groups for health services. The demand for health services in FS I1 and FS
111 is price elastic (coefficients of -1.324 and -1.025, respectively). The demand for
assets is the most price elastic in all farming groups (coefficients of -1.377 in FS I, -
1.751 in FS 11, and -1.751 in FS 111). This indicates that farmers would lessen their
demand for assets (agricultural assets and savings) if their price increases. These
assets include nonproductive assets such as radios and televisions.
I~zcottze elusticity. The denland for firewood and kerosene, education, social
activities and donations, and assets is income elastic in all farming groups. The
demand for assets is highly income elastic (coefficients of 3.253- in FS 1. 4.533 in FS
11, and 2.533 in FS 111). Social activities and donations showed a similar pattern.
Role of extension, farmer participation, and ~~olicy
Researchers and extension specialists can play a inajor role in improving the
conditions of small-scale farmers and encouraging policy. The technology developed
by these research projects have been transferred through multilocation testing; field
days attended by extension specialists, researchers, pol~cymakers, and farmer
groups; seminars and workshops; publications; and other media (radio and
television).

CONCLUSION
Rice-fish farming systems have been practiced since the middle of the 19th century.
However, this farming system was traditionally practiced without appropriate
technology, particularly without the construction of trenches. Farmers believed that
trench construction would reduce the yield of rice. This study shows that trenches
have no adverse effect on the production of rice.
After the introduction of the new technology, farmers adopted the technique
of trench construction but paid little attention to the amount of TSP or fingerling
density. The fingerling density farmers used was 569-1,128 fry/ha. The production of
fish ranged from 321 to 464 kg/ha (equivalent rice). This production is much lower
than the level obtained under research conditions (average 1,500 kg/ha equivalent
rice). Therefore, transfer of technology from the research institute to the farmers
should be intensified. This could be done by strengthening the links among
researcher, extension specialists, and farmers through on-farm research.
Fish culture in rice-fish farming systems has several advantages: increased
efficiency of TSP, herbicide, and pesticide use and better use of labor for weeding
and spraying; increased rice and equivalent rice yield, increased net income;
increased consumption of fresh fish; and increased accum~~lation of assets.
The annual yield of rice and equivalent rice per hectare in FS 1 and FS I1
were higher than in FS 111. The annual net income per hectare in 1989-90 of FS I
was 89.5% arld of FS I1 was 60% higher than in FS 111. While in 1990-91, FS I was
87.570 and FS 11 was 50.870 higher than in FS 111.
Because FS I farmers in the irrigated areas cultivated fish three times a year,
their per capita consulnption of fish was relatively higher than the consumption of
FS 11 farmers, who cultivated fish once a year. There were significant changes in
expenditures on food, particularly fresh fish, in all farming system groups. Significant
changes were also observed in expenditures on nonfood items. The share of food
expenditure to total expenditure is higher than nonfood expenditures in FS I and FS
11. However, the opposite is true for consumers in FS 111.
A significant variability in price and income eltlsticities of demand for food
and nonfood items was found in all farming system groups. The demand for
commodities within the food category is price inelastic in all farming groups, but the
demand for nonfood items varies. For example, the demand for education, health
services, and assets in FS I is less elastic than in FS 11 and FS 111.
Rice-fish farming has the potential for large-scale developrnent in Indonesia.
It can be supported by government policy, external sup ort, farmer participation,
and technology development. In spite of the prospects 1 or RFFS, there are certain
constraints. These are inconsistent supply of irrigation water, inadequate availability
of fingerlings, natural hazards, and lack of appropriate processing and marketing
systems of fish. To overcome these problems, local governments (vrovincial and

district fishery extension services) and researchers must exert efforts to improve the
technology.
Based on the potential, prospects, and constraints in the development of rice-
fish farming systems. Appropriate actions are needed at the national level. These
include the continuous improvement of the technology for hatching and rearing fry,
extension and guidance for farmer groups, credit facilities, and improved marketing
systems. Local governments may be needed to provide support services such as
provision of irrigation water and credit for hatcheries.
REFERENCES CITED
CBS--Central Bureau of Statistics (1976-1988) Statistical yearbook of Indonesia.
Jakarta.
Deaton A (1988) Price elasticities from survey data: extensions and Indonesian
results. Woodrow Wilson School, Princeton University. (mimeograph).
Fagi A M, Suryapermana S, Syamsiah I (1989) Rice-fish farming system in lowland
areas, the West Java case. Paper presented at the Asian Regional Workshop
on Rice-Fish Research and Development. Central Luzon State University,
Nueva Ecija, Philippines.
Heien D, Pompelli G (1989) The demand for alcoholic beverages: economic and
demographic effects. South. Econ. J. Agency for Agricultural Research and
Development, Bogor, Indonesia.
I

Table l. Area and production of freshwater (FW) fish and the share of RFFS to freshwater fish production, Indonesia
(1 960-87).
P P P P
Area of Production of Production of Production of Total Production Share
Year rice-fish rice-fish pond fish karamba* FW fish of RFFS
(ha) (t) - (t> (t> (0
1960
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
Average
Source: CBS 1975-89; Data for 1961-67 not available.
* Karamba = Bamboo basket for keeping fish in the river or in the irrigation canals. It could also in the form of fence, fixed
in the riverlirrigation canals.

Table 2. Production of freshwater fish in West Java (1974-90).
Year Sawah Pond Running water Floating net Karamba Total Share
(t> (t> (t> (t> (t> (t>
Average
Source: CBS 1975-89 and Provincial Office of Fishery;
* data not available.

Table 3. Area and production from rice-fish farming system, Subang, Indonesia (1982-89).
Area
P p
Production
Year Rice- Fish in Rotational Total Rice- Fish in Rotational Total
cum-fish between fish fish cum-fish between fish Prod.
(ha) (ha) (ha) (ha) (kg) (kg) (kg) (kg)

Table 4. Level of inputs used in each FS Model, Binong, Indonesia (1989-90 to 1990-91).
Inputs
1989-90
Rice seed (kg) 27
Fingerling (fish) 1,128
Feed (kg) 11.7
Urea (kg) 175
TSP (kg) 153
KCL (kg) 13
ZA (kg) 0
Liquid fertilizer (L) 0.06
Carbofuran (kg) 2.3
Herbicide (L) 0.05
Rodenticide (g) 1 .O
Insecticide (L) 0.7
Land area (ha) (0.7)
1990-91
Rice seed (kg) 29
Fingerling (fish) 723
Feed (kg) 5.2
Urea (kg) 191
TSP (kg) 148
KCL (kg) 55
ZA (kg) 5.8
Liquid fertilizer (L) 0.17
Carbofuran (kg) 8.1
Herbicide (L) 0.19
Rodenticide (g) 1,225.0
Insecticide (L) 1.2
Land size (ha) (0.7)
Wet season Dry season

l
Table 5. Labor requirement for each FS Model, Wet Season, Binong, Indonesia (1989-90 to 1990-91).
FS I FS I1 FS I11
Activities Men Women Tract Total labor Men Women Tract Totallabor Men Women Tract Total labor
(hlha) (hlha) (IRPIha) (hlha) (hlha)' (hlha) (1RPIha) (hlha) (hlha) (hlha) (IRPlha) (hlha)
1989-90
1 Land preparation 156 0 49,000 254 187 0 49,000
2 Seedling 3 1 1 0 32 3 3 0 0 34 29
3 Irrigation 2 0 0 29 24 0 0
4 Rice planting 3 1 210 0 157 29 194 0
5 Fish stocking 9 1 0 9 0 0 0
6 Rat hunting 59 0 0 59 57 0 0
7 Fertilizer application 24 0 0 24 26 1 0
8 Weeding I 50 38 0 73 68 66 0
9 Fish harvest 20 7 0 24 0 0 0
l0 Chemical spray 14 0 0 14 23 0 0
l 1 Rice harvest 187 220 0 3 19 135 196 0
12 Postharvest 0 1 0 1 2 2 0
4 Total (hlha) 610 478 49,000 995 584 259 49,000
I Labor cost (Rplha) 305,000 143,400 49,000 497,400 292,000 137,700 49,000 478,700 299,000 135,300
1990-91
1 Land preparation 248 0 6,300 248 135 0 63,000
2 Seedling 42 0 0 42 28 0 0
3 Irrigation 28 0 0 28 16 0 0
4 Rice planting 43 195 0 238 17 170 0
5 Fish stocking 10 7 0 17 0 0 0
6 Rat hunting 40 0 0 40 14 0 0
7 Fertilizer application 37 6 0 43 20 1 0
8 Weeding I 33 47 0 80 37 68 0
9 Fish Harvest 20 19 0 39 0 0 0
1OChemical spray 28 0 0 28 30 0 0
1 1 Rice harvest 24 1 327 0 568 173 260 0
12Posthmest 10 l l 0 2 1 11 1 0
Total (hlha) 780 612 63,000 1,392 48 1 500 63,000
Labor cost (Rplha) 390,000 183,600 63,000 636,600 240,500 150,000 63,000 453,500 316,000 162,000 63,000 541,000

Table 6. Labor requirement for each FS Model, Dry Season I, Binong, Indonesia (1989-90 to 1990-91).
Activities Men Women Tract Total Labor Men Women Tract Total Labor Men Women Tract Total Labor
(hlha) (hlha) (IRPIha) (hlha) (hlha) (hlha) (IRPIha) (hlha) (hlha) (hlha) (IRPIha) (hlha)
1989-90
1 Land preparation 207 0
2 Seedling 3 6 0
3 Irrigation 3 5 0
4 Rice planting 24 151
5 Fish stocking 7 2
6 Rat hunting 39 0
7 Fertilizer application 25 2
8 Weeding I 30 46
9 Fish Harvest l I 7
lOChemical spray 15 0
1 1 Rice harvest 179 205
-1 12 Postharvest 27 19
Total (hlha) 634 432
Labor cost (Rplha) 3 17,014 129,733
1990-91
1 Land preparation 226 0
2 Seedling 3 1 0
3 Irrigation 65 0
4 Rice planting 26 162
5 Fish stocking 5 2
6 Rat hunting 50 0
7 Fertilizer application 26 7
8 Weeding I 27 47
9 Fish harvest 10 12
IOChemical spray 22 0
11 Rice harvest 208 25 1
12Postharvest 19 2 1
Total (hlha) 715 502
Labor cost (Rplha) l 357,500 150,600
1.and area (ha)
I

Table 7. Rice and equivalent rice yield from rice-fish farming, Binong, Indonesia
(1989-90 and 1990-91).
WS DS I DS I1 Total
rice equivalent rice rice equivalent riceEquivalent rice Total
(kg) (kg) (kg) (kg) (kg) (kg)
FS IIf 5,702 0 4,204 0 0 9,906
(100%) (100%) (100%)
Note: Average rice price: WS = RP25O/kg; DS I = RP280/kg; DS I1 = RP320/kg.
Average fish price: WS = RP2,100/kg; DS I & DS I1 = RP2,200/kg.
Figures in parentheses = percentage of rice yield compared with FS 111.

able 8. Income analysis of each FS Model, Binong, Indonesia (1989-90 and 1990-91).
1989-90
FS I FS I1 FS 111
WS DS I DS I1 Total WS DS I DS I1 Total WS DS I DS I1 Total
Rice 1,761.840 1,390,230 0 3,152,070 1,409,760 1.320.840 0 2,730,600 1,273,200 1,055,160 0 2.328.360
Fish 11 1,400 86,(i 171,470 369,470 0 0 253,128 253,128 0 0 0 0
Gross reurn 1,873,240 1,476,830 17 1.470 3,521,540 1,409,760 1.320.840 253,128 2.983.728 1,273,200 1.055,160 0 2,328,360
Material cost 176,526 165.355 40.450 382,331 102,338 141,783 15,373 259,494 141,141 168,012 0 309,153
Labor cost 497.400 495,747 55,960 1.049,107 478,700 451.734 28.325 958,750 483,300 432,764 0 916.064
Total cost 673,926 661,102 96,410 1.43 1,438 58 1.038 593.517 43.608 1.218.253 624,441 600.776 0 1,225,217
Net returnlha 1,199,314 815,728 75,060 2,090.102 828,722 727,323 209,430 1,765,475 648,759 454.384 0 1,103,143
1990-91
Rice
Fish
Gross return
Material
Labor cost
Total cost
Net return
Increase (%)

Table 9. Monthly food expenditure pattern (IRPIperson) of farm families in each farming system model, Binong, Indonesia
(1989-90).
Farming Rice Meat Fresh Dry Egg Vegetable Spices Cooking Sugar Total
models fish fish oil coffee food
FS I
Average
Maximum
Minimum
FS I1
Average
Maximum
Minimum
FS 111
Average
Maximum
Minimum

Table 10. Nonfood expenditure pattern of farm families in each farming system model, Binong, Indonesia (1989-90).
Farming Fire- Toothpaste Electricity Education Clothes Taxes1 Health Donation Total
models wood and soap obligations nonfood
FS I
Average
Maximum
Minimum
FS I1
Average
Maximum
Minimum
& FS 111
h,
' Average
Maximum
Minimum
Note: USD1 = IRP1,925

Table 11. Monthly consumption pattern (IRPIperson) of fresh fish by farm families in
each farming system model, Binong, Indonesia (1989-90).
Month FS I FS I1 FS I11
November
December
January
February
March
April
May
June
July
August
September
October
Average
Maximum
Minimum

Table 12. The value of assets (IRP X thousand) owned by farm families in each FS
Model, Binong, Indonesia (1 990-91).
FSI FS I1 FS I11 FSI FS I1 FS 111
Agricultural assets 108 176 181 96 3 8 49
Livestock 6 8 6 6 82 194 265 193
Nonproductive assets 168 3 9 124 1,138 936 1,303
Savings 219 183 60 1 348 155 496
Total 563 466 988 1,776 1,394 2,041
Table 13. Monthly food and nonfood expenditures (IRPIperson) and budget share of
farm families in each farming system model, Binong, Indonesia (1989-90).
Food Nonfood Total
a~alues in parentheses are the budget shares. USDl = IRP1,925.

Table 14. Food expenditure pattern and budget share of farm families in each farming
system model, Binong, Indonesia (1 989-90).
Rice
Meat
Fresh fish
Dry fish
Vegetables
Spices
Cooking oil
Sugarlcoffeel tea
Total food
a~ote: Values in parentheses are budget share. USDl = IRP1,925.

Table 15. Nonfood expenditure patterns and budget share of farm families in each
farming system model, Binong, Indonesia (1989-90).
Electricity
(16)
Education
Clothes
Health
Asset
Total nonfood
aNote: Values in parentheses are budget share. USDl = IRP1,925.

Table 16. Elasticities in food and nonfood sectors, Binong, Indonesia (1990-91).
FS Model
Income
FS I
FS I1
FS I11
Commodity
Food Nonfood

Table 17. Elasticities of food commodities for own-price and income, Binong, Indonesia (1990-91).
Income
Rice Meat Fresh Dry Egg Vegetable Spices Cooking Sugarltea
fish fish oil /coffee
FS I 0.994 1.826 0.968 1 .OOO 1.058 1.017 1.008 1.037 0.979
FS I1 0.953 1.040 0.935 0.965 1.059 0.991 0.987 1.051 1.331
FS I11 0.953 0.940 0.935 0.965 1.600 0.981 0.977 0.949 1.781

Table 18. Elasticities of nonfood commodities for own-price and income, Binong, Indonesia (1990-91).
Firewood/ Soap/ Electric Education Clothing Tax/ Health Donation Asset
kerosene toothpaste Obligation
Income
FS I 1.046 0.933 0.832 1 .g58 0.892 0.526 0.589 1.398 3.252
FS I1 1.189 0.976 0.703 2.191 0.655 0.199 0.503 2.749 4.533
FS I11 1.197 0.979 0.991 1.095 0.655 0.199 0.986 2.749 2.533

l
Oct k Jan Feb Mar Apr May Jun Jul ~ u g Sep
Rice Rice / / Fish /
RicrA Fish Kiw + Fish
L-
FIB = Fish in &.hn = Fish grow between wet and dry besson rice
1. Rainfall partcrn and fanning niodcls in Binong, Indonesia.

THE IMPACT OF FARMING SYSTEMS RESEARCH IN THAILAND
B. shinawatra1, C. sukapon$, P. ~oodtikam' P. ~eundao~,
P. Padermchai , and B. Ontuam 3
This paper examines the impact of two farming systems research
technologies introduced in Dok Kham Tai District, Phayao
Province, Northern Thailand. The two technologies, mungbean
before rice and direct seedin of rice, were considered mature
enough for extension. The ormer was to increase cropping
intensity, farm income, and utilize beginning off-season moisture
while the latter was to stabilize rice production in areas where
there was a problem concerning the unreliability of rainfall. The
adoption of mungbean before rice was widespread with ups and
downs. It was more appropriate in upper paddy where
waterlogging was unlikely. Many farmers suffered losses from
flooding in certain years. Average yields were found to be lower
than expected (40-48 kg/rai versus the expected 88-161 kg/rai). A
total of 10,046 rai was found planted in mungbean in 1991.
Average cash gross margin per farm was 2,876 baht and 506 baht if
family labor was costed. On a per rai basis, cash gross margin was
271 baht and 91 baht with family labor included. Great price
variability was also observed. While mungbean provided farmers
some additional income, added organic matter and fertilizers to
the soil, and yielded higher rice output in the next season, it can
create delays and potential yield loss in the production of the
following rice crop. Direct seeding of rice was not as easily
adopted by farmers in the study area as compared to mungbean
before rice. When rainfall was adequate and regular, farmers did
not see the need to direct seed. Transplanting of rice was still
commonly practiced up to 1989. Direct seeding of rice became
popular in the study area in 1990 onwards because rainfall was
found to be usually inadequate for rice transplanting and labor
costs high during peak demand periods. Direct seeding of rice with
the use of an appropriate model of mechanical seeders introduced
by the FSR project substantially reduced costs of rice planting. In
1991, some 2,433 rai was planted to direct seeded rice in Dok
Kham Tai, Phayao. Farmers found direct seeding convenient, easy
to practice, and cost-effective. Many of them acquired their own
mechanical seeders. The practice is expected to expand at a rapid
rate in the future both in this area and neighboring areas. The
choice between mungbean before rice and direct seeding of rice
sometimes has to be made but with proper time management of
the two crops, farmers can ractice both technologies thereby
enjoying much increased bene p its.
'~ulti~le Cropping Center, Faculty of Agriculture, Chiang Mai University,
Chiang Mai, Tha~land.
2~arming Systems Research Institute, Thailand.
3~hayap University, Chiang Mai, Thailand.

From 1980 to 1986, the Integrated Rainfed Farming Research and Development
project was funded and supported by the United Nation Development
Programme (UNDP)/Food and Agriculture Ogranization (FAO) in cooperation
with the Royal Thai Government. The research project, which was initially
conceived by the Department of Agriculture, was later expanded as a joint
venture between research and extension. The Farming Systems Research
Institute (FSRI) of the Department of Agriculture \vas the main agency that
conducted and coordinated this project. The Department of Agricultural
Extension, the Department of Li\lestock, and the Office of Agricultural
Economics joined the project as cooperating agencies.
The goal of the project was to improve the productivity and income of
farmers in selected rainfed areas of major agroecological zones. The project was
to develop farming systems technologies, including alternative cropping sjTstems
and crop-livestock integration; introduce these technologies in different
agroecological zones ot selected rainfed areas; test these technologies in the
field; and train staff of the FSRI in interdisciplinary farming systems research
(FSR), development, and extension. The project coirered nine pro\.inces: five in
the north (Phavao, Chiang R:ii, Lampang, Phrae, and Sukothai), tlio in the
northeast (~ahasarakam arid Surin), and t\iro in the south (Phattalung and
Nakhon Sri Thaminar:it).
Because the project \vas farmer-oriented, the strategy for implementation
underwent several changes, i.e., from purely cropping systems, to crop-livestock
integration, to a whole-farm approach. The strategy of the project included:
defining the target areas according to agroecological and crop-production zones;
analyzing the existing farming practices and socioeconomic profiles of the
representative farmers in the rainfed areas; packaging and testing the developed
technologies and evaluating their technical feasibility and socioeconomic
viability; and e.utending pro\.sn viable technologies to more farmers.
Figure 1 shows the co~~ceptual frameivork of the project, which includes
the stages of FSR, the agencies in~lolved, and the approsin~ate time and
conditions required for creation, de\felopment, and transfer of the technology.
Mature technology is agroecologically feasible, economically viable. socially
acceptable, and ready for extension. The role of the FSR researchers decreases
over time; whereas, the role of extension officers and farmers increases as the
stages of multilocation testing, pilot production, and production programs are
reached. The farming and cropping technologies tested in the target farms were
developed in research stations riot only in Thailand but also in other countries
and international research csnters.
The 15 applied research packages or technologies were chosen to fit the
agroclimatic, socioeconomic, and indigenous farming practices in the project
sites. Five technologies were introduced in the different regions.

Phayao
Technology: three rice-based crops; two upland-based crops; two rice-based
crops; and one stabilization crop.
Cropping patterns: onion - rice - soybean; mungbean - rice soybean; sweet
corn - rice - soybean; mungbean - rice - wheat; mungbean - rice - potato;
mungbean - rice; corn/sorghum - mungbean; and direct seeded rice.
Sukhothai
Technology: three cotton-based crops; two cotton-based crops; and two soybean-
based crops.
Cropping patterns: soybean - cotton - blackgram multiple cropping;
soybean - cotton relay cropping; sesame - soybean - sorghum; and baby corn -
soybean - sorghum.
Technology: two cassava-based crops; two rice-based crops; and one stabilization
crop.
Cropping patterns: cassava + peanut intercropping; jute - rice; and
stabilization of cassava production through alley cropping and rotation cropping.
Crop-livestock integration (Phayao, Mahasarakham)
Technology: feed substitution for pigs; feed substitution for cattle; and feed
mixing at village level.
Implementation: use of by-products (rice bran, broken rice, corn, leafy
vegetables, and water plants) as partial substitutes for commercial feeds for
fattening pigs and cattle; and introduction of feed mixing equipment in the
village.
When the project ended in 1986, the direct seeded rice and mungbean -
rice systems were considered mature technologies. In addition, there were four
technologies at the multilocation testing stage and 29 at the on-farm trial stage.
Four technologies were returned to the research station for further study. Seven
promising technologies were believed to be relevant to smallholders in rainfed
areas. The technologies and their areas are summarized in Table 1.

THE 1'\VO ;MATURE TECHNOLOGIES
Direct (dry) seeded rice (DSR) and mungbean before rice were mature
technolog~es that u ~re adopted on a large scale because they were simple and
easy to practice. DSR was recommended for areas where rainfall was unreliable
(e.g., in the northeast and in amphoe Dok Kham Tai, Phayao).
Land preparation for DSR starts as soon as there is adequate rainfall.
Rice seeds should be coated with irisecticide to prevent insect damage before
germination. Seeding should be done in June-July in the northern areas and in
August-September in the southern areas. The rice varieties should be drought-
tolerant and appropriate to local rainfall patterns. A mechanical seeder is
recommended to facilitate weeding and other cultural operations. To support
this recommendation, the project, through the Agricultural Engineering
Division, developed l-row to 4-row mechanical seeders. Because manual labor
was required to operate these machines, farmers thought the task would be
difficult. Therefore, they resorted to draft animals but had little success. Finally,
small tractors Lvere used to pull the seeder, and this was received with a fair
degree of acceptability. Preemergence herbicides and chemical fertilizers were
also recommended.
In the northern area, where conditions are drier, farmers failed to grow a
good crop of transplanted rice (TPR) in about 2 out of every 3-4 yr. In this
situation, DSR would have a positive impact because farmers would not need to
wait for hea\y rains to establish the rice. Furthermore, DSR can withstand
drought better than transplanted rice toward the end of the rainy season because
of its early establishment and maturity.
The estimated gross margin from DSR was about THB1940lha using the
recommended levels of inputs. The cost of inputs for DSR is less than for TPR.
Direct seeded rice ivas more stable than TPR in rainfed areas. At amphoe
(district) Dok Kham Tai, Phayao, where the cost of labor during rice
transplanting was high. DSR was Inore profitable (UNDP/FAO 1986).
hlungbean before rice was designed to capture early season soil moisture
and to supplement farm income. hlungbean can be established before either
TPR or DSR, depending on local rainfall patterns. Land preparation for
mungbean inust be done immediately after the onset of the wet season, i.e., in
late April or early May. Seeding should be done immediately after land
preparation using the same mechanical seeders used in DSR. However, the size
of the slots must be adjusted (Suvanchinda et al 1980). The reconlmended
mungbean varieties are Utong 1, VC 1178, Kampaengsaen 1, and
Kampaengsaen 2. Utong 1, howei~er, had more problems than the other
varieties. The yield of Utong 1 decreased whenever the field was waterlogged. It
also had more than one flowering and pod-setting period, which prolonged the
harvest, increased labor for harvesting, and delayed the next crop. For all
varieties, insecticide application was recommended whenever necessary;
however, fertilizer was not needed.

Short-duration rnungbean sown in April or May (before the main crop of
rice in August) fits into the two-peak rainfall pattern of the country. However,
mungbean is not recommended in low-lying areas of the ricefield where
waterlogged conditions are likely to occur.
Farmers who followed the recommended input levels for mungbean and
rice obtained a gross margin of THB5,630/ha. This is about 100% higher than in
fields where recommendations were not followed (Table 2).
Other promising technologies, such as jute before rice and kenaf before
rice, were tested in four provinces in the northeast. The EEC- and USAID-
funded projects in the area joined this project on the basis of these two
technologies.
STUDY OBJECTIVES
In 1988, the International Development Research Centre (IDRC), in coordi-
nation with the International Rice Research Institute (IRRI), supported studies
in several countries to investigate the impact of FSR. In Thailand, an impact
study was conducted by social scientists from Chiang Mai University and Phayap
University together with personnel from the FSRI. The study area, amphoe Dok
Kham Tai, Phayao, was selected under the guidance of the FSRI. The two
mature technologies introduced by the Integrated Rainfed FR/D project were
the subject of investigation. The main objective of the study was to determine
the changes in productivity and income of farmers who adopted the new
technologies in the rainfed areas of Dok Kham Tai. The specific objectives were
to determine the level and extent of adoption of the new technology introduced
in the project site and in neighboring areas; to estimate changes in net farm and
household incomes resulting from the adoption of the new technology in relation
to other sources of household income; and to examine the adoption of the new
technology and its benefits to different groups of farmers.
The study lasted 3 yr (1989-91). The first 2 yr were devoted to data
collection and the last year to data analysis. Following the recommendations
made during review meetings in Chiang Rai in November 1990, the study
focused on the impact on institutions and communities. It was felt that without
this aspect, impact assessment might be viewed as inadequate. Therefore, this
study included the extent to which technologies and recommendations were
adopted by extension officers and farmers; and the contribution of FSR to
improvements in the capability of the research systems to meet the needs of its
clients. However, greatest emphasis was given to the original objectives because
this was the initial orientation of the study in 1989.

Conceptual framework
STUDY METHODS
To determine the impact of FSR technologies on the productivity and income of
farmers in the rainfed areas, a causal relat~onship should be established. Had the
changes took place because of the new technologies and the operations of the
FSR project? In the case of mungbean before rice and DSR, cause and effect
relationships could be established for income and productivity because both
technologies were unknown in the area before the project was introduced.
Changes in income and activities of the household could be directly attributed to
mungbean because the land would otherwise be left fallow. A comparison could
also be made between DSR and TPR. Other changes in the communities, such
as living conditions, education, health, migration, and off-farm employment,
were also studied.
Data collection and analysis
In 1989, DSR was no longer practiced by farmers in Dok Kham Tai. Earlier,
however, it had been widely adopted in the area. In the district extension office,
no mention was made of DSR and no statistics were collected. The team
concentrated on the adoption of mungbean before rice, but was puzzled by the
disappearance of DSR from the area.
A preliminary rapid rural appraisal followed by a formal survey was
conducted during the first year (1989). A total of 160 households were
interviewed using structured questionnaires. The sample was stratified as
130 households within the project area, consisting of 100 adopterz of mungbean
before rice and 30 nonadopters; and 30 households in amphoe Jun, Phayao, a
district adjacent to but outside the project area, but had a similar agroeco!ogical
environment.
In the second year (l990), 30 households from the 100 households
planting mungbean were selected for further data collection. Household records
on crop-production practices, farm income, and expenditures were maintained
every 2 wk. Two research assistants were assigned to collect data and to record
other socioeconomic changes in the communities. Data were analyzed using
descriptive statistics.
Dok Kham Tai study site
Dok Kham Tai is a district in Phayao with an area of 77,800 ha. About 18,900 ha
are ricefields and 5,800 ha are upland areas. The district is a long strip of land in
the center of Phayao. It is bounded by mountain on the east. The area slopes to
the west. The Mae Ing River runs across the northwest border, and the Rong

Chang River cuts through the middle of the district. Administratively, the district
is divided into eight tambons (subdistricts). The experimental plots were in
tambon Don Sri Chum and tambon San Koang.
All of Don Sri Chum is essentially ricefields; whereas, San Koang has
about 16% upland area. Don Sri Chum is largely lowland with a reasonably
stable rice production (Patanothai 1983), except for areas near the Mae Ing and
Rong Chang Rivers, which flood in some years. The rice area in San Koang is a
mixture of both uplands and lowlands and has a higher percentage of upland
rice. Its rice production is less stable. Tambons Ban Tham, Ban Pin, and Huey
Lan are ricefields. They have relatively less rice area (63-71%) than tambons
Dok Kham Tai and Don Sri Chum (97%).
The estimated population of Dok Kham Tai in 1990 was 77,297. The
majority are involved in rainfed farming. Rainfall averaged 1,052 mm from 1981
to 1989 alld had a bimodal pattern with a lapse in June. Rainfall variability is a
common problem in this district. Farms experience either floods or drought
every 2 yr and, as a result, the district is well-known for poverty and out-
migration.
Transpl;lnted rice is the main crop in the lowlands during the wet season
(WS). In some years, farmers experience delayed or inadequate rainfall. In some
tambon, it is possible to grow field crops (e.g., garlic and soybean) in the
ricefields during the dry season (DS). Most of the land, however, is left fallow in
the DS until August. In the uplands, maize - mungbean is the most popular
cropping pattern. Since 1984, when mungbean before rice was introduced, it has
been widely practiced in the uplands. The cropping intensity in Jun is higher
than in Dok Kham Tai. However, double cropping is possible in Dok Kham Tai.
The district has a reputation for migration of young girls seeking off-farm
jobs in the cities. They are usually employed in bars, massage parlors, night
clubs, and brothels. Remittances from these migrants result in ma:erial
prosperity in the district in terms of big new houses, cars, and electrical
appliances. Young men migrate to the cities or even overseas as construction
workers.
Exchange labor for farm work is uncommon in Dok Kham Tai.
Additional labor is usually provided by nearby areas or districts. The wage rate
increases during transplanting and harvesting when the demand for labor is high.
Expansion of area planted to mungbean
The research stages and the expansion of the area planted to mungbean before
rice from 1982-83 to 1985-56 are shown in Table 3. Mungbean before rice was
widely adopted during the pilot-production stage. Mungbean covered 62.4 ha in
Phayao Province in 1985-86. In the same year, information collected by the
impact team suggested there were 13.8 ha planted to mungbean in Dok Kham

Tai. Mungbean was introduced in Dok Kham Tai in 1983. From an experimental
area of 9.6 ha in 1984 it espanded to about 1,600 ha in 1990 (Table 4). In 1987,
658 households adopted mungbean in Dok Kham Tai (Table 5). However, the
cultivation of mungbean had been affected by frequent floods and waterlogging.
In 1989, floods destroyed much of the mungbean and lowered farm income. As a
result, many farmers abandoned the cultivation of mungbean a year later.
In 1990, 1,376 ha in the upland areas of tambon San Kaong were planted
to mungbean (Table 4), but much less was planted in the other tambons (11-S8
ha). Although many farmers successfully planted mungbean, the price fluctuated
widely and so did income. Many farmers abandoned mungbean cultivation in
1989 because prices were low at THB6-8/k (Table 6). In 1991, however, the
price of mungbean increased to THB~o-I~,~~. Those who had continued to
plant mungbean obtained high profits.
The average area planted to mungbean per liousehold isas 2.1 ha in 1988
and 2.2 ha in 1989. In 19S8, 19% of farmers planted mungbean on less than
on 0.8 ha of land-. The rnaior,ity (-35%) planted on 0.8-1.6 ha. Only 14% planted
on more than 3.2 ha (Tahie 7).
Data from the field sune!, rei,ealed that the average yield of rnungbean
was 250-300 kg/lia. This \+.as much lou'er than the estimated potential level of
550-1000 kg/ha. About 10% of the farmers obtained an average yield of
500 kg/ha or more. Most farmers (79%), however, obtained 375 &/ha or less in
1988. Yields were generally higher for mungbean planted in small plots
(0.5-0.6 ha) because of better management and more thorough harvesting than
in the large plots (Table S). During harvesting (July-August), labor is scarce and
expensive because it coincides with rice cultivation
Costs and returns of mungbean bcforee rice
Flooding in 1938 destroyed most of the niungbean crops especially in Dok Kham
Tai. About 175" of the farniers surveyed had totally lost their crop. Flooding
recurred in 1989 and many farmers gave up planting mungbean.
Variable cash costs per household were, on the average, TFIB1.278;
whereas, gross margin was TMB2,S70, excluding f~mily labor costs ('Table 8). If
family labor costs \yere included, the gross margin was only THB506. The
maximum area planted to niungbean per household was 8.7 11:~. 'T1:e ri?xiirnum
gross margin per household &.as THB31,6S1 (e:icluding Iariiil!: labor costs) clnci
THB22,700 (when farnily labor cost isas included). Farmsrs \;,lie here affected
by floods suffered losses. One farmer lost TIiB5,510. Avera~c: Ivsscc due tc
flooding were about THB70,Y.
Farmers who had an average yield of about 375-500 1x/lia and planted on
an average of 2.8 ha, had gross margins of THB11394 in 1988 (Table 8).
Average gross margin (excluding family labor) per hectare was TtiB1,691 for all

yield ranges. When family labor costs were included, gross margin (2) per
hectare was reduced to THB569. Gross margin per hectare could be THB3,750-
5,100 if the yield was 375-500 kg/ha. This would be THB2,638-3,981 per hectare
if family labor was deducted. This level of gross margin is lower than the
estimated level of THB5,625/ha.
Additional details were collected on planted area, output per hectare,
costs, and gross margin for mungbean before rice and were classified by farm
size. Farms were categorized as small (0-1.6 ha), medium (1.7-3.2 ha), and large
(greater than 3.2 ha). These categories were used as a proxy for socioeconomic
status. Small-scale farmers planted an average of 1.0-1.2 ha to mungbean and
obtained a yield of 306-319 kg/ha. Variable costs (cash) were THB681-925/ha.
Gross mar in (excluding family labor) was THB2,175/ha in 1988 and
THB1,000$ha in 1989 (Table 9). On a per farm basis, small-scale farmers
obtained a gross margin of THB1,822 in 1988 and THB1,219 in 1989. However,
large farms obtained lower yields (169-244 kg/ha) and lower gross margins
(excluding family labor) than small-scale farmers. On average, they obtained
THB3,360-4,830 gross margin (excluding family labor) per farm. Some successful
farmers obtained THB19,280-31,684 of gross margin (excluding family labor)
from their mungbean crop. If family labor costs were included, these farmers
would obtain a gross margin of THB12,980-22,700.
Opinions of farmers
The 100 h~useholds surveyed in 1989 were surveyed again in 1990 to determine
the opinion of the farmers about the performance of mungbean in 1989. The
floods that occurred in the project area for two consecutive years had a negative
effect on the attitudes toward mungbean. The majority (90%) of the households
continued to plant mungbean before rice until 1989. These results were obtained
when DSR regained popularity in 1990. Responses with regard to DSR were
insufficient.
Farmers continued to plant mungbean before rice because it provided
money to support the following rice crop, it increased rice productivity, it
increased household income, and prices were high in some years. The reasons
why farmers abandoned the cultivation of mungbean were: floods, late rains that
led to a conflict in timing of the mungbean harvest and rice transplanting (or
DSR), increased insect problems, and low price in some years.
The responses of farmers concerning the interrelationships of mungbean
before rice and other components in the farming systems are as follows:
Rice productivity. The majority of farmers reported positive effects on rice
productivity. The 13% who reported negative effects attributed these to
delays in transplanting rice.

Land preparation for rice. The reactions of the farmers to the effect of
rnungbean on land preparation were mixed. Although 32% cited ease in
land preparation for the next crop, 24% reported difficulty in preparing
the land for rice because mungbean plants were still in the field at the
time of land preparation.
Weeds in rice crop. Only 8% reported positive effects of mungbean. The
cultivation of rnungbean apparently introduced more weeds into the
ricefields.
Soil fertility. Most farmers (74%) agreed that the planting of rnungbean
improved the soil in their fields. The 3% who reported negative effects
cited the need to apply fertilizers to improve soil fertility (soil analysis
shown in Table 10).
Livestock raising. Only 5% of the farmers reported a positive effect.
Farmers observed that cows die from overeating mungbean. Others
observed that their cows grazed on their neighbors' mungbeans, creating
social conflicts.
Upland mungbean. Forty percent reported positive effects of mungbean
before rice on upland mungbean. There were no reports of negative
effects.
Mechanization. An increase in the degree of mechanization (i.e., use of
threshing machine) was observed by 21% of the farmers. However, 72%
reported no change in the level of mechanization.
Labor use. More labor was used by 60% of the farmers to plant
mungbean. There were no reports of a decline in labor use.
Capital use. Most farmers (69%) agreed that mungbean cultivation
increased capital requirements; 2470 reported no change.
Income effect. Higher incomes were reported by 42% who grew
mungbean; 29% experienced a reduction of income because of losses.
Processing. Farmers sold the bulk of their mungbean prcduce to local
merchants in the village. A small amount of mungbean was retained for
home processing (e.g., bean sprouts and desserts).
By-products. Some farmers used mungbean by-products for mushroom
culture (17%) and for compost (9%). Many farmers, however, reported
no knowledge of how to process or use the by-products.

Soil analysis
The soil was analyzed to determine if changes in mineral components or soil
texture might have affected the growth and yield of rice grown after mungbean.
The field was classified into three areas: high terrace, middle terrace, and low
terrace. In March 1991, 90 soil samples from the plots of mungbean - rice (30
samples per terrace) and 30 soil sam les from the plots of fallow - rice (10
samples per terrace) were collected P or soil analysis. Table 10 suggests that
organic matter (OM), P, and K in the mungbean - rice cropping pattern were
higher than in the fallow - rice pattern. The results from on-farm trials
conducted in 1986-88 indicated that rice yields in the mungbean - rice cropping
pattern were higher (3.75 t/ha) than those in fallow - rice pattern (3.3 t/haj
(Nichai and Rasamee 1991).
Expansion of direct (dry) seeded rice
The UNDP/FAO project reported that there had been an expansion of
DSR (i.e., 1,484 ha in five provinces, of which 1,276 ha were in Phayao in
1985-86) (Table 11). In 1989, there was hardly any DSR areas in Phayao. Field
researchers who introduced mungbean before rice and DSR in 1982 attributed
the shift to TPR to good rainfall In 1986-88. DSR reenierged in 1990 on about
160 ha because of late rains in 1989. However, in 1991, 163 households (about
419 ha) adopted DSR. Many farmers ordered mechanical seeders and some
went as far as Sukothai, a province approximately 300 km away, to purchase
these machines.
Interviews with farmers in Dok Kham Tai revealed that the readoption of
DSR in 1990-91 was due to the increased wage rate during transplanting. Some
reported wage rates as high as THB100/d. This was nearly 7070 higher than the
average wage rate in other districts and in other periods of the year. The normal
wage rate was THBGO-70/d. High wage rates were associated with delays in
rainfall. When the rains come, the rush to transplant rice as early as possible
creates stiff competition for labor and produces high wage rates. The labor
requirement to transplant seedlings is about 19-31 d/ha. This is eq~iivalent to
26-39 d of hired labor for an average farm (or approxin~ately THB2,500-4,000).
However, if DSR is adopted and mechanical seeders are used, an average
farmer would need 2 d to complete crop establishment. The cost of a seeder
(THB6,OOO) could therefore be recovered in 2 yr. Farmers in areas where
seeders are scarce hired seeders at THB188/ha.
Many farmers would like to grow DSR on all of their land bzcause it is
less costly. Given the rainfall pattern, farmers who adopted mungbean before
rice found it difficult tu establish DSR in August because the soil was usually too
wet. The mechanical seeder clogged easily. Late onset of rainfall rlelays the
mungbean crop and makes establishment of DSR almost impossible. A cut-off
date for mungbean should therefore be established if DSR is to be successfully
implemented. Some farmers purposely plowed their mungbean crops in early
August before it was fully harvested to make way for DSR. In 1991, when the

price of mungbean was high, some farmers wondered whether they had made
the correct decision.
The limited number of mechanical seeders was also a problem. In 1990,
FSRI had only three units in tambon San Koang. There was long waiting lists for
the use of these machines that year. In 1991, 16 more machines were purchased.
Large farm owners purchased their own mechanical seeders. Small- and average-
size farm owners hired machines (with operators TEIBZOO/d; without operators
THBlSOId). With the use of a one hand tractor, about 1.6 ha of land can be
covered in a day. Although the availability of seeders improved in 1991, farmers
still had to reserve the machines and wait for their turn.
Currently, many farmers make provisions for doing either DSR or TPR.
They prepare rice nurseries alongside the plots prepared for direct seeding. This
strategy provides a hedge against possible delays in transplanting if DSR cannot
be established. If direct seeding is possible, they can still sell their seedlings
to other farmers.
In a follow-up interview after the rice han-est in 1991, it was found
that the business of renting seeders was becoming popular. Some farmers talked
about purchasing additional seeders merely for this purpose. The 19 seeders in
the area were shared by 163 farm households in 1991 (i.e., an a\.erage 22 ha per
seeder). Farmers in the other tci)~lho)rs are also interested in the machines.
Information on yield, costs, and gross margin of DSR were also collected.
Only a few farmers were surveyed in 1990 because the practice was just being
revived when the impact study was about to end. h4ost of the information
concerning DSR in Dok Kham Tai in 1990-91 was obtained through informal
interviews. Yields from TPR and DSR were comparable among small and
medium farms (i.e., 2,588-2,688 kg/ha for DSR and 2,625 kg/ha for TPR). The
weed problem in DSR was more common and severe than in TPR. This was one
reason why farmers were slow to adopt DSR. The early adopters of DSR
experienced severe weed problems. Farmers, ho\+.ever, minimized yield loss
caused by weeds by more tt~orough land preparation (repeated tillage) and by
alternating DSR and TPR.
Among mungbean adopters, yields of TPR averaged 3,-t 19 kg,/ha in 1988.
This was higher than the average output of DSR. Costs per hectare were also
higher. Gross margin (excluding farm labor) was TFIB8,706/ha compared with
THB5,331/ha for DSR. Gross margin (including farm labor) for TPR was
THB7,581/ha but only THB3,700/ha for DSR. However, the Iligher yields and
gross margins for TPR compared with DSR are not conclusive becalise yields
were obtained during different periods.

Possible time conflict between mungbean and direct seeded rice
Delayed establishment of the mungbean crop because of the late onset of rains
poses a serious problem for DSR. If the onset of the rains is delayed until late
May, farmers must make a choice between mungbean and DSR. If mungbean is
to be planted and harvested, the rice crop must be transplanted. DSR could not
be established in wet soil because the mechanical seeders clogged. However,
TPR faces the risk of receiving inadequate rainfall for vegetative growth.
The probability of the accumulation of an adequate amount of rain
(75 mm) for crop establishment after the onset of the rainy season was
determined. If mungbean is planted on 1 Apr, the probability of adequate
rainfall is 0.1 (one in 10 years). If mungbean is planted on 21 Apr, there is about
a 0.7 probability of adequate moisture. A cumulative probability of a backward
accumulation of 500 mm of rainfall is necessary for a rice crop (Morris and
Zandstra 1978). Using this criterion and an 85-90 d growing season for
mungbean, DSR planted about 11 Jul has a 0.7 probability of a backward
accumulation of 500 mm of rain.
If farmers decide to keep the mungbean crop and choose TPR, they will
encounter several consequences. They will experience a lower probability of
adequate rainfall (50%) and will need rice seedlings for transplanting. Labor
costs for transplanting will also be higher than for DSR.
Currently, farmers in Dok Kham Tai are refining their knowledge about
these two technologies. If they adopt both mungbean and DSR. They can derive
greater benefits. Adopting any of the technologies can directly, or indirectly
improve income by reducing costs.
The probability of 10-d and 15-d dry spells in Dok Kham Tai were
determined using 10-yr 1981-91) rainfall data. The probability of 10-d and
15-d dry spells (< l mm i d) is 0.6 or 6 in 10 yr during late May and mid-June.
Mungbean affected by dry spells had low productiv~ty in Dok Kham Tai.
However, DSR requires a period of dry weather during seeding. If planted in
mid-June, the probability of having dry spells is still high. However, if planted
at the end of July, the probability drops to about 0.2 (two in 10 yr). It is not
practical to use DSR in August because of the probability of 5-d dry spells
(

manufacturers. The earlier models (e.g., l-row, 2-row, and even 3-row machines)
were unsatisfactory when tested on farms. In 1985-86, when DSR was popular,
the seeders used by project personnel were 2-row machines operated using
manual labor. Further modifications were done after a dialogue with farmers,
FSRI field personnel, and researchers from the Division of Agricultural
Engineering. In 1986, a 4-row model drawn by a small tractor was tested in
tambon San Koang. This inodel is now popular in the study area.
The role of Dok Kham Tai Agricultural Extension Office
After the project ended in 1986, the Department of Agricultural Extension
ceased to work with FSRI. It is unfortunate that the personnel of the District
Office of Agricultural Extension in tambon Kaset were new appointees, thus,
they were unaware of the events that had taken place before 1986. They learned
about mungbean before rice from farmers. but they learned nothing about DSR.
(Our team provided them with information about the practice and popularity of
DSR in Dok Kham Tai.) The agricultural data they collected were highly
aggregated. For example, information on mungbean from lowlands and uplands
were aggregated into a single category. Similarly, DSR and TPR were taken as
one category.
Role of farmers in adaptation and testing new technologies
Farmers in the area were active in testing new technologies. They observed the
performance of new technologies in their neigllborhood, sought new ways of
doing things, and knew about sources of seed varieties and farm machinery. For
example, a FSRI cooperator \vho planted mungbean (Utong 1) wanted new
varieties that would perform better. He went to Kasetsart University in Bangkok
to buy Kampaengsaen 1 and 2, which were not available in his area. Later, he
found that Kampaengsaen 2 was more appropriate to his cropping system. He
was also among the first farmers to test DSR, but he was not very successful
because of weed problems.
Threshing machines are essential for mungbean production. The project
offered a threshing machine that worked well but was not yet available in the
market. A group of farmers traveled to Khon Kaen. Northeast Thailand. to
purchase one for their own use and for renting at THBO.SO/kg. In 1?90, about
5-6 more threshers were available in tambon San Koang. M~ingbean was initially
planted using a mechanical seeder. Later, through dialogue with farnlers, it was
agreed that broadcast seeding would be a better method.
When problems concerning rainfall patterns and high labor costs in TPK
were encountered, some farmers thought about the possibility of DSR. Farmers
experimented with ways to control weed problems through good land
preparation and alternation of DSR with TPR. They also sought information
about obtaining 4-row seeders and traveled to Sukothai to purchase one.

Many of these adaptations were spearheaded by advanced farmers,
farmer leaders, and medium- to large-size farmers. These farmers have enough
capital to invest in their farms, to experiment, and to try new methods.
Eventually, the benefits of the new technologies diffuse to small farmers as well.
Expansion of mungbean and DSR in neighboring areas
In 1985, there was an expansion in the area planted to DSR and mungbean
before rice. For example, in Chiang Rai Province, there were 17.6 ha of
mungbean before rice, 7.2 ha of DSR; in Lampang province, 58.4 ha of
mungbean, 159.0 ha of DSR; and in Phrae, 8.6 ha of mungbean and 41.8 ha of
DSR. After 1985-86, statistics on mungbean and rice were aggregated in such a
way that it was impossible to ascertain changes. Initial interviews revealed that
expansion of the areas planted to these crops was limited to the original sites.
Adoption, however, was not substantial because of problems with marketing,
inadequate research and extension support, and the need for machinery. The
experience in Dok Kham Tai indicated that continuous support by research and
extension personnel is critical to sustain adoption.
SOCIOECONOMIC CONDITIONS OF ADOPTERS AND NONADOPTERS
The disappearance of DSR in 1986-89 limited data collection on mungbean -
rice adopters: Socioeconomic conditions were assessed among adopters and
nonadopters of mungbean before rice both within and outside the project area.
Table 12 shows important socioeconomic indicators of the three groups.
Land size and distribution
Adopters of mungbean before rice had larger ricefields and more upland areas
than nonadopters. The average farm size was 2.2 ha among adopters and 1.8 ha
among nonadopters both inside and outside the project area. For all farms
(including the upland areas) the average size was 2.7-2.9 ha. Of the adopters,
s~nall farmers (approximately 1 ha) constituted about 30% of the total. Small
farmers who were nonadopters constituted 50-53% of the total and had about
1.1 ha of land. The percentage of adopters who were medium and large farmers
(33-3796) was greater than for nonadopters (16-33%).
Land tenure
Most adopters were owner-operators (96%) compared with 73-80% of
nonadopters.

Net farm income per household
The adopters of mungbean before rice had higher net farm incomes per
household than nonadopters. Comparisons of net farm incomes of adopters and
nonadopters indicated that the new technologies contributed to an improvement
in income. Among small and medium farmers, adopters and nonadopters outside
the project area had higher farm incomes than nonadopters ~vithin the project
area. It appeared that farming in Dok Kham Tai was generally not as productive
as it should have been even with improved technologies. Without new
technologies, farm income in Dok Kham Tai was significantly less than in other
districts, especially for small farmers. Farmers in Dok Kham Tai had high farm
incomes only if they operated large farms.
Farm expenditure
Farm expenditures were, on the average, higher among adopters than
nonadopters both in and outside the project area, part~cularly for small- and
medium-size farms.
Off-farm and nonfarm occupation and income per household
Adopters obtained more income from farming; whereas, nonadopters in the
project area derived income from nonfarm and off-farm sources. Off-farm
income per household \rras higher for nonadopters in the project area
(THB22,841) than for adopters (THB9,703) and for nonadopters outside the
project area (THB3,114). Off-farm employment sources included construction
work, furniture making, vehicle repairs, sewing, farm Iabor, handicrafts, and
processing and sale of farm products. Among nonadopters in Dok Kham Tai,
salary-earning jobs were also available. Nonadopters in large farms both in and
outside the project areas had higher farm irlconies than adopters. Nonadopters
with large farms within the project area also had higher farm incomes because
their average farm size \vas larger (6.2 ha) than that of adapters (4.8 ha). For the
nonadopters outside the project area, rice cultivation was more productive
(3,806 kg/ha) than for adopters (3,250 kg/ha); therefore, the farni income of the
nonadopters was higher.
The availability of off-farm and nonfarm occupations in the project area
positively contributed to the adoption of labor-saving technology (e.g.,
mechanical seeder). Given the availability of off-farm job opportunities in the
project area, it is expected that the potenti:ll to expand DSR (labor-sa\zitig) is
greater than the potential for mungbean before rice (labor-usir?g).
Labor use
The introduction of mungbean before rice contributed to grzater use of
labor in May-July. Without mungbean before rice, labor was not used except

during the establishment of nurseries for the rice. The harvest of mungbeans,
however, sometimes conflicted with land preparation for WS rice. Some farmers
left their mungbeans unharvested to prepare their land for the next rice crop.
Migration of young people
The improvement in farm income did not slow down the migration of young
people to the cities. Among the adopters, 44% of the households had one or
more members who migrated to the cities compared with only 33% among the
nonadopters. However, nonadopters outside the project area had the largest
numbers of migrants (53%). The study team found that farming was increasingly
becoming an activity for middle aged and older people in the community. In Dok
Kham Tai, young men and women did little farm work. Scarcity of labor for farm
work was especially noticeable and resulted in higher wages and the presence of
labor from other districts.
Livestock
More adopters kept livestock than nonadopters.
Education
The level of education was evaluated on the basis of attendance of farm children
in high schools and tertiary schools. Nonadopters had a greater percentage of
children in tertiary schools.
Health
Of the adopters, 83% reported that household members were in good health,
comj~ared with 70% among nonadopters outside the project area. Nonadopters
within the project area were healthier (87%). These rough health indicators
suggested that the population of Dok Kham Tai (whether adopters or
nonadopters) were better-off than farmers in Jun district.
Savings and loans
Of the adopters, 30% had bank savings; whereas, only 28% of nonadopters in
the project area and 20% outside the project area had bank savings. Equal
numbers of adopters and nolladopters outside the project area borrowed money.
In contrast, 47% of nonadopters in the project area borrowed morley. It seems

that although adopters were better off than nonadopters in terms of savings, they
were as much in debt as nonadopters.
Assets
Adopters had more household assets than nonadopters. For example, 61% of the
adopters had hand tractors compared with 22% of nonadopters in the project
area. Adopters also had more livestock, trucks, motorcycles, bicycles, sewing
machines, rice barns and livestock houses compared to nonadopters, especially
those outside the project area.
Improvement in standard of living
About 92-93s of the households in all groups reported an improvement in their
standard of living during tlie last S vr. Only 5% of adopters reported a
deterioration in their standard of lhing compared with 8% among nonadopters
in the project area and 7 9 among those outside the project area.
Adopters of rnungbean - rice technology appeared to be more active in
farming than nonadopters in the project area. Adopters also engaged in livestock
enterprises more than nonadopters in the project area.
Nonadopters outside the project area were as acti\,e as adopters and
earned as much from fuming. Havever, their income frorn off-farm
employment and li\.estock was less than the adopters. Their out-migration rate
was also higher and they depended more on remittances than adopters. Their
health cond~tions and savings icere also slightly lower than adopters and
nonadopters in the project area.
hlungbean before rice
CONCLUSION
Although rnungbean before rice appeared to be a relativelv simple new
technology that would provide farmers with supplemental jncome, a closer
examination of the adoption of mungbean before.rice re\.ealed that it had tmtli
strengths and weaknesses.
Strengths
¤ It provided supplemental income and helped ease capital requirements
for the follo\ving rice crop.
Q.
.d

m It was easy to establish and required few inputs (including labor).
m It fitted the bimodal pattern of rainfall, intensified the cropping system,
and used labor when there was little opportunity cost.
m It positively contributed to soil fertility, rice yields, the use of by-products,
and upland mungbean increased mechanization and livestock feeding.
m It was widely adopted in rainfed upper ricefields in Dok Kham Tai.
Weaknesses
m The yield and income from mungbeans in the field were low compared
with the expected level.
m It was not suitable in lower ricefields that were prone to waterlogging and
flooding.
m In some years, prices of mungbean were low, which produced low income.
m In some years, the onset of the rainy season was delayed, which resulted
in a conflict between harvesting mungbean and planting rice. The growing
season for mungbean had conflicted with the timing of DSR.
m Recently, there had been some insect problems with mungbean that
require attention from research and extension personnel.
Direct (dry) seeded rice
The expansion of DSR was interesting in Dok Kham Tai. It was adopted,
abandoned, and readopted in a period of 7 yr (1984-91). The period with a good
rate of adoption was 4-5 yr after the project ended. The development of
appropriate machinery, which took several years, was an important factor that
contributed to adoption. Increased labor costs during mungbean harvesting and
rice transplanting helped accelerate the process of adoption. DSR displayed the
following strengths and weaknesses.
Strengths
It substantially reduced the costs of planting rice.

W It produced a good stand of rice that escaped drought toward the end of
the WS.
H It reduced the risk of low rice yields because of dry spells that delayed
transplanting operations.
H It was simple and convenient, especially with the use of mechanical
seeders and small tractors.
H The level of yield obtained from direct seeding was comparable to
transplanting.
Weaknesses
¤ It suffered from w.eeds, sometimes seriously.
¤ It required mechanical seeders for planting operations, but sometimes
these mechanical seeders were scarce.
H It could not be done if the soil was too \vet.
The study of these two mature technologies identified and recommended
by the project reveals that even the so-called mature technologies require many
adaptations. Adequate follow-up is needed. Continuity in research and links to
extension must be ensured. Adaptation and testing of new technologies by
farmers must be encouraged and recognized. The process of FSR is not simple
and clear-cut. New problems arise, and new research topics must be generated
from local problems. Constant interaction among FSR researchers, extension
officers, and farmers is a must.
At the same tirne, this case demonstrates the potentials and limitations of
FSR scientists. FSR researchers can make important contri1)utions to adaptive
research and can act as a link between experiment-station scienti$ts and farmers.
However, when a technology is ready for extension. FSR researchers cannot
adequately cope with the extension requirements of a large number of farmers.
Nor can FSR researchers cope with the diverse ran6e of environments found in
farms if the technology expands on a wide scale. Th~s limitation on the part of
FSR scientists points to the important role of extension officers and farmers
themselves in further adaptation of new technologies.

REFERENCES CITED
Morris R A, Zandstra H G (1978) Land and climate in relation to cropping
patterns. Pages 255 -274 itt Rainfed lowland rice: selected papers from
the 1978 International Rice Research Conference. International Rice
Research Institute, Manila, Philippines.
Nichai T, Rasamee K (1991) Green manure in paddy rice cropping system.
Paper presented at the Conference on the Progress on Biotechnology:
Agriculture and Environment, 12-14 Nov 1991 at Chiang Mai Orchid
Hotel, Chiang Mai, Thailand.
Patanothai A (1983) A review of the rainfed crop production research and
development project. Department of Agriculture, Thailand.
Suvanchinda P, Nichai T, Suwan H, Hatsachai B, Vicharn V, Pracha D, Sompet
K (1986) Pilot production in target areas in the rainfed agricultural
project [in Thai]. Irz Proceedings of the Third Farming Systems Research,
2-4 Apr 1986, Chiang Rai University, Thailand .
UNDP/FAO -- United Nations Development Programme/Food and Agriculture
Organization (1986) Integrated rainfed farming research and
development Thailand. Project finding and recommendations.
(~inp~blished).

Table l. The promising technologies (1986).
~ -
P
P P Pp
Package of technology - Status of technology No. of farmers Area covered Provinces
in 1986 participating 1985-1986
1985-1986
1. Direct seeding of rice trials Multilocation testing, 645 1,522 ha 7
preproduction
2. Mungbean - rice cropping system Multilocation testing, 373
preproduction trials
3. Jute - rice cropping system Multilocation testing 24 3.8 ha 4
4. Kenaf - rice cropping syslcln Multilocation testing 52 14.4 ha 4
5. Crops - pig fattening system On-farm trials 6 139 m2 2
G. Crops - duck in paddy fields On-farm trials 22 1,100 m' 1
7. Cl-ops - pigs - ducks - fish On-farm trials 7 7,150 m2 2
in farm ponds
Source: [JNDPIFAO 1986 (figures converted from rai to hectares).

Table 2. Details of the two technologies presented by the project.
Components of
technology
Agroclimatic
suitability
Direct seeding Mungbean - rice
of rice cropping systems
Variety
RD-6, RD-8 Utong 1, VC 1178
RD-15, KDML-105 Kampaengsaen 1,2
Fertilizer
125 kglha 125 kglha
(1 6-20-0) (1 6-20-0)
62.5 kglha
(2 1-0-0)
Pest Control
Furadan 3 1.25 kglha Furadan 18.75 kglha
Saturn G Lanate 75 mL/ha
25 kglha
Machete
Agroecological zone
R3S6 R3S6
Soil texture
Clay to sandy Clay to sandy
loam loam (upper paddy)
Yield (kglha) 1,706-3,062 550-1,006
Economic viability (THBIha)
Production cost 4,113-6,938 7,913-11,169
Gross revenue 4,944-8,875 12,344-16,800
Gross margin 831-1,938 2,975-5,630
Provinces introduced Phayao, Chiang Rai Phayao, Chiang Rai
Phrae, Lampang, Phrae, Lampang,
Phattalung, Surin, Phattalung, Nakorn
Nakorn Sri Tharnmarat Sri Thammarat
Source: UNDPIFAO 1986 (figures converted from rai to hectares).

Table 3. Mungbean before rice areas (1982-83 to 1985-86).
Year Research stage Place Areas Yield (kglha)
(ha) Mungbean Rice
1982-1983 On-farm trials
Phay ao
1983-1984 On-farnl trials
On-farnl trials
1984- 1985 Multi-location
testing
Multi-location
testing
Multi-location
testing
On-farm trials
1985-1986~ Pilot production
Pilot production
Pilot production
Multi-location
testing
On-farm trials
Amphoe Mae Jai,
Amphoe Mae Jai
Amphoe Mae Jai,
Chiang Rai
Amphoe Mae Jai
Amphoe Mae Jai
Amphoe Mae Ta
Amphoe Kuan
Kanon, Pattalung
Phayao Province
Chiang Rai
Lampang Province
Phrae Province
Pattalung Province
a~ncludes
6 amphoes in Phayao Province; 6 amphoes in Chiang Rai Province; 9 amphoes in
Lampang Province; 3 amphoes in Phrae Province; and 1 amphoe in Pattalung Province.
Source: Suvanchinda et al. 1986 (figures converted from rai to hectares).

Table 4. Area (ha) planted to mungbean before rice in Dok Kham Tai, Thailand (1984-1991).
San Koang
Pa Sang
Don Sri Chum
Ban Tum
Dok Kham Tai
Nong Lom
Huai Lan
Ban Pin
Total
Source: Dok Kham Tai District Agricultural Extension Office (figures converted from rai to hectares).

Table 5. Number of farm households planting mungbean before rice.
Tambon 1984 1985 1986 1987
San Koang
Pa Sang
Don Sri Chum
Ban Tum
Dok Kham Tai
Nong Lom
Huai Lan
Ban Pin
Total
-
Source: Dok Kham Tai District Agricultural Extension Office.

Tablc 6. Prices 2nd yield of mungbcan bcfosc sicc.
Price per kg 7 9 6-8 6-8 9-11 6-8 5-7 10-1 1
Yield (kglha) 687.5"
Utong 1 VC 1178 I

Table 7. Area planted to mungbean, Dok Kham Tai, Thailand (1988-89).
Planted area
(ha)
Total
average
planted area (ha)
Maximum (ha)
Minimum (ha)
Note: Figures converted from rai to hectares.
No. of farmers % No. of farmers %
1988 1989

Table 8. Area planted to mungbean, costs, and gross margin, Dok Kham Tai, Thailand (1988).
Yield Planted area
range (ha)
(kg1 ha)
Average (94 cases) 2.1
Average for those who
had some output
(78 cases)2.1 1,377
Variable cash
cost
(THBIha)
Variable costs
(including family
labor)
(THBIha)
Gross margina
(THBIha)
Gross margin b
(THBIha)
b
aGross margin is total value of production minus variable cash costs. Gross margin is total value of production minus variable
cash costs and estimated cost of family labor.
Note: Figures converted from rai to hectares.

Table 9. Area planted to mungbean, costs, and gross margin, Dok Kham Tai, Thailand (1989).
Yield Planted area Variable cash Variable costs Gross margina Gross margin b
range (ha) cost (including family (THBIha) (THBIha)
(kg/ha) (THBIha) labor)
(THBIha)
AV (94 cases)
AV for those who
had some output
(78 cases)
Maximum
Minimum
'~ross margin is total value of production minus variable cash costs. b~ross
margin is total value of production minus variable
cash costs and estimated cost of family labor.
Note: Figures converted from rai to hectares.

Table 10. Soil analysis of various lowland types under different cropping patterns, Dok-Kham Tai District (1991).
Lowland type
Low terrace . Middle terrace High terrace
MO M1 MO M1 MO M1
Texture Clay
Loam
Clay Clay Clay Loam
Clay
Note: MO = fallow - rice; M1 = mungbean - rice; figures in parentheses are ranges.
LR = lime requirement

Table 11. Area under dry seeded rice and rice yields (RCPRD project).
Year Research stage Areas Yield (kglha)
(ha)
Dry seeded Wet
198 1-1982 a On-farm trails
1982-1983 a On-farm trails
1983-1984 a Multilocation testing
1984-1985 Multilocation testing
1985-1986 Multilocation testing
Average
a1981-1982, 1982-1983, and 1983-1984 were areas in Dok Kham Tai. 1984-1985: Dok
Kham Tai 306.3 ha; Mae Ta, Lampang Province, 1.9 ha; Mae Suai, Chaing Rai Province,
1.9 ha; Kuan Kanoon, Pattalung Province, 4.0 ha. '1985-1986: includes 6 amphoes in
Payao Province, 1,276 ha; 6 amphoes in Chiang Rai Province, 7.2 ha; 12 amphoes in
Lampang Province, 159 ha: 3 amphoes in Phrae Province, 41.8 ha; 2 amphoes in Pattalung
Province, 25.8 ha.
Source: Suvanchinda et a1 1986 (figures converted from rai to hectares).

Table 12. Socioeconomic conditions of adopters and nonadopters both in the
project area and outside the project area.
No. of farmers in sample
Average size of farm (ha)
Average size of upland (ha)
Average land size (ha)
Small farm (0- 1.6 ha)
Medium farm (1.8-3.2 ha)
Large farm ( > 3.2 ha)
All farms (ricefield + upland)
Land tenure (%)
Land productivity
(measured as average
rice yield in kglha)
Small farm (0-1.6 ha)
Medium farin (1.8-3.2 ha)
Large farm ( > 3.2 ha)
Land distribution
(percentage of group)
Small farm (0-1.6 ha)
Medium farm (1.8-3.2 ha)
Large farm ( > 3.2 ha)
Net farm income (THB)
Small farm (0-1.6 ha)
Medium farm (1.8-3.2 ha)
Large farm ( > 3.2 ha)
All farm sizes
Off-farm income
per household (THB)
Small farm (0- 1.6 ha)
Medium farm (1.8-3.2 ha)
Large farm ( > 3.2 ha)
All farm sizes
Adopters Nonadopters
In project Outside
area project area
-

continued.. .
Table 12. Socioeconomic conditions of adopters and nonadopters both in the
project area and outside the project area.
Adopters Nonadopters
In project Outside
area project area
Total income (farm + off-fainl)
Small farm (0-1.6 ha) 25,609 30,304 14,803
Medium farm (1.8-3.2 ha) 28,934 40,083 32,844
Larse farm ( > 3.2 ha) 48,110 61.510 49,589
All farm sizes 34,320 38,589 27,292
Off-Tarn], nonfarm occupation
(%)
Wage labor
Salary earning job
Commerce
Average off-farm. nonfarm
income by sources (THB)
all farin sizes
Wage labor 3,654 1,997 1,782
Commerce 3?325 13,170 42 0
Salary earning job 702 5,250
Remittance 1,075 1,267 4,633
Off-farm \\!age labor (TI-IB)
Small farm (0-1.6 ha) 2,899 2,000 3,216
Medium farm (1.8-3.2 ha) 2,106 2,967 188
Large farm ( > 3.2 ha) 5,967 5 0 83
All farm sizes 3,654 1,997 1,782
Commerce (THR)
Small farm (0-1.6 ha) 5,695 20,694 -
Medium farm (1.8-3.2 ha) 2,581 667 625
Large farm ( > 3.2 ha) 2,024 15,602 1,267
All farm sizes 3,325 13,170 420
Salary-earning job (THR)
Small farm (0-1.6 ha) 2,333
Medium farm (1.8-3.2 ha) 11,300
Large farm ( > 3.2 ha) 1,900 -
All farm sizes 5.250 -

a % Table
continued.. .
12. Socioeconomic conditions of adopters and nonadopters both in the
project area and outside the project area.
Support from others (THB)
Small farm (0- 1.6 ha)
Medium farm (1.8-3.2 ha)
Large farm ( > 3.2 ha)
All farm sizes
Adopters Nonadopters
In project Outside
area project area
Labor Utilization more same same
Migration of young men and women
(% of households
in the group)
Average number of persons in the
household who have migrated
Livestock (q of households)
Chickens
Pigs
Cows
Buffalo
Income from remittances
(% of households
in group)
Education (observed)
Sons and daughters able
to go to secondary schools
(% of households)
Sons and daughters able
to go to tertiary schools
(% of households)

continued.. .
Table 12. Socioeconomic conditions of adopters and nonadopters both in the
project area and outside the project area.
Adopters Nonadopters
In project Outside
area project area
Health
Households
reported in good health (%) 8 3 8 7 70
Savings and Loans
Farm households with
bank savings (5%) 30 28 20
Farm households with borroived
money (72)
Assets
2-wheel tractors
Pick-ups
Motorcycle
Bicycle
Sewing machine
4-wheel tractor
Rice barn
Television
Livestock pens
Impro\~ernent in the standard of
living in 5 years (76)
Better
Worse
Same
Note: Figures con\lerted froin rai to hectares.

Table 13. Soil analysis data of various lowland type with different cropping patterns at Dok-Kharn Tai District, Phayao Province, 1991
Lowland type
Element Low terrace Middlc tcrracc High terrace
Texture Clay Clay Clay Clay Loam
MO = fallow-rice
M1 = mungbean-rice
( ) = range
Clay

l~ndicative figures only.
'~ature technology is defined as agroecolcgically feasible, econcrnicaliy
viable, and socially acceptable to farmers.
1. Linkage between research and extension.

IMPACT ASSESSMENT OF FARMING SYSTEMS RESEARCH-BASED
TECHNOLOGIES IN THE PHILIPPINES: THE ISABELA EXPERIENCE
R. R. ~onza~a', C. V. C. ~ arba~, N. P. ~ordoncillo~, and N. F. C. an awe era'
The apparent inability of conventionally developed agricultural technology to serve
the needs of resource-poor farmers has led to the popularization of Farming
Systems Research (FSR) as an alternative approach to research and development.
During the last two decades, developing countries in Asia, Africa, and Latin
America have adopted FSR and, most if not all, have institutionalized FSR in their
National Research Systems (NARS). The FSR dornain is wide and varied. Activities
in all phases of FSR are carried out in an interdisciplinary manner. Farmer
participation is a key element. The approach requires a thorough understanding of
the production systems of the farmer and the ways they are conditioned by the
biophysical, socioeconomic, and political environments. The objective is to identify
important farm production problerns and to design appropriate solutions that are
not only technically and economically feasible but also sustainable. As such, FSR
employs various tools, techniques, and methods from the socioeconomic and the
biological sciences.
In spite of this methodological complexity, FSR has been accepted because it
was deemed appropriate to the varied physical and socioeconomic conditions of
farming environments in developing countries. Since then, several FSR approaches
and processes have emerged. It is imperative to assess the impact of technologies
developed through FSR, not only to gauge their effectiveness and real contributions
to small farmers, but also to make methodological improvements and redirect future
efforts.
The question, however, is by what measure should the contributions of FSR
be assessed? In general, the explicit objective of FSR is to increase cropping
intensity and improve cultural practices to achieve liigher output and factor
productivity while increasing family income. It is implicitly assumed that the
improvement of the indicators of household welfare will follow. Ranaweera (1958)
summarized the flow of the contribution of FSR to the different quality of life
indicators (e.g., positive changes in purchasing power, asset accum~llation, quality of
education, health, and household nutrition).
The pathways to tliese quality of life indic~ltors exhibit complex relatio~~ships.
Although it is con~monly mentioned that undernutrition is almost synonymous with
poverty, and that income and purchasing power are key variables that allo\v the
household to purchase food items not produced on the farm and to diversify dietary
'social Sciences Division, International Rice Research Institute, P.O. Box 933,
hdanila, Philippines.
"7nstitute of Human Nutrition and Food, College of Human Ecoloa, University of
the Philippines Los Barios, College, Laguna, Philippines.

composition, increases in income can also esacerbate malnutrition. Jodha (1994)
contends that commercialization can adversely influence the nutritional position of
the farming household if it leads to an overall decline in the availability for
consumption of general food commodities or of specific food items with high
nutritive value. Indeed, the link between FSR technologies and the nutritional
position of the household can be directly related to the consumption of 0~i.n-farm
produce and indirectly related to the income path (Gonzaga et a1 1990).
Although improvement in these welfare vari;ibles is an ideal goal, it cannot
be overemphasized that fulfillment of one Lvelfare indicator may lead to shortfalls in
others. The household makes decisions to meet its objectives according to the order
of their priorities. Impact assessment therefore should not consider a failure to
improve one or two welfare measures as a fdilure of FSR technologies in general.
Assessment is an integral component of FSR: from the diagnostic and design
phase (ex-ante), to the testing, preproduction, and production phases (on-going), to
the extension and monitoring phase (ex-post). Although the parameters used in
impact analysis for each FSR phase differ, each of these ph;lses in\.olves
measurements related to the impact of FSR technologies. During the ex-ante and
on-going phases of impact assessment, the focus of analysis is on biological and
technical feasibility, economic viability, and sociocultural acceptability of the
technoloby (Zandstra et a1 1981). Es-post assessment, ho\ive\/er,, goes beyond these
parameters and includes other indirect effects such as changes in real income levels,
asset accumulation, educational and nutritional positions, and health of the farming
households (Ranaweera 1985). In this study. impact assessment of indirect effects is
limited to changes in household income and the nutritional position of the
household. In addition, measurable direct effects such as yield le\iels, input use, and
changes in cropping patterns are assessed.
Several approaches can be used to assess the impact of introduced technologies
(Ranaweera 1988). One approach is the 11c.fot.c and ojtc>r approach. Different impact
parameters are compared using information obtained before the introduction of
technoloq and 5-10 yr after its introduction. This approach requires good baseline
informatbn. In the absence of baseline inforniation. a wirlz il~ld ~t.it/zol,t technology
approach can be used. Impact parameters from sites where the technology was
introduced are compared with parameters collccted from sites where no
technological innovation was introduced. The rocllt~olo~ udoptet. arid rzorltrliopter
approach, in which two groups of farniers are classified :iccording to specified
adoption rules, can be applied in a situation where it is diffic~~lt to find a site that is
homologous to the project site.
This study used a variant of the technology adopter and nonadopter
approach. One dilemma was deciding on the domain of the impact assessment.
Should it only recognize innovations carried out by the Regional Integrated
Agricultural Research Systems (RIARS) in Cagayan Valley Region? Or, sho~lld it
also take into account the contributions of other entities (e.g., seed companies),

whose goals nln counter to the objectives of the RIARS, and of the farmers
themselves, who continuously modify the technologies?
Farmers were classified according to the degree of technology adoption,
using a single criterion (croppin8 intensity). This classification of the degree of
adoption allowed technological innovations from various sources to be considered.
Biggs (1989) called this a nlulti'~le sorcrce of innovatio~z r?zodel that describes
agricultural research and diffusion processes in the context of the historical,
political, economic, agroclimatic, and institutional setting in which technological
changes take place.
The sample consisted of 105 farmers randomly selected from two villages and
monitored for crop years 1989-91. Three farmers dropped out of the project;
therefore, 102 farmers were used in the analysis. The farmers were classified
according to degree of adoption using total cropping intensity of the farm (CI): low
adopter < 1.3, medium adopter 1.3-1.7, and high adopter > 1.7.
The observed cropping intensities ranged from a low intensity of 0.75 (some
parts of the farm were not cultivated for at least one agricultural cycle) to a high
intensity of 3.00. A cut-off C1 of < 1.30 (based on 2-yr averages) defined low
technology adopters. The cut-off C1 was determined from a frequency distribution
and a subjective judgment of the amount of land allocated by farmers to the new
technologies (cropping patterns). A 30% increase in cropping intensity after about
5 yr of exposure to the newr technologies is considered low. A 70% increase in C1 is
considered high given the climatic situations that prevailed during the study period
(i.e., late onset of rainfall and waterlogging during planting season).
It was assumed that adoption of the rice - rice or mungbean - rice cropping
patterns, in addition to the intensive maize-based cropping systems of their upland
areas, was a sufficient condition to classify farmers as technology adopters The
intuitive appeal of this approach was based on the argument that farmers who were
not totally convinced of the qualities of the introduced technologies would not
allocate all of their land holdings. The other extremes were that a fully convinced
farmer would allocate all his kind; whereas, an unconvinced farmer would continue
to follow traditional technology. A farmer's perception of the soilndness of a
technoloby can, therefore, be nieasured to a large extent by the amount of land
allocated to the new technoloky.
Other component technologies that are included with the introduced patterns
were not included as criteria. This was not meant to disregard their critical
contribution to the tot;il perfor~nance of the technology. In fact, their noninclusion
was meant to avoid the effects of other exogenous variables on the question of
adoption. For example, if a farmer failed to apply the correct level of fertilizer, this
does not imply that the farmer was not convinced of its expected benefits, but
perhaps was unable to afford the input cost. Similarly, a fariner might not apply the
optimum mix of inputs to a plot if less profit was expected (e.g., in an area that is
likely to be adversely affected by flood or drought). Also, farmers whose established
crop(s) are affected by drought or tlood will not apply their remaining inputs to
minimize profit losses. All of these are rational management decisions that could

not be captured if the criteria for farm groupings was based strictly on component-
technology recommendations.
Study area
The studv area covered two villages in Isabela Province. The province is located in
the northeastern part of the Philippines, a region with high agricultural potential.
This area has a unimodal rainfall pattern with an average annual rainfall of about
2,200 mm. The area is situated along the typhoon belt. It experienced seven
typhoons during crop years 1989-90 and three typhoons the following year. The
region as a whole is usually isolated from the rest of the country for a few weeks
when a strong typhoon hits the area. Prices of agricultural commodities are reduced
when the area becomes isolated. Two land types exist in the study area: the river
floodplains (uplands). lvhich are traditionally cultivated for maizs and upland crops,
and the rainfed lowlands. which are traditionally culti\lated for rice.
An average farming houlehold of six people cultivates about -7 ha, which are
almost equally d~vided between the two land types (Table 1). It is uncommon to find
farming households specializing in the cultivation of either the rairlfed lowlands or
the floodplains. The area is flood-prone during the monsoon and drought-prone
during the dry season. In addition to upland crops and rice, farming households
raise several head of water buffalo and cattle.
Rainfed lowland area
TRADITIONAL AYD INTRODUCED TECHKOLOGIES
The traditional cropping pattern in the rainfed lowlands is fallow - rice. Rice is
transplanted in August-September. The thrust of the now defunct RIARS of the
Department of Agriculture in Cagayan Valley was to establish two crop patterns.
These patterns were designed to take advantage of the traditionally long f,
cl 11 ow
period before rice and the rainfall available during this period. To achieve this
objective. RIARS introduced a short-duration upland crop (rnungbean) and dry
seeded rice (DSR) before transplanted rice (TPR) in the wet season. Either
mungbean or DSR must be established during the onset of rainfall sonletime in rilid-
April. This is followed by TPR in August-September. Table 2 shows the distribution
of the present cropping patterns in the rainfed area. It suggests that the f~llow - rice
pattern still predominates. The introduced patterns (mungbean - TPK and DSR -
TPR) command a smaller share of the area. The sudden decline in area of these two
patterns in crop year 1990-91 can be attributed to the extended drought that
affected the whole region. This indicates the instability of the introcluced
technolosy.
/
On average, component technologies as implemented by the farmers were
within the recommendation domain of RIARS (Table 3). In some cases, input levels
exceeded the recomnlendations. The high seeding rate, particularly of mungbean, is

largely due to reseeding after early crop failure caused by flashfloods. Present yield
levels are below those achieved after the preproduction phase of RIARS (RIARS
19SS).
Floodplains
The traditional cropping pattern in the floodplains is maize - maize (Table 2). The
first maize crop is established at the onset of the rains (April-May) and is followed
by a second crop of maize in November-December. There are other minor but more
intensive cropping patterns practiced by farmers using different cornbinations of
upland crops. These are established on small patches of land for home consumption
and the local market.
The research focus of KIARS in this land type was on component
technologies, with particular emphasis on the use of high-yielding varieties (HYVs)
to replace traditional varieties. The present component technologies adopted by
farmers far exceed the original recornmendations (Table 4). RIARS advocated high-
yielding open-pollinated varieties of maize; however, private seed companies, with
better logistics and the help of government extension personnel, promoted the use
of hybrid seeds. 'The latter technology prevailed in this land type. Average yields,
hoivever, remained low largely due to climatic vagaries.
The establishment of maize in the upland areas (floodplains) coincided with
the establishlnent of the introduced ~nungbean or DSR in the lowland in April-May
and created cornfietition for farm resources (time, labor, and capital inputs). The
maize crop in the upland area took precedence over crops in the lowland area.
Farmers unanimously agreed that establishment of their maize crop was their first
priority. Maize not only com~nands a better price and higher yield. but there is less
risk of crop failure. Mungbean in the lowland was susceptible to flashfloods,
whereas, DSR was vulnerable to water stress. Resource-strapped farmers were
unanimous that, if time permitted, any residual inputs would be devoted to the
cultivation of their 1owl;tnds.
Lately, farmers have started to buy certified hybrid maize seeds in one
season, and then use selected F2 seeds for the next crop season. This was an
apparent reaction to the high cost of hybrid seeds. Seed companies have now started
to sell high-yielding open-pollinated maize seed.
Changes in income
RESULTS AND DISCUSSION
Table 5 shows the diversity of income sources of the farming households in the study
area. One revealing observation was the low earnings of low technology adopters
relative to medium ancl high technology adopters. Income from th,o three major

crops (rice, maize, and mungbean) appeared unstable over two periods in all three
categories of adopters. The FSR-pushed mungbean technology in the lowlands
along with other crops (mostly vegetables in the upland area) accounted for the
difference in income betiveen the degrees of adoption in year one. Maize dominated
in year two.
The most important nonfarm income was wage earnings from nonfarm and
off-farm labor re ardless of the extent of adoption. Total household income showed
no significant dif f erences anlong the three categories of adopters although medium
and high adopters appeared better off. The findings, in general, indicated that low
farm earnings could be compensated through other means.
Changes in expenditures
Table 6 shows the comparison of cash expenditures of the farms. All farm groups
apply relatively the same amounts of inputs. Fertilizer usage in crop years 1989-90
reflects the only significant difference among the major items considered. Farmers
in the area were applying inputs at rates almost equal to, if not above, the
recommended level.
Table 7 shows nonfood household expenditures according to degrees of
adoption. Except for loan repayment and educational expenses in crop year 1990-
1991, all other major items of expenditure were not significantly different.
Food expenditures reflect tastes and preferences and decision-making of the
family. Table 8 shows expenditures on major food items. Other than expenditures on
bean, no significant differences among the three categories of adopters were
observed. The findings suggest that all households turn equally to the market for
additional food.
Changes in nutrient intake
A food consumption survey, based on 24-h recall of food items consumed by the
family, was conducted for eight periods. The periods represented different farming
activities determined at the village level. The intention ivas to capture seasonal
variations in food intake. Nutrient adequacy was determined by taking the ratio of
actual intake to the recommended daily allowance (RDA). The use of aggregate
household consumption assumed that food and nutrient intake were equally shared
among household members.
Table 9 shows nutrient adequacy in all three categories of adopters over
time. All groups exhibited inadequate energy intake. Protein intake was adequate
only during the first two periods. Similarly, diet rating (a measure of the average
intake of macronutrients and micronutrients) was inadequate in all periods.

lnadequacy of nutrient intake was prevalent whether the survey was conducted
during lean or surplus periods. One surprising finding was that medium adopters
tended to be better nourished than other groups of farmers. On average, energy
intake of a medium adopter was above the 80% critical level. The other farm
groups, low adopters in particular, fell short of the critical level. Protein intake,
however, was above the 70% critical level for all groups.
The nutritional status of the most vulnerable group of the household
(children less than 6 yr of age) was used as a proxy for the general nutritional status
of the household. The ratiogale is that in the short run, preschoolers are sensitive to
even slight changes in food and nutrient intake. Table 10 shows the proportion of
undernourishment in the three categories of adopters over time using the weightfor-age
standard reference (relative to average weight of well-nourished
population). The prevalence of undernutrition followed the trend in nutrient
adequacy measure, i.e., the prevalence of undernourishment was relatively high
during periods where adequacy in energy and protein intake were low in all tliree
categor~es of adopters. All farm groups exhibited a high prevalence of moderate
undernourishment, i.e., weights of preschoolers were 60-75% below the normal
weight-for-age reference. The difference in undernourishment among the three
categories of adopters was varied in all periods.
Determinants of impact
This analysis may not be sufficient to make a categorical statement on the
contributions of the introduced technologies. A Cobb-Douglas model (log-linear
model) wasgestirnated simultaneously using the two-stage least square method
(2SLS). The endogenous variables were productivity of rice, maize, and mungbean
(kg/ha), total household income (P/household), and per capita nutrient intake. The
estimated productivity of rice, maize, and mungbean enters the right hand side of
ihe income model along with other exogenous variables. These exogenous variables,
in turn, enter the models on nutrient intake as predicted income (Table 11).
Impact on producti\.ity
The farrlling households in the study area were engaged in mixed-crop farming (rice,
mungbean, maize, arld some vegetable crops). An aggregate production function
liornogenized by the prevailing market prices in the area m y be more appropriate
to capture the overall productivity of the farm; however, an aggregate production
function would hide the contribution of the individual commodities.
Maize productivity
The productivity of maize (kg/ha) can be explained by the rate of fertilizer
application, seeds used, pesticide, preharvest labor, power-tiller rental for land
preparation, farmer characteristics, and a dummy variable for year.

The explanatory Lwiable, nitrogen (N), explained a large portion of the
productivity in maize. A 1% increase in N application, while other factors being held
constant, is expected to increase yield by 1.4%.
The value of seeds used, a proxy for the amount and quality of seed used,
made a positive significant contribution to maize yield. The result indicates that
farmers Lvere correct to use hybrid maize (although expensive) over their traditional
varieties or the open-pollinated maize, Lvhich ~vas being pushed by researchers, but
was not readily available to the farmers.
Other sources of productivity were preharvest labor and the use of
powertillers for land preparation. Farmers Lvere obsencd to do thorough land
preparation and trying to maintain ~i.eed-free crops. Ltely, farmers have been
observed substituting animal draft power for small and large power tillers,
particularly in maize-based areas. The rental cost may not be the prime
consideration. Timeliness in land preparation may be the most critical factor.
The nonsignificant contribution of pesticides to maize >ield ma!/ indicate that
farmers Lvere spraying their maize crop even if it was not necessary. It was common
for farmers in this-area to establish an agreement Lirith local grain traders who
provide them with credit on the condition that the farmers sell a11 of their produce
to the trader.
Age of farmer, used as a prosy for long-term farming esperience, had a
significant positi~~e impact on maize yield. Years of schooling, a proxy for stock of
knowledge for effective implementation of the technoloby, did not significantly
increase maize productivity. The intercept shifter ()fear dummy variable) suggested
that maize yields, in general, were low during the first !,ear of the monitoring period,
but the difference was not statistically significant.
Rice product i ~itj
The yield of rice (&/ha) was regressed with rate of fertilizer application, seeds
used, pesticide, prehanest Iabor, power-tiller rental for land preparation, farmer
characteristics, and a year d~lniriiy variable.
The results indicated that N fertilizer, seed value (prosy for amount and
quality), and pesticide cost had significant positive effects on rice Ilield. Preharvest
labor and power-tiller rental made no significant contribution. However, farmer
characteristics represented by age and years of schooling, were statistically
significant.

Mungbean productivity
The productivity of mungbean came mostly from pesticide application. Farmers
were fully aware of the potential damage if insect pests were not controlled during
the flowering stage of mungbean. Seeds did not significantly affect mungbean yield.
Farmers had totally shifted to the new mungbean variety (MG-9) introduced by
RIARS. Similarly, inputs, labor, and power tiller did not significantly affect
mungbean yield. The intercept shifter (year dummy variable) indicated that
mungbean yield in crop year 1989-90 was significantly higher than in the succeeding
year.
Impact on total household income
The endogenous variable, total household income, represented the total earnings of
the farm household from different sources. The explanatory variable, nonfarm
income, was an arithmetic component of the endogenous variable in question;
therefore, it was introduced in the model as a share of total income. Proxy variables,
such as the number of hours spent on nonfarm economic activities, may be a more
appropriate estimator. Different economic activities, however, yielded different
levels of earnings. Total household income was explained by the technology
variables (productivity in maize, rice, and mungbean, cropping intensities in lowland
and upland areas of the farm, total land holdings, household size, and year dummy).
Although productivity in rice and maize had a significant positive impact on total
farm household income, mungbean contributed negatively (although the difference
was not sta~istically significant).
The significant negative effect of lowland cropping intensity compared with
the positive impact of upland cropping intensity, reaffirmed the preference of the
farmers to intensively cultivate their upland areas rather than their lowlands.
Similarly, total land holdings provided a significant positive impact on total
household income.
Household size had a significant positive effect on total income. Larger
families tended to have an edge in generating cash income for the household. As
expected, the value of landlord shares decreased total income. This particular
variable represents tenurial status of the land, or land rent in general. Most farmers
cultivated several parcels of land with different rental arrangements. Weather
affected overall crop production during the first year of the study; therefore, total
farm household income was affected that year (the significant negative sign for the
year dummy variable).
Impact on adequacy of nutrient intake
Adequacy in nutrient intake only considers the macronutrients (energy and protein).
These macronutrients are still the most limiting in the diet of small farming
households. The endogenous variables were calculated as a per capita intake instead

of the ratio of actual intake and reconlmended daily allowance (RDA) to ensure
consistency in the use of the specified econometric model. Furthermore, the average
adequacy in nutrients has yet to be satisfied.
Per capita energy intake (calories) was determined by total household
income, age and years of schooling of the mother, family size, and share of food
expenditure of the total farm household budget. All exogenous variables had a
significant positive impact on per capita energy intake. Characteristics of the
mothers such as educational attainment, a proxy variable for a\i.areness of good diet
preparation, and age, representing long-term experience on the part of the mother,
both positively contributed to increases in energy intake. Per capita protein intake
(grams) was also explained by these \,ariables. Total household income,
expenditures on food. and characteristics of mothers had significant positi\.e impact
on protein intake. The positi\.r effect of household size on energy and protein intake
may indicate the capacity of the household to acquire enoush food.
CONCLUSIOS
If the explicit goal of FSR i~ to de\pelop a crop-nlis that incre~~ses producti\,ity of
land ivhich can he translated into higher incomes. then its implicit goal is to impro\,e
the total welfare of the fartning households. This study assessed the i~npact of FSR
on this basis.
The study indicated that there \vas a rnised imp;ict on the different \\.elfare
measures of the fdrming households. It is probable that increases in rlourishnient
\rere positiirely affected by the introduced technologies. The nutritional inipact of
FSR technologies could be directl!! through an increase in household food supply as
a result of an Increase in total production (represented by value of prod~rctivity in
the model), or indirectly througli an increase in purchasing power as a result of
increased total ho~15ehold incorne t7rought about by increased productivity. Changes
in food supply, ho\i.e\:er, affect the n~.~tr~tional stat~~s of the household mernbers only
to the extent that food consumption is affected. Altlioi~gh the technologies have a
significant positive effect on per capita nutrient intake, the nutrient adequ;lcv
indices suggest that houseliold intake still falls sliort of recli~ired daily nutrient
intake. It appears, ho\\.ever, that sni;~ll farming households can hetter satisf! their
protein requirement than their energy needs (other sti~dies have made similar
observations). T\vo plausihle esplnnations ;ire offered: the m;li~i diet of Filipinos, is
rice, which has a relatively high protein content; ;lnd Filipitios in gcner~ll. consume
less fat. In the absence of baseline information, one can onl! ~pt~illtlte whe1l:er
there was an increase in nutrient intake or \chetl~er tllat inr;~ke I-enl;iins ; ~t the sL\iTltl
level as that of the preproject period.
As R:lvillon (1990) h;~s pointed out, the nutritional imp:!ct of a~ricultural
changes depends on whetlier or not the vulnerable groups u'ithin the ho~~sehold
benefit from them. The prevalence of ~lnderno~lrishmeut among the preschoolers in
all farm categories is noticeable. The nutritional st;ltus of the prrschoolers tends to
follow seasonal fluctuations in the indices of nutrient adequacy. One limitation of
the study is its inability to link direc.tly (at least within the specified econometric

model) the nutritional status of the preschoolers with the technology variables in the
model because the endogenous variable is qualitative in nature; and there are many
farmers within the sample who do not have preschoolers. Nevertheless, the authors
believe that total income or food nutrient intake per se are necessary, but not
sufficient conditions to alleviate undernourishn~ent. There are other exogenous
factors that are as important (e.g., health and sanitation practices) but were not
captured in the study.
Income gains of the household still largely depend on the size of its farm
holdings. The contribution of crop intensification technology in the lowland (as
represented by mungbean - rice and the rice - rice cropping patterns) to inflows of
household cash is in doubt. As long as these technologies remain unstable, maize
crop in the upland area is expected to be the main source of income.
On the production side, the inputs farmers used were equal to and
sometimes above the recommended level. Productivity, however, remains low
relative to the expectations of FSR researchers at the end of technology generation.
One ready explanation was the harsh weather conditions that prevailed during the
course of the impact-assessment study. Although the technology seems unstable, its
actual contribution is already sizable. The evidence indicates that farm productivity
could be increased by adopting introduced technologies. Considering the magnitude
of the contribution of the technology variables, the results further indicate that
improvement on the introduced technology (i.e., improved stability) could further
enhance farm productivity.
Because of limitations of available information, the assessment of the impact
of FSR technologies on other welfare measures (e.g., education and wealth
accumulation) was not attempted. Asset accumulation and education are long-term
objectives of the household. To surmise that a link could be properly established
between technology adoption (FSR) using cross-sectional data would produce
misleading inferences (particularly because the introduced technologies were
relatively young and the sample size was small). Time-series data with sufficient
information on ho~~sehold asset possession before adoption wo~~ld provide a better
understanding of the relationships of these welfare measures to the technologies in
question. Nevertheless, the results have provided insights on the contribution of
FSR (or any agricultural technology) to some welfare measures which are given high
priority by households.
REFERENCES CITED
Biggs S D (1989) A nlultiple source of innovation model of agricultural research and
technology prumotion. Network Paper 6. Agricultural Administration Unit,
Overseas Development Institute, Lorrdon.
Gonzaga R G, Gordoncillo N P, Ranaweera N F C, Barba C V C (1990) Assessing
nutritional consequences of FSR projects. Paper presented at the First Asian

Farming Systems Research and Extension Symposium, 19-22 Nov 1990,
Asian Institute of Technology, Bangkok, Thailand.
Jodha N S (1994) Discussant's Note on Commercialization in Agriculture.
Ranaweera N F C (1988) The need to assess impact of farming systems research
(FSR) within the Asian context: an overview. Paper presented at the
Monitoring Tour Cum Workshop on Impact of Farming Systems Research in
Selected Asian Countries, 25-30 Ap 1988, Amigo Terrace Hotel, lloilo City,
Philippines.
Ravallion M (1990) Income effect of undernutrition. Econ. Dev. Cultural Change
38(3):489-5 15.
RIARS--Regional Integrated Agricultural Research Systems (1988) Barangay pilot
productitin program of improved cropping system. Paper presented at the
CVIARS/PCARRD Coordinated Research and Development Review, 8-10
Jun 1988, Isabela State University, Isabela, Philippines.
Zandstra H G, Price E C Jr., Litsinger J A, Morris R A (1981) A methodology for
on farm cropping systems research. International Rice Research Institute,
P.O. Box 933, Manila, Philippines.

Table 1. Basic characteristics of farm households, Isabela Province,
Philippines (1989-91).
Degree of Adoption
Low Medium High
Characteristics of farmers (1989)
Age 37 40 38
Educational attainment 6 6 6
Farm Size (ha)
Lowland
Upland
Total
Table 2. Percentage distribution of cropping patterns in each crop year.
Lowland
Fallow - Rice
Mungbean - Rice
Rice - Rice
Other monocrop patterns
Total
Upland
Corn - Corn
Mungbean - Corn
Monocrop pattern:
Corn
Mungbean
Other crops
Other 2-crop patterns
Other 3-crop patterns
Total

Table 3. Input levels and productivity of crops under rainfed lowland conditions.
Material inputs
N (kglha)
P (kglha)
Insecticide cost (Plha)
Herbicide cost (Plha)
Seed (kglha)
Labor Input: (hlha)
Land preparation
Power cost (Plha)
Crop establishment
Weed control
Other crop care
Yield (kglha)
Crop Mungbean 1st season 2nd season
year before rice rice rice

Table 4. Input levels and productivity of upland crops under floodplain conditions.
Crop 1st season 2nd season 2nd season
year maize maize mungbean
Material inputs
N (kglha) 1989- 1990 80 75 22
1990-1991 95 90 2
P (kglha) 1989-1990 22 2 1 22
1990-1991 2 1 22 -
K (kglha)
Insecticide cost (Plha) 1989-1 990 185 221 45 1
1990- 199 1 216 242 3 13
Seed (kglha) 1989-1990 17 17 19
1990-1991 18 16 14
Labor Input: (hlha)
Land preparation 1989- 1990 72 100 89
1990-1991 74 5 9 74
Power cost (Plha) 1989- 1990 195 97 39
1990-1991 242 220 154
Crop establishment 1989- 1990 42 43 34
1990-1991 38 3 8 3 5
Weed control 1989- 1990 46 90 65
1990-1991 7 7 100 7 1
Other crop care 1989- 1990 50 50 3 1
1990-1991 5 6 52 22
Yield (kglha) 1989-1990 2,313 2,655 435
1990- 1991 2,709 3,503 3 85

Table 5. Comparison of annual household income (P) across degrees of adoption.
Farm income
Rice
Maize
Mungbean
Other products
Subtotal
Household Income
Wages
Remittances
Loan proceeds
Others
Subtotal
Total
P P -
Degree of adoption
Year Low Medium High
Note: Means followed by the same letter or its absence are not significailtly different.

Table 6. Comparison of annual farm expenses (P) across degrees of
adoption.
Labor wages
Fertilizer
Pesticide
Seed
Implements
Others
Total
Degree of adoption
Year Low Medium High
Note: Means followed by the same letter or its absence are not significantly
different.

Table 7. Comparison of annual nonfood household expenses (P) across degrees of
adoption.
Loan repayment
Durables
Other household items
Rentals
Repairs
Clothing
Education
Health
Others
Total
Degree of adoption
Year Low Medium High
Note: Means followed by the same letter or its absence are not significantly different.

Table 8. Comparison of annual food expenditure (P) across degrees of adoption.
Rice
Other cereal
Root crops
Sugar
Beans
Vegetables
Fruit
Meat
Fish
Dairy products
Fats and oil
Other food items
Total
Degree of adoption
Year Low Medium High
Note: Means followed by the same letter or its absence are not significantly
different.

Table 9. Comparison of percentage per capita nutrient adequacy and dietary
rating across degrees of adoption.
P P
Degree of adoption
Survey
period Nutrient Low Medium High
Sep 1989
Oct 1989
Jan 1990
Mar 1990
May 1990
Jul 1990
Oct 1990
Aug 1991
Average
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Energy
Protein
Diet rating
Note: Means followed by the same letter or its absence are not significantly
different.

able 10. Percentage distribution of nutritional status of children using weight-for-age
across degrees of adoption.
-
Undernourished
Survey Degree of Over-
Period adoption Normal weight Mild Moderate Severe
Sep 1989 LAW 26 13 47 7 7
Medium 23 9 45 23 0
High 23 6 36 32 3
Oct 1989 Low 3 2 13 35 10 10
Medium 24 2 45 22 7
High 13 13 44 26 4
Jan 1990 Low 3 2 33 57 4 4
Medium 18 8 47 22 5
High 26 4 3 7 33 0
Mar 1990 Low 27 10 50 10 3
Medium 19 2 46 26 7
High 33 4 33 26 4
May 1990 Low 33 3 3 3 3 28 3
Medium 16 0 45 3 7 2
High 20 0 38 38 4
Jul 1990 Low 27 7 38 2 1 7
Medium 24 3 34 39 0
High 25 0 5 8 13 4
Oct 1990 Low 28 12 44 16 0
Medium 18 9 46 24 3
High 3 3 8 38 2 1 0

Table 11. Log-linear models of impact determinate estimated using two-stage least square
method (2SLS).
A. Dependent Variable: Maize yield (kglha)
Independent variables Coefficients
Intercept
Nitrogen fertilizer (kg Nlha)
Seed cost (Plha)
Pesticide cost (PI ha)
Preharvest labor (hlha)
Power rental (Plha)
Land rental (Plha)
Age of farmer (years)
Schooling years of farmer
Year dummy (1989-1990 = 1)
R2
B. Dependent variable: Rice yield (kglha)
Independent variables Coefficients
Intercept
Nitrogen fertilizer (kg Nlha)
Seed cost (Plha)
Pesticide cost (Plha)
Preharvest labor (ldha)
Power rental (Plha)
Land rental (Plha)
Age of farmer (years)
Schooling years of farmer
Year duinmy (1989-1990 = 1)
R2
C. Dependent variable: Mungbean yield (kglha)
Independent variables Coefficients
Intercept
Seed cost (Plha)
Pesticide cost (Plha)
Preharvest labor (hlha)
Land rental (Plha)
Age of farmer (years)
Schooling years of farmer
Year dummy (1989-1990 = 1)
Note: *, **, and *** significant at 10%, 5%, and 1 %, respectively
- 150 -
Standard error
Standard error
Standard error

,
!
Table 11, continued.
D. Dependent variable: total household income (log)
Independent variables Coefficients
Intercept
A. Predicted maize yield
B. Predicted rice yield
C. Predicted mungbean yield
Land rental (Plha)
Ratio of ilonfarm income to total income
Farm size (ha)
Lowland cropping intensity index
Upland cropping intensity index
Household size (No.)
Year dummy (1989-1990 = 1)
E. Dependent variable: per capita protein intake
Independent variables Coefficients
Intercept
D. Predicted total income
Ratio of nonfarm income to total income
Age of mother' (years)
Schooling years of mother
Household size (No.)
Year dummy (1989-1990 = 1)
F. Dependent variable: total household income (log)
Independent variables
Intercept
D. Predicted total income
Ratio food expenses to total expenses
Age of mother (years)
Schooling years of mother
Household size (No.)
Year dummy (1989-1990 = 1)
Coefficients
Note: *, **, and *** significant at 10%, 5%, and l%, respectively.
Standard error
Standard error
Standard error

INSTITUTIONALIZING THE FARILIIIVG SYSTEhlS RESEARCH APPROACH
IN INDOCHINA
A. hl. iIlandac1
Farming systems research (FSR) is a coordinated and integrated
effort to develop tschnolop that will enable farmers to increase
production. FSR addresses itself to each farm enterprise and to the
interrelationships among them and between the farm and its
environment. The research uses information about the various
production and consumption systems, the animal production system,
the cropping system, and the secondary production activities that add
value to the primary product, to identify ways to increase the
efficiency with which the farm uses its resources. The research is
carried out by a coordinated group of scientists from various
disciplines:
At least si~ distinct research and implementation phases
characterize the FSR methodology: site selection and description;
economic and biological component studies; design and testing of the
farming systems; multilocation testing; implementation of pilot
production programs; and full production programs. The broad
objective of this paper is to describe farming systems research in
Indochina (Cambodia, Lao PDR, and Vietnam).
Basic data for the Indochinese countries are given in Table 1. Cambodia has an area
of 181,000 km2 comprising a large central plain, has one of the largest freshwater
lakes in Asia (Lake Tonle Sap), and mountains in the northeast and southwest. The
population is estimated at 7.2 million with an annual growth rate of about 37~. The
average population density is 40 people/km2, with no more than 100 people/km2 in
the more densely populated central plain and Tonle Sap provinces. The majority of
the population is of Khmer origin. with minority ethnic groups making up less than
5%. The birth rate is high (about 6%), however, the infant mortality is also hi~h (about 2%) because of poor sanitation, scarce medical services, and malnutrition.
Lao PDR is a predominantly mountainous country coverifig 236,800 km2.
There are plains bordering the Mekong River near Vientiane ancl Snvannakhet
where most of the lowland rice is grown. The population is about 3.7 mil!ion. Lao
PDR has one of the lowest population density in Asia (16 pe~ple/km2). Average
'~nternational Programs Management Office, International Rice Research Institute,
P.O. Box 933, Manila, Philippines.

population growth is 2.9%. The rural population of Lao PDR is among the poorest
In the world and has an inadequate diet. The population is ethnically diverse, and
some traditional customs may have constrained efforts in the past to provide social
and economic development. The dominant ethnic group, the lowland Lao, resides in
the river valleys and represents about 50% of the population. The remainder is
distributed between the upland areas and mountain Lao, and comprises Khmu,
Lamet, Hmong, Yao, Man, and tribal Tai.
Vietnam covers an area of 329,600 km2. Over 40% of the country is forest
and about 17% is cultivated for crops. Government policy aims to increase the
amount of land under cultivation. The country is divided into two main agricultural
areas: the Red River Delta in the north and the Mekong River Delta in the south.
A mountain range runs along the western boundary with Cambodia and Lao PDR,
and along the northern border with China. The population of Vietnam is
approximately 63 million with an average density of 191 people/km2. Its population
growth rate is about 2.5%. The population is basically rural and is concentrated in
the two rice-growing deltas. In some northern provinces, population densities are
among the highest in the world.
Economies
The Cambodian economy functions at low capacity in nearly all sectors.
Immediately following the fall of the Pol Pot regime in 1979, there was a continued
food shortage and a massive relocation of the population. A UN-sponsored relief
operation costing US$213 million averted famine and assisted in resettlement. The
former Soviet Union provided an additional US$300 million in aid.
The Lao economy is poorly developed. Production is almost entirely agrarian
and aims at self-sufficiency. Modernization of agriculture and the exploitation of
mineral resources are constrained by shortages of skilled labor, domestic capital,
and inadequate internal transportation and communications. Lao PDR is also
landlocked, which is an additional constraint to its growth and development. The
major objectives of its development plan are, first and foremost, self-sufficiency in
food and improved infrastructure (e.g., roads, rural electricity, health, and
education).
Vietnam is predominantly an agricultural economy based on rice production.
Crop cultivation accounts for about three-quarters of the gross value of agricultural
product (GVAP), and roughly two-thirds of this, or almost 50% of total GVAP,
consists of grain production (of which rice accounts for 85%). Food-grain
production amounted to 19 million t in 1988, of which rice was 16.4 million t.
Government policies in Vietnam are in transition. Several measures have
been taken in recent years to liberalize agricultural production. There is a move
toward independent planning by the provinces and the districts to exploit the private
and open-market opportunities. In 1981, Vietnam departed from the collectivized

agricultural production system by introducing the individual-oriented contract
system of production. In its initial form, the contract system restored the farm family
as the basic production unit, while retaining compulsory production and
procurement targets. However, it failed to provide security of tenure and market
freedom. These deficiencies were corrected in April 1988 by Resolution No. 10,
which liberalized all input and output markets and allowed households to maximize
their own output and incomes.
Agricultural production systems
Indochina is an important rice-growing region in Asia. Almost 8 million ha of rice
are harvested annually. Vietnam ranks first in terms of both area (5.66 million ha)
and yield (2.7 t/ha). Lao PDR has 679,269 ha of rice with an average yield of about
2 t/ha. Cambodia, with an estimated yield of 1.1 t/ha from about 1.4 million ha, has
the lowest rice yield in Asia.
Rice dominates agriculture ill Indochina in terms of the number of people
employed in cultivation, the area grown, and volun~e of production. In Cambodia,
95% of the population makes its living from agriculture and 93% of the total
cropped area is planted to rice. In Lao PDR, only 740,000 ha or 3.2% of the total
area is cultivated. Therefore, the land-people ratio is at a low (0.2 ha/person). The
rice area is about 86% of the total cropped area. In the Mekong River Delta in
Vietnam, rice is the predominant crop (97.5%). The northern provinces of Vietnam
have a total rice area of 2,391,000 ha or about 74% of the total area of farm
holdings, which makes rice the most dominant crop.
Rice farming systems
Cambodia has four rice farming systems based on the degree of water control:
rainfed lowland (including supplementary irrigated), upland, deepwater (floating),
and dry season irrigated rice. About 80% of the rice area is grown in the rainfed
lowland (Table 2). An almost equal proportion of floating and dry season irrigated
rice is grown. Rainfed lowland is further classified into high, medium, and low fields,
which are grown with early- (90-120 d), medium- (120-150 d), and late-maturing
(> 150 d) rice varieties (Cambodia-IRRI Project 1990a,b).
The main cropping system in L20 PDR is based on a single wet season rice
crop. Almost 60% of the total rice area is rainfed lowland; about 39% is planted
under upland conditions and contributes about 25% of total rice production (Lao
PDR-IRRI 1990). Traditional photosensitive varieties are widely grown and because
of their long duration (140-180 d), there is little opportunity to grow subsidiary crops
either before or after the rice crop.
Compared with Cambodia and Lao PDR, Vietnam has more developed
infrastructure. In the northern provinces, 84% of the total area is irrigated lowland,
9. '. i
, c,
1

12% shallow rainfed (0-50 cm), and 4% intermediate rainfed (50-100 cm)
(Table 3) (Huke and Huke 1990).
Multiple cropping systems
In Cambodia and Lao PDR, very little area is planted to a second rice crop,
therefore, cropping intensity is very low. It is not known how much of the rainfed
lowland rice area is planted to secondary crops after rice. Under upland conditions,
land is usually left fallow after a single rice crop. However, limited cropping of
mungbean and soybean has been observed in Cambodia (Nesbitt, 1991, pers.
commun. ).
In northern Vietnam the dominant cropping pattern is spring-summer rice. In
the Mekong River Delta, rice is produced during three major cropping seasons:
Dong Xuan (winter-s ring), He Thu (summer-autumn or midseason), and Mua (wet
season; long duration 7 .
Other crops have high potential in Indochina: sugarcane, coconut, sugar
palm, pineapple, banana, orange, and other fruit crops. In addition, niungbean,
sweet potato, soybean, and groundnut are important crops.
FARMING SYSTEMS RESEARCH
Integrated farming traditions are thousands of years old in Indochina, but are not
fully reflected in production or in institutional support to agricultural production.
Increased production of rice and increased productivity of rice-based farming
systems, remain primary goals of the national plans in Cambodia, Lao PDR, and
Vietnam. Crop selection has been guided by national policies and plans that stress
rice production. Consequently, crop diversification has not occurred to any
significant extent. During the past three decades, the development of farming
systems research has mainly occurred in Vietnam, which is the focus of this section.
Achievements
There have been various programs and projects to support development plans and
strategies in farming systems research. In the Red River Delta, where rice is the
dominant crop, short season varieties were introduced to enable farmers to grow a
third crop (e.g., sweet potato, potato, or vegetables). A system of raising livestock
(garden + fish pond + animal house) has been introduced under the household
system. Rural industries and handicrafts have been emphasized for nonagricultural
laborers, but difficulties were encountered because of lack of materials and
marketing.

In the midwest plain, where there are problem soils, zero tillage, raising
soybean between rice, integration of rice and shrimp, raised beds for growing sandal
trees, and raising shrimp in the canals have been studied. In the upland areas, where
environmental degradation is a major problem, coffee trees have been planted
across the slopes and green manure crops or legumes planted between the rows for
the first three years. Different systems of land preparation have been tested for
growing upland rice. Forest and abandoned lands were given to farmers.
Studies in the Mekong River Delta focused on various rice-based farming
systems models. Some of the models (e.g., rice-shrimp in fresh water, rice-shrimp in
saline area, rice-fish in deepwater area, rice-fish integrated with fruit trees and beef
cattle or dairy cattle, and rice-cash crops in floating rice areas) were initially
developed by advanced farmers in the region.
Technology transfer
The transfer of technology was done mainly through demonstration plots.
Researchers worked extensively with farmers to establish pilot farms in different
ecological zones.
Institutions
The general level of interest in farming systems among scientists and planners in
Vietnam is high. FSR in Vietnam is carried out by different agencies such as the
National Institute of Agricultural Sciences (NIAS), the National Institute of
Agricultural Planning and Projections (NIAPP), the National Institute of
Agricultural Economic Research (NAER), the Mekong Delta Farming Systems
Research and Development Centre of the University of Cantho, and various
universities. Vietnam is also an active participant in the regional project Farming
Systems Development in Asia: Crop/Livestock/Fish Integration in Rainfed Areas.
However, there was a feeling that there was fragmentation in the support to
agriculture at the separate research centers. This led to a project proposal for
coordinated farn~ing systems research and evaluation in Vietnam.
Use of resource maps
FARMING APPROACH
General land-use maps have been extensively used in Vietnam for physical
planning. The crops most suited to the given physical conditions (e.g., climate, soil,
and irrigation regime) are chosen with no account of the relative economic value of
various crops.

In Cambodia and Lao PDR, general land-use maps are being developed
based on Landsat MSS data. Details are current1 being incorporated into these
maps to estimate the total and projected areas o ! land under various rice
ecosystems. The Cambodia-IRRI Rice Project has engaged the services of a landuse
specialist to develop a comprehensive set of rice ecosystem maps for
information gathered from 1:50,000 topographic maps, land-use images, and
available aerial photographs. A national rice-ecosystem map (scale 1: 1,000,000) and
a set of more detailed provincial maps (scale 1:250,000) are being prepared.
Site description
Considerable time and effort were spent in conducting baseline surveys in
Indochina. The output of these surveys has been used for farming systems
characterization and as a basis for farming systems zoning at the district level in
Vietnam. In addition, household surveys of farms have been conducted to get more
detailed information to better understand farmer problems and to better plan
agricultural development programs. The method compared the farming systems of
low-performing farms with the systems used by high-performing farms. From the
results, agricultural package outlines were developed as potential intervention
mechanisms to bring about rapid increases in production (Mandac 1990).
Baseline surveys have similarly been completed in three rice ecosystems
(rainfed lowland, deepwater, and irrigated) in Cambodia, and in rainfed and upland
environments in La0 PDR (Lando and Solieng 1991, Schiller et a1 1991).
Long-term cropping pattern and fertility
The objective was to develop sustainable rice-based cropping systems that included
increased production of nonrice crops and incorporation of grazing animals. In
developing these systems, emphasis was placed on ensuring that the workload of the
farm family was not unacceptably increased.
The research was undertaken in the context of the whole farm (including on-
farm or natural water storage and provision of feed for grazing animals). More
specifically, the research involved experiments that addressed low soil fertility, pest-
management strategies, and the introduction of proven appropriate models. An
example of the work done in Cambodia is shown in Table 4.
Component technologies
The components of the farming systems currently undertaken in Indochina are
shown in Table 5. They involve a range of activities, from varietal improvement to
crop combinations.

Varietal irnprovernent. This componerlt seeks to develop consistent high-
yielding rice varieties appropriate to different rice environments. This is being
accomplished by continuing the collection, evaluation, and conservation of rice
varieties and introducing other varieties adaptable to these areas. An important
activity is technology transfer through on-farm trials and field days.
Integrated nuttient r?~urlagcmctlt. The focus of the integrated nutrient
management program is to develop systems of nutrient management in various
agroecosystems using green manure. legume crops, farm yard manure, crop residue,
and inorganic fertilizers. Identification of suitable species, varieties of green manure
and legume crops, and the incorporation of these crop residues are being
investigated. Research is also being conducted on applied fertilizers to gain
maximum benefit from their use.
Iiltegrufcdpcst r?zatlclger?zent. The main objectives of integrated pest
management are to identify and determine the relative importance of the major
insect pests, diseases, nematode, and weed problems affecting rice in Indochina; and
to initiate component research on the more important pest problems.
Ir77proved water ~?t~~n~g(:t?zctlt. The broad objective of improved water
management is to develop methods of water management that make best use of
water resources (as farm inputs and means of land reclamation and improvement)
and increase farm productivity in various rice ecosystenls.
IRRI APPROACH TO COUNTRY PROGRAMS
The rationale for the IRRI country programs in Intlochina is based on the belief that
strong natioxal research and extension programs are fundamental to increased
productivity of rice and rice-based farming systems. The country and regional
programs are designed to respond to the specific needs and problenls of each
country. The type of help that IRK1 e\tends depends on the stage of development of
the research, training, and development programs ill the individulil countries. IRRI
has fornal or inform;~l rel:~tionships in both research and tr:iining with nearly all the
rice-growing countries in the world. Collaborr~tion is usually in research and
training, however, IRRI is occasionallv invited to help plan the development of a
national rice research institute.
CONSTRAINTS TO FARMING SYSI'EMS RESEARCH
The key constraints to farming systems research and development in Inclochina are
lack of trained personnel, lack of research facilities and planning capacity, lack of
effective technology transfer, and generally low level of infrastructure.

Cambodia, Lao PDR, and Vietnam lack trained scientists and technicians in
sufficient numbers to provide an effective research-extension continuum. Cambodia
and Lao PDR are much more seriously affected than Vietnam because they have
very few research workers with college degrees. In addition, extension services in all
three countries are severely understaffed and are nonexistent in some areas. Again,
Vietnam appears to be in a better position than Cambodia and Lao PDR in this
regard.
A major constraint in Cambodia is the absence of a national research center
that will coordinate the activities of the Ministry of Agriculture (although similar to
Lao PDR, work has commenced on a national agricultural research center). At
present, the few research workers in Cambodia are located at three different
centers, none of which has the potential to expand sufficiently beyond its present
area of 8-10 ha. The main constraint here is research direction. Vietnam has a
stronger research and development infrastructure than the other two countries.
There is a particular need for assistance in the development of an effective
system of technology transfer in both Cambodia and Lao PDR. Both countries have
the beginnings of a province-based agricultural service dealing with seed and
fertilizer distribution. However, without an effective research program, extension
services have little improved technology to extend to the farming communities.
Roads are very poor in Cambodia and Lao PDR. This situation results in
transportation difficulties for personnel, equipment, and materials. Close to Phnom
Penh and Vientiane, some improvements are being carried out, but the poor state of
their national economies will preclude substantial improvement in the short term.
Vietnam has a relatively well-established road network, particularly in the south,
and does not have a major problem in this regard except, perhaps, in the uplands
and highlands.
CONCLUSION
The main objective of agricultural development in Indochina is to produce enough
food and to export goods and raw materials. The strategy is to use FSR to support
national plans for agricultural development, rural development, and environmental
protection.
Cropping systems research in Indochina, particularly in Vietnam, has been
going on for many years. In the 1960s, cropping system activities started with
emphasis on the growing of three crops in areas where two crops were previously
grown. In the 1970s, a large breeding effort was initiated on many crops including
rice, maize, soybean, sweet potato, wheat, barley, and sorghum. Many ecological
(soils and climate) and physiological studies were conducted to support these
activities. All these contributed to the development of the technological components
of farming systems in the region. Farming systems research in the 1980s focused on

solutions to problems under the basic conditions of disappearing lowlands and
increasing population pressure.
FSR is carried out by different agencies in Indochina. Apparently, there is a
lack of coordination, and there is a strong need to integrate the activities of these
agencies to strengthen FSR in Indochina.
REFERENCES CITED
Huke R E, Huke E H (1990) Human geography of rice in Southeast Asia.
International Rice Research Institute, Los Bafios, Philippines.
IRRI--International Rice Research Institute, Cambodia-IRRI Project (l990a)
Annual Report for 1989. IRRI, P.O. Box 933, Manila, Philippines.
IRRI--International Rice Research Institute, Cambodia-IRRI Project (1990b)
Inception Report. IRRI, P.O. Box 933, Manila, Philippines.
IRRI--International Rice Research Institute, Indochina Program (1987) Project
document. Phase 2. IRRI, P.O. Box 933, Manila, Philippines.
IRRI--International Rice Research Institute, Lao PDR-IRRI Rice Research and
Tanning Project (1990) Project docun~ent. IRRI, P.O. Box 933, Manila,
Philippines.
IRRI--International Rice Research Institute, Lao PDR -1RRI Rice Research and
Training Project (1991) Progress report, Jan - Jun 1991. IRRI, P.O. Box 933,
Manila, Philippines.
Mandac A M (1990) Farming system report on strengthening the NIAPP. Hanoi,
Vietnam.

Table 1. Basic data on countries in Indochina.
Land area (km') 181,000
Population (million) 7.2
Population density (people/km2) 40
Population growth rate (%) 3 .O
Climate Tropical
Hottest month Mar- Apr
Coldest month January
Wettest illonth Oct (256 mm)
Driest month Jail (8 mm)
Cambodia Lao PDR Vietnam
236,800 329,600
3.7 63 .O
16 19 1
2.9 2.5
Tropical Tropical
April (23-34 OC) June (26-33 'C)
January (14-28 'C) January (13-20 'C)
June (302 mm) August (343 mm)
December (3 mm) January (18 mm)

Table 2. Rice farming systems in Can-tbodia and Lao PDR.
Rice farming system Cambodia Lao PDR
Rice area as percentage of
total cropped area
Rainfed lowland
Early
Medium
Late
Irrigated
Deepwarer
Upland
Total
Average national yield (tlha)
Note: Figures in parentheses are percentages.
Table 3. Rice farming systems in Vietnam (1990).
Water
regime
Irrigated lowlarid
Spring-Summer
Summer- Autumn
Winter-Spring
Nol-thern pro\~ilicesa Mekong River ~ elta~
Area (000 ha) % Area (000 ha) %
Rainfed lowlalid
Shallow (0-50 cm) 2 84 12 300 12
Intermediate (50-100 cm) 95 4 550 23
Deepwater (floating) 300 12
Total rice area -,- 3 391 100 2,400 100
a~ource: Huke and Huke (1990). 'source: Vietnam-UNDP (1991).

Table 4. I,ong-term cropping patlcrns at I'rcy 1'hd;tu Sla~ion, Kampong Spcu I'rovince, Cambodia (Irrigated, 1990).
TI-eatmcnt 'TIiird Crop" Firs1 crop 0
First second Third Plant plant Grain Plant plant Grain
crop crop cl-01' hcight population yield heighl population yield
(cm) (no./rn2) ((/ha) (cm) (no. /m2) (t/ha)
Rice Rice - 0 0 0 67 255 3.2
Rice Mungbean Rice 75 200 1.3 7 7 252 3.2
Rice Mung bean 33 5 8 0.05 7 2 250 3.2
Rice Munghean 0 0 0 75 255 3.2
Rice Mungbean Mungbean 3 5 62 0.03 6 8 202 3.1
Rice Rice Rice 78 220 1.5 66 217 3 .O
'planting date 13 Mar 1990; transplanting date 2 Mar 1990; harvest date 2 Jul 1990.
b~lailtillg date 27 Jul 1990: transplanting dale 2 Aug 1990; harvest date 17 Nov 1990.

Table 5. Component-technology studies in Indochina.
Varietal improvement
Cultivar trials
Germplasm collection/evaluation
Hybridization
Quality analysis
Integrated nutrient nlanageinent
Fertilizer responses (NPK)
Green manure (legume) evaluation
Integrated pest management
Y ield-loss assessment
Iniproved water management
h'lixed farming
Animal and fish
Crop conibinations
Rotations
Intercroppilig combinations
Cambodia Lao PDR Vietnam

IMPACT ASSESSXIENT OF FARhIIKG SYSTEhlS RESEARCH AND
DEF-ELOPRIENT AT THE FARM LEVEL: THE CASE OF KABSAKA
TECHNOLOGY IN ILOILO, PHILIPPINES
V. T. ~illanciol, C. H. ~analol, hl. L. V. I. ~ebulanan',
A. sotornill, and N. F. C. s an awe era^
One of the most successful farming systems projects in the Philippines
has been the KABSAKA project in Iloilo. The KABSAKA technology
introduced the two three crops option from the traditional single crop
practice that framers were involved in. This study attempted to
quantify some of the benefits derived by the farring communities
which adopted the technology. The study concludes that there are no
strict adopters; farmers use only specific components of the
technology particularly the ones beneficial to them. Also, while the
income of adopter farmers is higher than the nonadopters, still the
incomes are inadequate to sustain the development in the countryside.
KABSAU is the acronym for Kabusugan sa Kaumahan, an llonggo phrase
meaning bortnty irz tlze fanlz. The KABSAKA project was initially a rice-based crop
diversification strategy in the lowland rainfed areas that served as a basis for the
development of a cropping systems research methodology. Although the KABSAKA
project may not have initially used the basic elements of farming systems research
(FSR), most of the FSR components were tested within the project at different
stages of its development.
The KABSAKA project had a farming systems perspective and included
adaptive trials and pilot-production programs implemented in 1974-85 in the rainfed
lowland areas of Iloilo. Two or more crops could be grown because of the
introduction of various components of the KABSAKA technology (which includes
ezrly land preparation; use of early maturing varieties; direct seeding of the first rice
crop; use of fertilizer, insecticide and herbicide; short turnaround period; and
planting of upland crops, particularly legumes, in the drier areas where it is not
possible to grow a second crop of rice).
During the last 10 yr, several studies measured the impact of KABSAKA
technoloa in Iloilo (Price 1982, Barlow et a1 1983, Wangwacharachul 1983). These
studies indicated that the KABSAKA technology had increased cropping intensity,
input usage, annual rice production, and farm income.
a arm in^ System and Soil Resources Institute, College of Agriculture, University of
the Philippines Los Bafios, Laguna, Philippines.
2~ocial Sclences Division, International Rice Research Institute, P.O. Box 933,
Manila, Philippines.

Wangwacharachul (1984) examined the macro effects of the KABSAKA
technology and concluded that the income structure h:id changed over a period of 5
yr in favor of nonagricultural households in partially and fully irrigated areas. It had
also improved the overall income of the rural sector. Barlow et a1 (1983) concluded
that the economic impact of the new technologies depended on the resource level of
the farmers. Under rainfed conditions where cash is scarce, low input levels are
generally employed. Price (1982) discovered that the :idoption of KABSAKA
technoloo reduced input use in relation to the recommendetl rate.
The objective ot'tl~is study was to quantify the direct :ind indirect benefits of the
KABSAKA technology to farmers. The first part of the study was conducted in
1957-88; the second part continued until 199 1. 'The first phase of the study focused
on the degree of adoption of the ne\v technology, the impact of the new technology
on overall production and income, the nonqi~antifiat)lc benefits (e.g., education and
nutrition) that co!llti be attributed to rhe technology, and the role of support
institutions in popul:irizjng tlie technology.
The second phase of the study (1989-91) focused on finding several ways to
classify adopters of the new technolop according to the level of adoption and,
consequently, to determine the impact of the technology on farm household income
and expenditures.
The with and ~ifllolit approach was al~plied. 'l'he frarnev~ork proposed by
Ranaweera (1988) was used to measure the impact of the adopted technology. This
was based on the premise that the inlpxct of FSR (at the farming systems level or
the farm household level) can he attributed to the technology that was generated.
The impact of FSR can then be measured as the difference between the adopters
and the nonadopters \s.itli respect to selected in2pnct parameters.
Selection of the study area
The study area, Ajuy, Iloilo Province, \us selected on tlie basis of the extent of the
rainfed area, the extent of the KABSAKA project activity, average yield, tenurial
status of farmers, and average landholding. Except for average yield, farmers in
Ajuy were, more or less, similar to farmers in lloilo in all other aspects. The study
initially covered three barangays or villages (Culasi, Pili, and San Antonio) in the
municipality. Another t\vo barangays (Luca anci Poblacion) were added in the
second phase of the study.

Site description
Iloilo is located in the southeastern region of the Island of Panay. The municipality
of Ajuy is situated in the northeastern part of Iloilo, approximately 87 km from
Iloilo City. Ajuy is composed of 34 barangays, three of which are islets.
The topography of Ajuy is dominated by a mountain range (400 In in height)
in the west that is covered with grasslands, shrubs, and secondary forests.
Agricultural lands are located mostly along the foot of this mountain range and
extend to the relatively flatter area along tlie sea coast. The soil type is generally
sandy loam and clay loam.
About 36% of the total area of the rnuniciprility is considered agricultural
land, 41% of which is under rice-based farming systems. Of this' rice-based farming
area, 90% is rainfed. Other crops in the area are coconut, sugarcane, maize, root
crops, and legumes.
Fishing is a major source of income in the coastal areas. Fish ponds
constitute 6% of the total area. Livestock is raised mainly for home consumption
and as 3 supplenlentary source of income. The site belongs to the Type 111 climate,
which is characterized by two distinct seasons. January-April is the dry period with
an average rainfall of 230 mm/mo, May-December is tlie wet season (WS) with an
average rainfall of 600 mm/mo. The monthly mean temperature is relatively
constant (25.2 OC,in January, 28 'C in May). The monthly mean relative humidity
ranges from abo~lt 75% in April to 84% in October.
Selection of sample farms
Many difficulties were encountered in the selection of san;ples that would represent
adopters and nonadopters of the technology. F;irrners who had established their first
crop using dry seeded rice (DSR) were classified as adopters. The other f~rmers
were considered to be nonadopters. Initially, the selection of adopters of
KABSAKA technology was based on the information provided by the Department
of Agriculture (DA). However, there were discrepancies, especially among farmers
that changed categories year after year. Therefore, the farmers were cl:lssified
according to the cropping system they had adopted over the last 4 years. Sixty
farmers were selected during the first phase of the study. Those who dropped out
during the first year were replaced with another 12 farmers.
Data collection and monitoring
Records on crop production and household transactions were maintained daily from
March 1987 to April 1989. All crop production data were recorded on a plot basis
using n farm activity sheet; whereas, household transaction dates were recorded on a

household basis on an income and expenditure sheet. Farmers were visited weekly
to collect the completed record sheets.
Seasonal surveys of crop production activities were conducted during the WS
of 1989 and the dry season (DS) of 1990. Details of household income and
expenditure were excluded from the survey.
Methods of analysis
Initial analysis was based on three farm-size categories. This did not reveal a
significant difference in mean yield or inconle-expenditure patterns among adopters
and nonadopters (Medialdia and Ranaweera 1988); therefore, further analysis was
done to compare the impact parameters between adopters and nonadopters. The
impact indicators included input use, yield and pattern of household consumption,
income, and expenditure. The partial budget technique was used to compare the
econoniic perfornlance of the t\vo groups.
Cluster ai~alysis was used to classify the adopters of the new technology
according to the level of adoption. Initially, plot-level data rather than farm-level
data were used because farmers may apply different types of technology to plots
with diverse characteristics (e.g., land tenure, Iandscilpe position, and soil texture).
However, farm-level data were subsequently used for cluster analysis.
Demographic characteristics of farmers and other farm-related inforrnation
were also recorded along with farm-level data. Variables related to the different
components of the KABSAKA technology were tabulated on a hectare basis or as a
percentage of the area where the technology was used. For ex:imple, the percentage
of the area planted using DSR was used to denote the extent to which the farmer
adopted the recommended crop establishment methods. Likewise, the percentage of
the area grown before the cut off date of the first crop and the percentage of the
area with a turnaround period of less than 16 d were used to denote the cut off date
for sowing and the turnaround period, respectively. Inputs (fertilizer, insecticide,
and herbicide) ancl yield were tabulated on a hectare basis. The VARCLUS
procedure was used to group the variables for cluster analysis. About 106 variables
were considered, but only 35 variables were used in the analysis (Table 1).
An attempt was made to combine the b;isic practices related to a conlponent
with f~rm-level characteristics, and to use these as the classifying vari~~bles for
cluster analysis. For example, for fertilizer usage as a cor-nponent technology, the
variables considered were the number of applicr~tions, the level of NPK in each
application, and the value of inputs used. Other components of the technology that
were tested were crop establishment, weed control, and turnaround period. These
components were tested on the premise that these f~rnlers could be classified
according to the level of technology adoption.

Cluster analysis \vas done using the CLUSTER procedure (Ward's Method)
of SAS. The value was used to determine whether t\tro clusters were dissimilar.
Two clusters with R2 values of more than 0.75 \\..ere considered to be one cluster.
An R2 value of 0.75 may either denote certain similarities or dissimilarities among
clusters.
The CANDISC procedure was used to derive canonical variables that
summarized between-class variations. After the clusters were identified, each cluster
was described according to the following parameters: plot and farm-level
characteristics; level of adoption of the KABSAKA technology; productivity;
profitability; household income; and expenditure patterns. The differences among
these parameters reflected the impact of the variations in technology adoption.
ADOPTERS AND SONADOPTERS
The first part of the study viewed the dichotomous aspect of technology adoption.
Adopters used dry seeded rice (DSR) for the first rice crop; nonadopters did not.
The researchers intentionally avoided the terms "high adopters" and "low adopters"
to avoid being biased in relation to the technology promoted by the FSR project. It
should be mentioned that FSR promotes experimentation and farmers should not
be penalized for modifying the technology introduced by the project.
Changes in farm practices
A comparative study of the adopters and nonadopters showed significant differences
with regard to farm practices associated with the KABSAKA technology. Adopters
plowed and harrowed their fields three times. The nonadopters plowed only once. In
1987-88, adopters planted 50% of their farm area to DSR and the balance to wet
seeded rice (WSR) and transplanted rice (TPR). The date of crop establishment for
adopters coincided with the date used by the non:idopters, who established their
crop after the third week of June 1987. Although the land was prepared and
supposedly planted to DSR, the rainfall during June prompted the adopters to use
WSR in certain portions of their farms. The farm area of adopters that was planted
to DSR increased to about 88% in 1988-89 and was established earlier (before the
third week of June) than the farm area of nonadopters. This was also true in
1989-90.
The seeding rate did not vary much, but adopters were more inclined to
provide some allowances during the first crop. Farmers had to maintain higher
seeding rates than recommended to provide an allowance for damage caused by
golden snaiis.
The turn-around period during 1957-88 was longer in the case of
nonadopters (only 38% of the area was planted within the recommended period of
15 d). The adopters had 66% of the area planted within 2 wk after harvest of the

first crop. In 1989-90, the adopters prepared their lands earlier (92% of the rice area
was planted before the prescribed turnaround period of 15 d). The drought that
occurred in the previous !!ear prompted the farmers to plant earlier.
The second crop of rice was established primarily using WSR (81% of the
total area cultivated in 1987-88, and 96% in 1988-89 and 1989-90). Replanting was
more common among nonadopters. About 13% of their land was replanted during
the first crop in 1987-88; about 12% in 1988-89. Golden snails caused more damage
during the second crop. Therefore, 27% of the farm areas of nonadopters had to be
replanted in 1987-88 and 18% in 1988-89.
The use of herbicide was considered an important component of the
KARSAKA technology, particularly for the DSR crop. Adopters applied an average
of 1.0 liters/lia before the establishment of the first crop in 1987-88 compared \vith
only 0.5 liters/ha for nonadopters. This rate was reduced to 0.7 liters/ha in 1988-89.
For preemergence application, ado ters used 0.4 liters/ha of herbicide; whereas,
nonadopters applied only 0.2 litersfha during the first crop in 1987-88. Adopters
also used postemergence herbicide at the rate of 0.5 liters/ha during the first crop in
1987-88 and 0.9 liters/ha in 1988-89. The cost of herbicide application was as high as
P267 during the first crop of 1987-88. Despite the use of herbicide, manual weeding
had to be done. Atfopters devoted relatively more time to weeding than
nonadopters during their first rice crop.
All farnlers used limited amounts of insecticide, ~vhicli indicated that insect
pests were not a serious problem. However, in 1988-89, the nonadopters had to use
1.2 kg ai/ha of insecticide because of a severe pest infestation. During that crop
year, the infestation affected all crops except the DSR crops, which had been
planted 2 wk earlier. The insect problem also affected the newly established WSR
crops. The application of insecticide during the second rice crop did not vary
between adopters and nonadopters.
All farmers used less fertilizer than the recomn~ended level of 60-30-30.
Commonly used fertilizers were urea and aninionium sulfate. The fertilizer costs
were as high as P578 in 1987-88 and P764 in 1988-89 for the first crop of
nonadopters.
Average yield and profitability
The yields obtained by 60 farmers before and after the introduction of KABSAKA
were compared. The fidrmers were asked to recall production data 5 yr before the
KABSAKA project was initiated. Yield increased as a result of the adoption of
KABSAKA technology. However, there seemed to be no difference between
adopters and nonadopters. The yield of adopters was even lower than nonadopters,
except in 1989-90 (Table 2). This raises the Issue of the validit of the categorization
of adopters based oo cropping systems (i.e., DSR versus WSR~ when dealing with a
package of technology like KABSAKA.

A comparison of costs and returns on a per hectare basis for crop years
1987-88 and 1988-89 showed that despite the h~gh production cost incurred by
nonadopters, the adopters had lower net benefits compared to the nonadopters
because of lower production (Table 3). However, in 1989-90, the adopters gained a
little more than the nonadopters, but the difference was not significant.
Farm household income and expenditure
Household income and expenditures can be classified according to the source of
income and nature of expenses. Sources of income are classified as those derived
from farm and nonfarm sources. Expenditures are classified accordin to farm and
nonfarm expenditures. Farm income includes income from the sale o k rice, livestock,
and roduce from the home garden. Nonfarrn income includes income derived from
P
non arm activities and remittances from children. Farm expenditures are related to
expenses in crop and animal production. Nonfarm expenditures include those
related to food, basic household items, health, education, and other social
obligations.
There was a marked difference in the monthljl incomes of adopters and
nonadopters. Nonadopters had a higher monthly farm income in 7 mo within a
period of 11 mo (May 1987-Mar 1988). A higher farm income was observed among
the nonadopters in October because of an increase in rice sales. A similar trend was
observed in 198889 when the nonadopters had higher farm income in 6 mo within a
period of 11 mo (Jun 1988-Apr 1989).
A comparison of the cash and noncash incomes of adopters and nonadopters
showed that adopters had a substantial amount of noncash income particularly in
the months of June, July, and November. Noncash income, however, was not very
substantial during the preceding year. Total annual cash income was similar for
adopters and nonadopters. However, the pattern of monthly cash inflow varied.
Adopters had a relatively stable monthly cash inflow from August 1987 to February
1988 (Table 3).
After September 1987, cash inflow was mainly derived from the sale of rice.
For nonadopters, rice sales contributed to household income from October 1987 to
May 1988. During a period of 12 1110, income from the sale of rice contributed 38%
to the household income of adopters and 3770 to the household income of
nonadopters.
In 1988-89, the total cash inflows were almost the same as in the previous
year. A peak occurred in December 1988 for both adopters and nonadopters.
Among the nonadopters, rice sales contributed about 50% to the household income
in October. Within a period of 11 mo, rice sales contributed about 24% to the
household income of adopters and 37% to the income of nonadopters.

Nonfarm expenses constituted the bulk of household expenditures,
particularly during October and January, for both adopters and nonadopters in
1987-88. The same pattern was observed in 1988-89, but expenditures were higher
The adopters had a substantial cash outflo\v from July to December 1987.
The cash outflow during the 12-mo period was P1,070 more than the cash inflow.
The cash inflow among the nonadopters covered their cash outflow and provided a
net cash flow of P1,268. The noncash outflow was significant among the nonadopters
from October 1987 to April 1988. However, this trend was not observed in 1988-89.
Except in December, cash and noncash expenses were evenly distributed throughout
the year.
Farm household asset accumulation
The accumulation of assets was given special emphasis in the crop production survey
of 1989-90. From April to September 1989, there were only 12 farmers who acquired
farm and household assets, most of which were household items such as gas stoves,
clothing, blankets, and kitchenwares. One farmer bought a hand tractor engine, and
two farmers had their houses renovated. During this period, adopters acquired
assets worth P1,571; nonadopters spent about P523 on assets. Household assets
were generally purchased with income gained from crops sales; other assets, such as
tractor engines, were procured iitith loans.
A similar trend was observed in a survey conducted during the second crop
(October 1989-April 1990). There were 11 farmers who bought household assets
and had their houses renovated. The adopters acquired household assets worth P809
during this period, compared with P185 in assets acquired by nonadopters. One
farmer obtained a loan to purchase a carabao; another farmer acquired a loan to
renovate his house. Income from crop and animal sales was used only for the
purchase of small household items and appliances.
ALTERNATIVE TOOLS FOR CLASSIFYING
TECHNOLOGY ADOPTERS
The results of cluster analysis on data collected in 1987-88 revealed four dissimilar
clusters. A partial tree diagram indicated that CL4 and CL7 were under CL2 with
= 0.52; CL6 and CL8 were under CL3 with = 0.64 (Table 4). However, CL7
had only two observations. The cluster analysis on the 1958-89 data showed 4 major
clusters but 1 cluster had only 1 observation. For both cropping years, only 3 clusters
with more than 5 observations were considered. Cluster analysis based on variables
related to a particular component of technology was also used, but it produced the
same result as when the VARCLUS-selected variables were used.
hlembership between clusters derived using data from each year were
compared by considering the characteristics common to all clusters. There were 32

farmers who were common to both years. The association of the clusters derived
using 1987-88 and 1988-89 data was significant using the chi-square test.
Results showed that farmers transferred from one cluster to another within
the two periods. Differences in impact among the clusters in one period were not
considered. Rather, the differences were compared between the two periods on the
assumption that farmers were subjected to more or less similar conditions in a
particular period, whereas, conditions may vary widely between two periods.
The results of cluster analysis for 1987-88 data were presented by comparing
the clusters in the context of basic farm and household characteristics, farm
practices, crop yield and profitability, and income and expenditure patterns.
Production function models were also estimated to determine the influence of the
clusters on the production function.
Farm characteristics
The demographic characteristics of the clusters showed that CL4 farmers were
younger and had less farming experience. However, they had a higher educational
level than farmers in CL6 and CB.
Share tenancy is a dominant tenurial status among CL4 farmers (82%)
followed by those in CL6 (58%). A more diverse tenurial status is found among
farmers in CL8.*~he CL4 farmers used rice-based cropping systems in flat areas.
Adoption of KABSAKA technology
All farmers started plowing their lands on the last week of May, and crops were
mostly established after the third week of June. Farmers in CL4 and CL8 plowed
their fields twice for the first crop and then, either rotovated or harrowed using draft
animals. About 58% of farmers, covering 79% of the area in CL4, cultivated their
fields using rotovators. All the second crops were WSR except in the case of CL8
where only about 51% of the area was planted to WSR. Farms in CL4 and CL6
established their second crop as soon the first crop was harvested. About 73% of the
CL4 and 72% of the CL6 rice areas had a turn-around period of less than 15 d. A
short turn-around period was possible because land preparation was accomplished
with the aid of tractors (80% of the land in CL4 and 90% in CL6).
Crop damage caused by golden snail infestation was a major problem in
Ajuy. The damage to the second crop was greater than to the first crop. Rice
seedlings, particularly DSR, are vulnerable to golden snails. During the second crop,
farmers in CL4 had to replant about 50% of the area because of the damage caused
by golden snails.

Herbicide is essential for DSR. However, it appeared that farmers in CL4
were using less preemergence herbicide than farmers in CL6 and C U. Despite the
use of herbicide, manual weeding was still employed (i.e., as much as 70 h during
the first crop). Hourever, there was relatively less manual weeding during the second
crop.
Farmers in CL4 used less seed, insecticide, and herbicide during the first
crop than farmers in CL6 and CL8 (Table 5). However, during the second crop,
farmers in CL4 used more seed. The same trend was observed in expenditures on
material inputs (e.g., fertilizer, insecticide, and herbicide). Among the clusters, CL6
had the highest cost for hired !abor for the first crop, while CL8 had the lowest. A
significant proportion of hired labor was used for replanting. On the whole, CL8
farmers had the lowest cost.
In terms of productivity, CL4 and CL6 had almost the same yield, while the
yield of CL8 was significantly lower. Cluster CL4 had the highest net benefit among
the clusters, followed by CM. Cluster CL8 had the lowest net benefit (Table 6).
ANALYSIS OF PRODUCTION FUNCTIONS
The production-function model was estimated for each season in 1987-88. The
estimate of the full model produced negative coefficients for nitrogen and potassium
fertilizers, herbicide, and insecticide (Table 7). In the second round of estimation,
the variables that did not have the expected positive sign were taken out of the full
model. The values for both seasons were acceptable: 0.60 for the first crop and
0.86 for the second crop. The elasticities for hired labor at the 0.02 level were
significant for both seasons. However, the eiasticities for seeding rate were
significant only during the second crop. The coefficients of the dummy variables in
every cluster were significant for both seasons. This result shows the importance of
the clusters in shifting the production functions. Based on the coefficients of the
dummy variables, CL4 had the highest coefficient of 1.24. CL6 had only 0.39.
Cluster CL8 was used as the base cluster.
Household income and expenditures
The income and expenditure patterns of farm households were anrllyzed by
examining the income and expenditure flow per month and its total for the year
(Table 6). The period considered was May 1987 to April 1988. Cluster CL4
appeared to have the highest income for the period (P17,248), CL6 had the lowest.
This confirmed the good performance of the CL4 farmers as reflected in their
output. The share of crop sales in farm income only averaged 37%. On a cluster
basis, CL4 had 44% of farm income derived from rice.
On average, income was distributed evenly, except in September and April
when income was relatively higher. However, when cluster analysis was applied,

there were differences in income throughout the year. For example, CLA had a
relatively stable income flow from October to March. This was not the case in CL6.
However, for all clusters, the period April-September showed an inconsistent flow
of income.
The majority of farmers reported that their expenditures were higher than
their income. In the case of CLA, expenditures were higher than income when
compared with the other two clusters. Expenditures were relatively higher in
October and March. On average, an annual deficit of P6,800 had to be met with
loans. Loans obtained in kind, such as fertilizer from private dealers, were usually
paid in the forin of rough rice. However, there were instances of positive net cash
flows. Generally, a negative monthly cash flow occurred in July and from November
to January. The high expenditure in July and November can be attributed to the
purchase of farm inputs, hired labor costs, and education. Annually, all the clusters
except CL8 had positive net cash floivs.
Cluster CL4 had the highest farm income during the 12-mo period (May
1987-April 19S8), followed by CL6 and C U. The contribution of farm income to
household income was highest in October anlollg farmsrs in CLA. In this case, 84%
of total farm income was attributed to rice production.
CONCLUSION
The KABSAKA technology was not fully adopted in iloilo. Its adoption varied
according to prevailing circumstances. In a way, the technology contributed some
benefits to farmers in rainfed areas by providing them alternatives.
o Classifying KABSAKA adopters as those who used DSR is no longer
valid because filrnlers decide on the crop establishment method based on
various factors, primarily, weather cond~tions. If crops cannot be
established using DSR because of early rain, the fields must be rotovated
before they can be planted to WSR.
o Classifying technology adopters on the basis of level of adoption was a
useful initial step to measure the impact of the KABSAKA technology.
Differences between groups were examined in ternis of practices related
to land preparation, crop establishment, weed control, insect control, and
fertiIizer application. These differences were reflected in yield and net
benefit and in the pattern of household income and expenditure. The
data collected in 1987-88 revealed that CL4 farmers had adopted the
KABSAKA technology more comprehensively and had proved to be
better performers than farmers in the other clusters. Production-function
analysis disclosed that cluster groupings shifted the production function.
Cluster CL4 had the highest level of productivity.

o The classification of farmers on the basis of level of technology adoption
does not permanently confine farmers to a particular group. They can be
shifted from one group to another depending on their response and
circumstances.
o Another approach that needs to be considered is the classification of
farmers on the basis of farm characteristics and the environment. This
approach will determine whether farmers in a particular group have the
same response when a particular change in the environment or
technology occurs (e.g., late rainfall or increases in the cost of herbicide).
o An attempt to analyze the data on a plot basis showed that farmers
manage their farm plots in diverse ways that depend on farm
characteristics. Because an average of the practices is provided when the
analysis is aggregated at the farm level, this variability is not considered.
The case study approach seems appropriate to address this issue.
o The profits from rice production are not sufficient to sustain the
development of the countryside. The pattern of household expenditures
showed that farm income was mostly spent on household consumption.
There were no investments made to improve farm level resources. The
accumulation of assets was for household requirements (e.g., house repair
and household appliances) rather than for farm resources. This pattern
indicated that economic gains due to the new technology are inadequate
to encourage further accumulation of capital among farmers. However,
some farmers did purchase tractors and water pumps.
o Institutional changes in one of the study areas (Barangay Pili) resulted in
increased gains from the new technology. A cooperative was organized
among the farmers in Pili to provide credit and marketing facilities.
These changes were brought about only after the KABSAKA project was
implemented.
REFERENCES CITED
Barlow C E, Jayasuriya S, Price E C (1983) Evaluating technology for new farming
systems: case studies from Philippines rice farms. Internatic~nal Rice
Research Institute, Los Baiios, Philippines.
Medialdia M T S, Ranaweera N F C (1988) An assessment of the impact of
KABSAKA technology (FSR) in Ajuy, Iloilo, Philippines. Paper presented at
the 8th Annual Farming Systems Symposium, 9-12 Oct 1988, University of
Arkansas, Fayetteville, Arkansas.

Price E C (1982) SAS User's Guide: Statistics. SAS Institute, North Carolina.
Ranaweera N F C (1988) The need to assess impact of farming systems research
(FSR) within the Asian context: an overview. Paper presented at the
Monitoring Tour Cum Workshop on Impact of Farming Systems Research in
Selected Asian Countries, 25-30 Apr 1988, Arnigo Terrace Hotel, Iloilo City,
Philippines.
Wangwacharachul V (1984) Direct and indirect impact of the new cropping systems
technology and irrigation in a community economy: the case of Oton and
Tigbauan municipalities, Iloilo Province, Philippines. Unpublished Ph D
thesis, University of the Philippines Los Baiios, Philippines.

Table 1. List of \,ariables idc~l~lfit'd by VARCLUS procedure among 106 variables and
used for cluster ana1)'sis. Aju! . Iloilo. Philippines (1987-88).
\'ariable
code
YRSFARlI
\VHLTR.\CT
PL
SPL
AREA
SLPl
ST2
T 3
T1
STI
l'BWK20
PLOW NI-
SPLOWST
PLPMA
SPLPMA
PLPMM
I-I\VNT
I-IiVPMA
H\VPMhI
RTNT
SRTNT
RTPhIM
SPTPhIbI
SiVSR
TPR
REPLTNG
S REPLTNG
FERTNT
SFERTNT
SHNDLBHR
SAHERBQ
AVEAI
TURN
AVEYIELD
SAYIELD
Years in farming
Wheel tractor o\\.ned
plot number
2nd crop plot number
2nd crop ar2a planted as percenl
of Is1 crop arca planted
2nd crop land position (flat)
2nd crop tenant
tenurial status (leaschuld)
renut-ial sratus(others)
2nd crop tcnurial status (olliers)
lst.c~.op planting bct'ose week 20
1st crop plo\\'inz nu~iihes of rimes
2nd crop pltnving niimbe~. of times
Is1 c1.0~ plo\\.ing po\\,er animal source
2nd crop plcwing po\vsr animal source
1st crop plo\\,ins p\\-er machine sousce
1st crop lia~.~~o\\li~ig number of times
1st crop liar~.o\i~ing power animal source
l sr crop liarr~\vi~lg power machine source
1st crop I-otu\.atiny number of times
2nd crop rotovalin$ number of times
rotovatin_r po\\,er machine source
2nd crop roto\~ating power
n~achins source
2116 crop wet seeded rice
1st crop transplanting
l st crop replantins
2nd crop replan~iny
1st crop fertilizer nu~uher of rimes
2nd crop fertilizer number of times
2nd crop u~eeding labor (h/Iia)
2nd csop a\7erase l~erbicide quantity
I st crop, average active ingred ient
of insec~icide
turn around period
1st crop average yield
2nd crop a\leraSe !:ield
Mean Standard
deviation

Table 2. Average rice yield (kglha) and profitability of rice production by adoptioil category, Ajuy Iloilo, Philippines (1987-90).
First rice crop
Average yield (kglha)
Gross benefit ( P)~
Total paid out cost (P)
Net benefit (P)
C,
4
\O
I Second rice crop
Average yield (kglha)
Gross benefit (P)'
Total paid out cost (P)
Net benefit (P)
a~4.50/kg of rice.
Adopters Non adopters All Adopters Non adopters All Adopters Non Adopters All

Table 3. Conlparison of cash flow of adoprers and nonadopters, Ajuy, Iloilo, Philippines (1987-88 and 1988-89).
Pcl-ccnlagc shar-c
of rice ~o
Cash inflow Cash outtlow Net cash inflow cash inflow
Month Adopter N-adopter Adopter N-adopter Adopter N-adoptes Adopter N-adoptcr
(n = 15) (n = 32) (11 = 15) (n = 42) (11 = 15) (n = 42) (n = 15) (n = 42)
May 1.061
June 490
July 790
Auzust 1,817
September 1,23 1
Octobcr 1,121
Novelnber 1.74 1
Decembcr 1,243
January 1,478
February 1,282
March 930
Aprii -
Total 13.184
May
June
-
820
July 1,071
August 1.528
September 1 ,l 19
Octobel- 1.1 17
November
December
993
2,s 1 1
January 794
February 875
March 565
April 1,440
'rota1 12.833
Note: 1:i~urcs in parentheses are not cash outflows.

Table 4. Partial I-esults of Ward's minimum variance cluster analysis,
56 rice-based farmers, Ajuy, Iloilo, Philippines (1987-88).
Cluster Clusters joined Number of
farms

Table 5. Level of input use for the rice crop by clusters, 56 rice-based farmers,
Ajuy , Iloilo, Philippines (1987-88).
First rice crop
Seeding rate (kglha)
Fertilizer use (kglha)
Urea
11-14-14
h? ixed
Insecticide (kg ailha)
Herbicide (literlha)
Second rice crop
Seeding rate (kglha)
Fertilizer use (kglha)
U sea
14-14-14
Mixed
Insecticide (kg ailha)
Herbicide (lirerlha)
CL4 CL6 CL8 All
(n = 15) (n = 22) (n = 17) (n = 56)

Table 6. Average rice yield (kglha) and profitability of rice crop by clusters, 56 rice-
based farmers, Ajuy, Iloilo, Philippines (1987-88).
First rice crop
Average yield (kglha)
Gross benefit (P)'
Total paid-out cost (P)
Net benefit (P)
Second rice crop
Average yield (kglha)
Gross benefit (P)'
Total paid-out cost (P)
Net benefit (P)
'~4.501kg of rice.
CIA CL6 CL8 All
(n = 15) (n = 22) (n = 17) (n = 56)

Table 7. Production elasticities of various production input variables in the estimated
production function, 56 rice-based farmers, Ajuy, Iloilo, Philippines (1987-88).
Variable Full model Reduced model
1st Crop 2nd Crop 1st Crop 2nd Crop
Intercept 5.34** 0.04 5.46* 1.13
(8.45) (0.10) (8.24) (0.3 1)
Seedins rate 0.04 0.48* 0.02 0.49**
(1.33) (0.08) (0.57) (1.89)
N fertilizer -0.07 0.05
(-1.32) (0.042)
P fertilizer 0.18 0.18
(1.42) (0.42)
K fertilizer -0.22 -0.19
(-1.57) (-0.44)
Herbicide -0.34* -0.60*
(-2.39) (01.88)
Insecticide -0.004 -0.22
(-0.06) (-1.65)
Hired labor 0.24** 0.36** 0.22** 0.40**
(2.68) (1.75) (2.41) (1.97)
P fertilizer
F-v alue 9.41** 34.21** 12.22** 52,51**
% *c
Significant at 1 % level. Significant at 10% level.

IMPACT OF FARMING SYSTEMS RESEARCH ON THE RESEARCH AND
EXTENSION SYSTEM: THE CASE OF THE PHILIPPINES
V. T. ~illancio', A. ~unzalan', C. ~ina', and V. R. Caranga12
The Farming Systems Approach has a key role in the strategy for the
development of the agricultural sector in the Philippines during the last
two decades. Many of the institutions involved in research and
development have adopted the concept and have developed
methodologies over time to provide more meaningful and relevant
technology to the farmers in their individual environments. The study
highlights the developments and the operations of Farming Systems
Development in the Philippines. analyses its impact, and concludes that
further emphasis should be provided to the strengthening of the networks
that exist as a rneans to further enhance the FSR programs in the
country.
A policy declaration has been made in the Philippines to use a farming systems
approach (FSA) as a general strategy to promote agricultural development. Executive
Order 116 (30 Jan 1987), which provided for the reorganization of the Ministry of
Agriculture and Food (MAF), mandated to "encourage people's participation in
zgricultural development . . . and use a bottom up, self-reliant farming systems approach
that will emphasize social justice, equity, productivity, and sustainability in the use of
agricultural resoprces." The objective of this strategy was to "improve farm income and
generate ivork opportunities for farmerslfishermen and other rural workers."
The national thrust on farming system research and development (FSR&D)
stemmed from the lessons and experiences gained by implementing various projects
using the FSA. These projects began with multiple-cropping and cropping-systems
projects (1970s to mid-1980s) and have continued to the current farming systems
research and extension (FSR&E) projects. This paper highlights the historical
development and operation of FSRSrD in these projects and the response of these
projects to evolving patterns, concepts, and procedures. The effects of these projects on
small farms, their farming systems, farm households, and the community are also
discussed. Finally, lessons, esperiences, and issues that affect the operations of these
projects are identified.
'lowland-based Farming Systems Division, Farming Systems and Soil Resources
Institute, College of Agriculture, University of the Philippines Los Bafios, Laguna,
Philippines.
2~sian Rice Farming Systems Network (ARFSN), International Rice Research
Institute, P.O. Box 933, Manila, Philippines.

FROXl GREEN REVOLUTION TO FARhlING SYSTEhlS APPROACH
The national thrust on FSR&D stemmed from the lessons and experiences gained
from various projects that used the FSA (Table 1). These had several common
characteristics: a focus on mu1 tiple cropping and cropping systems research and
extension (R&E) in the rainfed lowland areas (e.g., MCEPP, KABSAKA, RADOS,
MAhTBILAYAKA. and KASATINLU); the implementation of cropping systems
R&D as a component of an integrated development project (e.g., ABC project,
CVIADP, NSIRDP. and PIADP); a focus on croppin systems RcYrE in the uplands
and hilly areas (e. .. VRP and AUDP); a divergence T. rom activities oriented toward
cropping systems P e.g., FSDP-EV and FSDP-B~col); and the development of
regional and provincial capabilities to implement FSR&E activities, such as those
done by the Regional Integrated Agricultural Research Systems (RIARS) and later
by the AMP-ROS.
The development of FSR&D in the Philippines was characterized by a shift
from a comniodity-oriented strategy to a m~~ltifarni-enterprise approach. With the
intention of increasing the income of small-scale farmers, \rarious crop
intensification and diversification programs were implemented. In 1972, a
collaborative pilot project knolvn as the Multiple Cropping Extension Pilot
Production Program (MCEPP) was launched by the University of the Philippines
Los Baiios (UPLB) in collaborcltion with Central Luzon State University (CLSU)
and Camarines Sur State Agricultural College (CSSAC).
The strategy for diversification included expanding the farm area, increasing
yield per unit area, and increasing the number of crops grown in an area for one
year. To a large extent, the strategy focused on rice-based farming systems. This
prompted the establishment of an interagency applied research project on rainfed
and upland rice with other crops by the Department of Agriculture, IRRI, and the
Bureau of Agricultural Extension (BAEX).
The government recognized the need to consolidate the efforts of various
commodity programs and the successes of the pilot multiple cropping projects. Thus,
the National hlultiple Croppirig Production Program (NhlCPP) was launched in
1975. The program integrated the existing commodity progfams (hf-99, Masaganang
Maisan, and GSK). Integration \vas designed along three d~niensions: the use of a
cropping systems approach in crop productio~i, thc change of respo~isibility of
agricultural technicians from sinsle-crop to multiple-crop cultivation on the farm,
and the provision of credit facilities hy shifting from single-crop loans to loans for all
crops grown lvithin a period of 1 yr.
In a parallel development to the NMCYP, IRRI, BAEX, and the Bureau of
Plant Industry (BPI) conducted cropping systems research in 1974 in the rainfed rice
areas of Iloilo through the KARSAKA Project. This research demonstrated the
feasibility of t~vo cropping seasons for rice plus a third upland crop in the area.

The remarkable performance of the technology for a two-crop system under
the KABSAKA Project in Iloilo encouraged multilocation testing of the technology
in other parts of the country. This gave rise to other projects such as KASATINLU
in South Cotabato (1979), MATISAYON in North Cotabato (1979),
MANBILAYKA in Pangasinan, and ZAMDUGANI in Zamboanga del Sur.
The lessons and experience generated from these projects became the basis
for the development of cropping systems research n~ethodology in the Philippines.
During this period, further testing of the cropping systems methodologies was
undertaken in projects such as the Agusan, Bukidnon, Capiz (ABC) Settlement
Project, Philippine-Australian Development Assistance Program (PADAP), Bicol
River Basin Development Pro'ect (BRBDP), and Samar Integrated Rural
Development Project (SIRDP~.
Activities on cropping-systems research and development were expanded
through the Rainfed Agriculture Development (Iloilo) Project (RADIP). This
extended the KABSAKA project in Iloilo, and in 1951, established Rainfed
Agriculture Development Outreach Sites (RADOS) in provinces with vast areas of
rainfed rice: Ilocos Sur, Pangasinan, Mindoro Oriental, Leyte, Iloilo, Bohol, Davao
Sur, South Cotabato, and North Cotabato. The site staff came from the Ministry of
Agriculture and Food (MAF) and technical staff and support came from UPLB,
IRRI, BPI, and NFAC. The lessons and experiences gained from RADOS were the
basis for the national technology verification program of the RIARS in 1983-88 and
the Research and Outreach Sub-Project of the Accelerated Agricultural Production
Project (AAPP-ROS) in 1958-91.
The N'ational Technology Verification Program was the prime activity and
thrust of the RIARS. The RIARS was created under the agricultural-research
component of the Agricultural Support Services Project (ASSP) in 1991. The
objective of the project was to strengthen essential services in agriculture,
particularly research. It also paved the way for the reorganization of the different
bureaus and agencies of the DA (e.g., BAEX, BPI, BS, and BAI) to give more
responsibility to the regional offices for faster dissemination of agricultural
technologies. All efforts centered on cropping systems technologies because
research developed from problem identification in the target sites to technology
generation, adaptation, verification, and finally technology dissemination.
Subsequently, crop-livestock integration activities were added in 1985.
Although most efforts were geared toward cropping systems activities, s(?i-!zi
projects also focused on FSR&D. These projects include the USAID-supported
Farming Systems Development Project - Eastern Visayas (FSDP-EV), the Farming
Systems Development Project - Bicol (FSDP-Bicol), and other projects under the
Rainfed Resources Development Project - I1 (RRDP).
The historical development of FSR&D in the Philippines had three critical
stages: multiple cropping, cropping systems, and farming systems. The KABSAKA
project made valuable contributions to the development of cropping systems R&D
(which was subsequently developed into FSR&D) and to the development of

ainfed areas. The RIARS project applied the methodology in the national program
using local resources and expertise and external funding.
IMPACT ON ORGANIZATION OF RESEARCH AND EXTENSION
The evolution of FSR&D in the Philippines is characterized by the policies,
organization, and management of the research and extension systems in the country.
Various institutions integrated the FSA concept into their R&D activities at
different stages (i.e., at the conceptual, structural, and operational levels). These
institutions adopted the FSA concept, translated it into various programs, and
developed an organizational structure that operated the FSRSrD projects.
The impact of FSR&D on the organization 2nd management of the R&E can
be seen in the way various RSLE institutions responded to the incorporation of
FSR&D. Three types of units were created in the institutions to address FSR&D:
units created as a separate institute in academic institutions, units within projects,
and divisions or units within the DA.
At UPLB, the Multiple Cropping Section (h4CS) was organized by the
Department of Agronomy in 1977 to implement the MCEPP. Likewise, with support
from NFAC, the UPLB College of Agriculture Iaunchetl Comprehensive Farming
Technology Support to Small Farmers (CFTSSF). In 1980, the MCS collaborated
with the NFAC to coordinate the cropping systems program of the RADOS as part
of RADIP. In the same year, staff from the UPLB-MCS were detailed to NFAC to
constitute the Cropping Systems Diirision (NFAC-CSD), which was a reorganization
of the former Multiple Cropping Section at NFAC. In 1983, the Farming Systems
and Soil Resources Institute (FSSRI) was established. It pooled staff from the MCS-
and the NFAC-supported Countryside Action Program (CAP). The FSSRI
implemented the Small Farm Systems (SFS) Component of the World Bank-
supported ASSP in 1933-1988.
Anticipating, the role of the Regional State Colleges nnti Universities (SCUs)
in the implementation of FSRJiD-related projects, staff from the SCUs were
trained. This training started with the involvement of CLSU and CSSAC in the
MCEPP (1972- 1979).
In 1980, staff from the Visayas State College of Agriculture (ViSCA) trained
in cropping systems methodology with RADOS staff in anticipation of their future
involvement in FSDP-EV in 1982. The ViSCA subsecluently est:~blished the Farm
and Resource Management Institute (FARhlI) in 19S5 to address its farming
systems thrust. Benguet State University (BSU) was likewise ir~volved with the
FSR&D component of the Highland Agricult~~ral Development Project (HADP),
and attempts were made to establish an institute on farming systenis research.
The farming-systems research component of the Philippine Council for
Agriculture, Forestry, and Natural Resources Research and Developn~ent
(PCARRD) was approved by the Governing Council on 23 Sep 1975. A Farming

Systems Research Network was organized. It consisted of 13 research centers and
stations, with UPLB as the national center for farming systems research. Priority
areas for research shifted from understanding the basic determinants and
performance of farming svstems in the country (1976-80) to developing a crop-based
farming systems approach (19S0-83).
The Farming Systems Research and Development Network (FSRDN) was
organized in 1989, composed of UPLB through FSSRI, DA through BAR and ATI,
a network of SCUs in various regions of the country. The FSRDN facilitates the
exchange of expertise and information on FSR&D in the country. With the farming
systems development project in Bicol and Eastern Visayas, a Site Research
Management Unit (SRhlU) has been organized to formulate and implement the
farming program in each site selected within the region.
In 1982, the Agricultural Research Office (ARO) was organized under the
Office of the Minister of the MAF to coordinate cropping systems research
programs, whereas, the KFAC-CSD coordinates production programs. The farming
systeins thrust of DA was further strengthened with the reorganization of MAF by
Executive Order 116 (19S7), which also created the Bureau of Agricultural
Research (BAR). BAR assumed the responsibilities of ARO and was mandated to
coordinate a11 ;igricultural research of the DA.
The most recent development in agricultural RLQD was the enactment of the
local government code, which decentralized agricultural extension to local
governments. More attention is being focused on the operations of FSRRrD at the
provincial and municipal levels. Although there is already a certain degree of skill
and an appreciation of FSRRrD as an approach nt the provincial level, more efforts
must be focused on advising local governments about FSRRrD. This is a challenge
that must be met in the coming decade.
DEVELOPhrIENT OF FSRkD METHODOLOGIES
The development of FSRLQD in the Philippines hr~s been influenced by global
development of the approach. The development of methodologies is most apparent
if all stages of FSRRrD are examined. In site selection, tools are being refined and
include spatial maps and con~puter-aided tools such as Geographic Information
Systems (GIS). Sites selected for FSR&D activities have shifted from rice-basecl
environments to marginal areas (e.g., rainfed uplands and hilly areas).
Site description and diagnosis has shifted from formal tools to less formal
2nd rapid techniques such as Rapid Rural Appraisal (RRA) and other variants.
Agroecosystem analysis, gender issues, diagnostic techniques, and ethnographic
tools have enriched the tool kit that can be used.
The design of R&E strategies has increasingly focused on farmer
circumstances. Ex-ante evaluation of the technology is beginning to integrate

stability and sustainability. 1nstitution:il support, particularly marketing facilities, is
being considered. The PCARRD-supported FSSRI and developed Agricultural
Suitability and Evaluation S!.stems (ASES) in 1990. The use of biophysical
parameters in ASES has already been initiated. These are now integrated with
socioeconomic parameters.
There is increasing participation of farmers and farmer groups in the testing
and evaluation process. The FSDP-Bicol provided major innovation with the
Porbaran approach, in which farmers were provided with a range of technology
options during a community planning workshop. The farmers themselves dec~ded
what to try and how to do it. The project staff served as facilitators. Farmer-to-
farmer extension has also been effective in FSDP-EV and FSDP-Bicol.
Some statistical methods are used to evaluate OFR, but economic analysis is
still given extra weight. Risks, stability, sustainability, gender effects, and
practicability are also gaining wide consideration. Efforts have been made by the
RIARS to train noneconomists in the tools and techniques of economic analysis.
The dissemination stage has suffered a set-back because of a lack of
extension-research links during the last four stages of FSRcYrE. Successful cropping
systems have been tested and evaluated by the RIARS, but the results have not been
disseminated because of a lack of extension support. Another f~ctor is the emphasis
given to research compared ivith extension.
IMPACT OF FARhlING SYSTEhlS ON FARM HOUSEHOLDS
Assessment of the impact of FSR'QE has g;lined attention over the last 5 yr. Impact
studies place emphasis on the rate and degree of adoption of tlie technology and its
impact on resource use, productivity, and income. h4inimal consideration is given to
factors that indicate an i~nprovenient in the socioeconomic well-being of the farm
population. Also, little attention has been gi\.en to tlie impact on conimunities and
institutions.
Impact studies include significant changes in the cropping patterns practiced
by farmers. An increase in cropping intensity from 1.3 to 2.4 was observed among
KABSAKA farmers when the KABSAKA technology was adopted. KASATINLU
farmers increased their cropping intensity froni 1.9 to 2.57, as did farmers in the
Capiz Settlement Project.
Another aspect of impact is physical changes that occur in the fiirm after
project participation. An impact evaluation study of RRDP reported an increase
from 0.5 ha to 2.75 ha in tlie average size of farms cultivated by the beneficiaries.
This change was attributed to production opportunities that had been brought about
by the project. There was also increased use of idle lands for crop production,
improved soil fertility, better watershed protection, and decreased soil erosion.

Another impact has been on the ninnagement of inputs. There has been an
increase in the use of commercial inputs, particularly fertilizer, pesticide, and
herbicide. Various studies have shown hisher le\.els of fertilizer, pesticide, and
herbicide use among farmers after the introduction of K,ABSAI(A. Also, 31% of the
KABSAKA farmers resorted to niechaniz:ition, i.e., the use of tractors for land
preparation during the first rice crop, whereas, 50% of the area of the second rice
crop was prepared using machinery.
Farming systems performance has also retlected the impact of FSR&D
projects. Increases in productivity and income were observed ainong project
beneficiaries. For e~ample, with KABSAKA, annual rice production rose from
1.2 t/ha to 8 t/ha. In the case of upland rice in Capiz, yield increased from 1.5 t/ha
to 2 t/ha. Increased yield was also obsend among KASATINLU and
MATISAYON farmers. The KABSAKA teclinology also allou~rld farmers to
increase their labor productivity (i.e., average physical output per person-day).
Based on the 1953 RADIP monitoring survey, l:lbor productivity increased by
45.6%. Generally, farm income illcreases with increases in the level of production,
but this may not necessarily increase net income bec:luse of the high costs associated
with the recommended technologies. The KABSAKA project, however, reported
higher net farm income among farniers after project participation. In the case of
RRDP, average family income before and after :idoption of the technology rose
from P1,278 to P2,049 per month. The integration of li\,estock into the farming
system also increased farm inconie of farlners in RADIP.
Other impacts reported in 1990 by the RRDP Impact Ev:~luation Study
included the increased motivation to plant crops, a\vareness of the potential of
natural resource: in the comn~unity, lessened ju\.enile delinquency, encouragement
to be industrious, and promotion of self-reliance anlong farmers.
SOh4E ISSUES OF CONCERN
During the 1990 National Rice-based FSRLSLE PI:i~ining Workshop, several issues
were identified in the implementation of FSRLQE
in RBFS:
o Determination of recommendation domain :\lid extrapolation area. More
effort is required to refine the use of GIS ancl ASES.
o Too much reliance on RRA. Emphasis should be placed on the use of
formal surveys and other data-gathering techniques that will aid
monitoring, evaluation, and impact assessment.
o Limited participation of farmers and extension specialists. Their
participation must be encouraged.
o Limited expertise on the technology options that are available. A
mechanism is needed to provide updates on recent developments.

o Limited feedback at all levels. A mechanism is needed to encourage
frequent interaction among project participants.
o Tools for monitoring, evaluation, and impact assessment and the need to
link these activities as a continuum in FSR&E projects.
o Cases of extension specialists turned researcher. This attitude was
encountered with RADOS and RIARS; therefore, there is a need to
instill the extension responsibilities in FSR&D staff and to develop a
research-extension interface.
o Limited appreciation of the contribution of farmers to FSRRrE by other
development workers. There is a need for intensive training and
information dissemination on FSRRrE.
o Limited FSRRrE personnel because of the reassignment of trained
personnel with the implementation of the local government code.
Apart from these issues and problems, other matters must be mentioned: the need
for more practical and flexible approaches or methodologies for FSR&D, the
organization and managerial problenls associated with decentralized FSR&D, the
operations of a multidisciplinary and interdisciplinary team, reorientation from a
technology-focused approach to problem (opportunity)-driven activities, indigenous
technical knowledge and the changing environment, and technology
commercialization and FSR&E.
A COURSE OF ACTION
This historical analysis of farnling systems research and development in the
Philippines has revealed the impact of the approach on the research and extension
system of the country. The impact is reflectzd in the changes that have occurred in
the focus, conceptual approacl~, organization, and management of the agricultural
research and extension system. The research and extension system responded to the
evolution of farming systems research and development methodologies and
concepts.
The farming s stems research and development approach is still evolving.
The potential of the ! arming systems research and development network to
orchestrate this evolution is evident. The farming systems research and development
could be mobilized to address these issues by specifically supporting the
development of (1) ASES and related tools (e.g., GIS) to make use of the data bases
that are generated a common framework for FS diagnosis and design that employs
RRA and related techniques and other formal approaches, (2) techniques to
integrate stability and sustainability analysis in farming systems development,
(3) impact assessment methodology to tackle both micro and macro impacts, and

(4) a mechanism to link the commercialization of technology with farming systems
research and development.

Table l. Chronological sequcnce of projects and activitics rclatcd to farming systems research and dcve1ol)mcnt in [he Philippines (1972-')l)."
Y ca I- Prograni/pro.ject Agencies iavolved Fu~idi~ig source
1972-79 Multiple Croppiiig Extension Pilot Production
Progl-am (MCEPP) at Laguna, Nucva Ecijn,
Camarines Sur, and Iloilo
1974-85 National Multiplc Cropping Program (NMCP)
1978-80 Cropping Systems Rcscarch ~utrcachProjccr
a[ Tanauan, Batangas; Sta. Barbara,
Pallpasinan. and Oton, Iloilo
1077-8 1 Two Ricc Crop Systenis Projccts at Pangasinan
(MANBILAYAKA), lloilo (KAESAKA), South
Cotabato (KASATINLU), Zamboanga (ZAMDUGANI),
and North Cotabaco (MATISAYON)
Cropping Systcms 1'rogr;rm at thc hgusan,
Bukidnon and Capiz Scttlc~ncnt Arcas (ABC
project under the Second Rural Devclopmcnt
L;III~ ScttIci11cnt Pro.jcc~)
Sloping Agricultural Lilnd Technology (SALT)
at Ba~lsalan, Davao del Sur
Cropping/Farming Systems Research Outrcach
Sitcs at Tugucgaraa, Cagi~yan; Guilnba
Nucva Eci,ja and Clavcrin, hlismnis Oricntnl
Rainfcd Agricultural Devclopment (Iloilo)
Projcct (RADIP) - An Expansion of KABSAKA
Rainfed Agricultural Devclopmcn~ Outrcach
Si tcs (RADOS) at llocos Sur, Pangasinan,
Mindoro Oricntal. Lcytc, Iloilo. Bohoi, Davao
Sur, Soutli Cotabato, and North Cotabato
- - -----p-pppppp
UPLB. DA Rcgion IDRC
NFAC, IRRl
M BLR C
IKRI/DA
NFAC
IRRI/IDRC
COP ant1 Ford
IRRI-PCARRD
NFAC/
World Bank
World Bank
World Bank
1981-85 Multiple Cropping Projcct urldcr Philippine- D A AlDAU
Australian Dcvclop~nent Assistance Program
(PADAP)
--

Table 1. Chroaological scqucncc of ill-ojccls and activities rc1;itcd fo Farming Sys~clns Rcsearch and Dcvclol)lllcnt in thc I'liilippi~~cs, 1972-0 1.
Farming Systems Development Projec~ at Eastern
Visayas (FSDP-EV)
Palawan Integrated Area Development
Project (PIADP)
Phase I ( 1982-90) and Phase 11 ( 199 1-96)
Farming Systems and Soil Resources
Inslilulc (FSSRI)
Regional Integrated Agricultural Research
Syslcms (RIARS) under thc Agricultural
Support Services Program (ASSP)
Northern Samar Intcgratcd Rural Development
Project (NSIRDP)
Philippilie Farmiiig Systelns R & D Progralll
Farming Systems Dcvclopment Prqject at
Bicol (FSDP-Bicol)
Philippine Australian Rainfed Lowland Antique
Project (PHARLAP)
Rainfed Resources Development Program
(RRDP)
DA, NIA, DPWH ADUIEEC
DENR, DOH, DSWD
DAIARO, IRRI World Bank
PCAliKD
DA-V
AIDAB
USAID
DAIARO, ANU ACIARIANU
DA, PCARRD, SUCs USAID

Table l. Chronological sequence of projccts and activities related to Farming Systems Research and Development in the Philippines, 1972-91.
1985-prcscnt Ccntrnl Visayns RcgionnI Projcct-l (CVRP) DAIDENR USAID
1985-present Farm and Resources Management Institute
(FARMI) at ViSCA
1986-present Accelerated Agricultural
Production-Rcscarcl~ and
Outreach Subproject (AAPP-ROS)
1987-present Highland Agricultural Development
Project (HADP) DA-BSU
1988-present Sorsogon Integrated Area Dcvclopmcnt
Project
1988-present Central Cordillera Agricultural Program
(CEC AP)
ADB
DA/LGUs, NCO EEC
DA World Bank
1989-present Farming Systems R & D Network DA-ATI, FSSRl DAlBAKlSUCs DAIUSAID
1989-present Southern Mindanao Agricultural
Project (SMAP) DAISCO EEC
his list is an updated version of the co~npilation by R V Labios, January 1991 (Acronyms listed in Appendix).

ASSESSMENT OF THE IMPACT OF A FARMING SYSTEMS-BASED
TECHNOLOGY SITE IN SRI LANKA
N. F. C. Ranaweera, P. A. Samaratun 3, J. M. K. P. Jayasinghe,
and G. K. Renuka B
Sri Lanka has been actively involved in the development of new
technologies within the perspective of farming systems over the last 15
yr. Increasingly, questions have been asked as to the impact of such
technologies to the farming community. Previous impact studies
concentrated primarily on the adoption levels of the technologies and
less in terms of actual impact. This study critically examines the
impact of a new technology at a particular site in Sri Lanka. Using
production function techn~ques, the study concludes that there were
structural changes in the production process and in the personal
incomes of farmers. However, there were no significant changes
observed in capital accumulation, nutritional status, and expenditure
patterns between the adopters and nonadopters of the new
technology.
Agriculture in Sri Lanka faces problems of increased consumer demand for basic
foods, high unemployn~ent in the rural sector, and diminished land resources.
Strategies were developed to address these problems by increasing the intensity of
cultivation and diversifying the use of limited farm resources. Within this
framework, a strategy for crop diversification combined with intensification of
resource use was considered the key to stronger agricultural growth.
FARMING SYSTEMS RESEARCH IN SRI LANKA
These problems in agriculture required the developnlent of suitable component
technologies (e.g., varieties with appropriate duration, crop combinations, and crop
sequences) that were not only technically feasible but socially acceptable and
econon~ically tenable. Rice and other field crops (OFC) are produced in Sri Lanka
on small-scale family farms on which interactions between farm production, off-farm
and nonfarm activities, and household consumption are highly significant. Initial
studies began in 1976 at Walagambahuwa (a minor tank-based cropping system in
the low-country dry zone) and Katupotha (in the low-country intermediate zone).
Subsequently, the Department of Agricult~lre commenced farming systems research
(FSR) programs in other locations under the purview of six regional agricultural
research stations (Table 1). Details of these findings are described by Fernando
(1979), Upasena (19Sla,b), and Sikurajapathy (1986).
'~ivision of Agricultural Economics and Planning, Department of Agriculture,
Peradeniya, Sri Lanka.

Impact studies
A number of studies documented the adoption of the new technologies, but few
concentrated on their impact. Ranaweera and Siripala (1980) and Ranaweera
(1983) studied the impact of new cropping systems technology under minor-tank
irrigation conditions and concluded that the impact had been primarily in terms of
component technologies--bztter crop management and use of improved varieties.
To e\.aluate the impact of FSR on real incorne or on household expenditure
patterns, nutrition, education, accumulation of household and agricultural capital
items, or other assets, a study was initiated in 1987 at two FSR sites--Uva
Paranagarna and Katupotha.
OBJECTIVES
The spzcific objectives of the study were to examine the adoption of new technical
practices by farmers and estimate the relative efficiency of resources used under
traditional and new technologies; to study the impact of technology adoption on the
structure of crop-production functions, factor inco~nes, and personal incomes; and to
examine the impact of the technology on nonq~~antifiablt: benefits such as better
standards of nutrition.
STUDY SITE
The Uva Valley, represented by the Uva-Paranagama FSR site, has 25,000 smallscale
vegetable farmers ~ ~llo operate, on average, on less than 0.5 ha and are
responsible for nearly 60% of the total vegetable and potato production of the
country (Agricultural Implementation Programn~e 1990).
Of thz 6,600 ha of 1o:vland ricefields in the region, about 6,400 ha are
cultivated nith rice during the maha (January-May) season. A major portion (50%)
of the lowland area is used for a second crop of vegetables and potatoes planted
immediately after the rice crop. The balance of the land has problems with drainage
or irrigation. A second crop of rice is usually grown if the problem is drainage; if
poor irrigation is the problem, the field is left fallow. The third crop for the year in
the lowlands coincides with the heavy rains and cold ten~perat~~res of October-
December. This is the only period when nonirrigated ~~pland areas can be cultivated
with a seasonal cash crop. The FSR site at Uva Paranagama represents the complex
physical environment of the region.
Patter~is of land use
The topography of the Uva Brlsin ranges from undulating hills with gently sloping
broad valleys to steep narrow inclines. The predominant soil is a red-yellow
podzolic, and the valley bottom is a fertile alluvial fill. Terraced upland areas and

icefields are supplemented Lvith irrigation water from stream diversions. The land-
use pattern can be broadly classified into four main categories.
A'onimgated uplarzd areas. Annual cropping is limited to one vegetable or
potato crop during the main rainy season (November-January). A few farmers grow
a low input, short-term second crop of legumes.
Imkated upland area aud borne garderzs. Two or three seasonal crops of
vegetables or potatoes are cultivated according to the availability of supplementary
irrigation facilities. A characteristic of the home garden is a mixture of perennial
tree crops and livestock that is given preference around the home.
Imkated Lowl17?1ds. These are further classified as ricefields that receive
assured irrigation water every year and ricefields that receive assured irrigation
water on a 2-3 yr rotation. Just after the maha season, rice is cultivated in lowlands
which are assured supplementary irrigation. Within the irrigated lowlands, poorly
drained or imperfectly drained lowland areas, especially those situated below the
perennial water channel, are cultivated with rice during the second season.
Ii'ell-drained lo~t~la?zds. If these have assured irrigation, they are usually
cultivated with potato (the most profitable crop) immediately after the first rice crop
(late June- mid-September). The third crop in the lowlands coincides with the heavy
rains in November and December and the coldest period of the year. Only welldrained
and moderately well-drained soils are cultivated with a third crop (where
cattles are not a threat). Usually cattles kept in the highlands are allowed to graze
on the lush grass in the lo~vland areas during this time of the year, which makes the
highlands available for a seed crop of potatoes.
OBJECTIVES OF THE FSR PROGRAM
In Uva Paranagama, the FSR program sought to shorten the time of the rice crop in
the field frcjm 5.5 to 4.5 mo to allow a second crop to be stabilized and possibly a
third crop to be grown and introduce new potato and vegetable varieties and new
crop cultivars (e.g., soybeans and onions); to take best advantage of the environment
by adjusting the time of lanting and recommend a fertilizer package to take
advantage of residual ef P ects; and to improve patterns of labor use, particularly by
using family labor more evenly throughout the year. Results of the research at Uva
Paranagama are presented by Fernando (1979) and Upasena (1981a,b).
CONCEPTUAL FRAMEWORK OF IMPACT STUDY
Most studies of the impact of FSR on farm productivity and welfare are made
between with and witllout, or udopter and nonadopter, groups of farmers. The
common practice is to estimate a production function with a dummy variable to
differentiate between farmers using and not using the technology and to ascertain
the difference in productivity between the two groups. This is often accompanied by

some simple statistical tests to ascertain whether there are significant differences in
the welfare determinants of the farmers belonging to the two groups (Hafi and
Ranaweera 1990). The rationale behind this approach is that there is an impact on
productivity if the dummy variable is significant. The significant differences found
among welfare indicators are then attributed to this impact on productivity.
However, when a production function between two farmer groups is
estimated using pooled data with a dummy variable, the implicit :issumption is that
there is only one set of structural parameters common to the two groups. The only
difference, if the technolop had an impact, would be in the intercepts. This
represents only partial reality because a substantial difference between the
technologies used by the t ~'o groups of farmers nlould most probably result in two
different production functions with different parameters for another variable. This
necessarily changes the factor proportions and results in changes in factor incomes
(factor shares) and consequzntly in personrll incomes.
In the earlier approach, the differences in welfare indicators between the two
groups of farmers are unquestioningly attributed to adoption of the new technology.
The actual factors that link a technological change to a change in f:lrm welfare (i.e.,
income generation and distribution parameters) are left totally unexamined because
of a paucity of data
In this study, three facets of this in1p:lct were considered:
o If the key practices or inputs of the new technology package are adopted
widely, it can be stated that there has been an impact on agronomic
practices (i.e., there has been a technical inipact);
o Adoption of some agronomic practices, or a technical impact alone, does
not guarantee an economic impact. Economic impact req~lires the
adoption of practices to such a degree that a structural change is induced
in the production functions of the farm; and
o A structural change leads to changes in functional and, thereby, personal
income distributions, which, in turn, vary .the levels of welfare and give
rise to a welfare impact.
The levels of adoption of various components of the tecllnology must 172
examined to determine their agronomic impact on farm practices. To ascertain the
economic impact, an analysis is required of structur:ll ch:lnges in production
functions and of changes in factor payments.
If any welfare impact of the new technology exists, a c11:lnge in the le\fels and
distribution of personal income would rnost probably be cliscernihle. The factor
incomes are, therefore, converted to personal incomes by taking into account the
ownership of the various factors by farmers and by other individuals or institutions.

Changes in personal income are used as a major welfare indicator and as a means to
substantiate the impact on other welfare indicators (e.g., accumulation of wealth
and better nutrition).
Sample selection
Because of certain complexities at the Uva Paranagama site, a with and without
methodology was used. At the initial FSR site, more than 90% of the farmers grew a
short-duration rice variety and a third crop. This created a situation in which there
were hardly any nonadopters and, therefore, it was impossible to select a reasonable
sample of nonadopters. Therefore, another village (Medawala) about 10 km from
the FSR site was selected as the second (without) site. Medawala had similar
climatic and topographic conditions but had not been exposed to the FSR
technology.
Although the farnlers at the with site had been exposed to the FSR
technology, some (10%) had not adopted it. There were also farmers in the without
site who had observed the FSR technology and adopted it without persuasion from
outsiders. Farmers at both sites were categorized into two groups: adopters and
nonadopters. The adopters cultivated n short-duration rice variety and grew three
crops per year. The nonadopters cultivated long-duration rice and cultivated two (or
sonletin~es three) crops per year. In both groups, there were farmers to whom FSR
technology was formally introduced (the with-site farmers) and to whom formal
exposure was not given (the ~vitliout-site farmers).
Twenty-three farnlers from the with site and 14 farmers from the without site
cooperated with the data collection. Of the total number of farmers from the two
sites, 19 farmers were adopters and 18 farmers were nonndopters.
Analytical tools
As a preliminary analysis of farm productivity, simple arithmetic means of inputs
and outputs were compared between the two groups of farmers. Mean yields and
incomes from these crops for the two groups of farmers were compared using a
t-test. Whole-farm budgets for the three cropping seasons were coniputed to
compare the productivity for the three different crops.
To analyze structural changes in production activities, separate production
functions were estimated using ordinary least sqiiares for the two groups of farmers.
Changes in functional, and thereby personal, income distribution as a result of
structural changes in the production pattern were obtained using the accounting
method proposed by Herdt (1978). This analysis was conducted separately for three
cropping seasons as well as for the full-year production cycle.
Change in personal income was used as a major welfare indicator and as a
means to substantiate impact on other welfare indicators (e.g., accumulation of farm

assets). Patterns of food consumption by farmers within a one-year period were
taken into consideration to assess the impact of the new technology on nutrition.
A pooled t-test was used to determine whether the differences in crilorie and
protein-consuniption levels in the tn.0 groups were significantly different.
Productivity anal3sis
RESULTS AKD DISCUSSION
Group averages of far~ner characteristics (i.e., age, number of years of schooling,
and size of the farm family) of adopters and nonadopters in both study areas fell
into narrow ranges. This indicated tllrit there was ho~nogensity between the two
oroups of farnlers in the tu.0 areas (Table 2). An average farmer was about 52-54 yr
Eld, had about 4-7 yr of schooling, and supported a krinily of 5-6 members. Although
the years of farming experience of adopters was nun~erically higher (about 32 yr)
than nonadopters (25 yr), both groups had spent sufficiently long periods in
agricultural production to fully understand their far111 practices. Therefore, a
significant difference in production patterns of the tulo groups is highly unlikely to
be induced by social background.
The averxge farm size of an aclopter (0.81 ha) was ljigger than that of a
nonadopter (0.76 ha). The average lo\vland size (0.42 ha) of adopters was also
bigger than that of nonadopters (0.40 ha). Nonadoptsrs had larger highlands (0.40
ha) than adopters (0.39 ha). hlajority of farmers in both groups had land holdings
below 0.7 ha. Less than one-third of the farmers had land holdings larger than 1.0
ha, and a slightly higher percentage of adopters owned holdings in this category.
The distribution of loiipland by tenurial arrangement revealed that 42% of
adopters and 43% of nonadopters were owner-operators (Table 3). Only a small
percentage of farmers did not own lo\vlands. The f:irmers who did not own lands
accounted for 22%- in the nonadopter group and 217c in the adopter group. Some
farmers operated their o\4.n lowlands as \veil as some lowl:inds owned by others
(3770 of adopter farniers and 33% of no11:idopters). Ollly s small percentage of
farmers in each group did not own hig1il;inds. Both adopters and non:ldopters
operate \.cry slnall holdings and more than h;llf of them are tenants. There is no
substantial difference betn~een land ownership or tenurial patterns of aclopters and
nonadopters.
Input use in crop cullivntion in lowlnncis
First-season rice cultivatiot~. Analysis of the first-season rice crop presents some
interesting results. The cost of agrocheniicals used was significantly higher for
nonadopters than adopters (Table 4). Although preharvest 1:ibor used was not
different between the two groups of farmers, adopters used less labor for nursery
and land preparation and Inore lrtbor for weeding. These differences can be
attributed to land preparation using ani111;ll power or tractors.

The yield of rice was significantly higher for adopters than for nonadopters,
and this higher yield was achieved at a lower total cost. Consequently, the net
income obtained from rice cultivation by the adopters was higher than the income
earned by nonadopters.
Second-season potato cultivatiorz. In the case of potato, mean levels of
preharvest labor used were significantly different and higher in nonadopters than in
adopters (Table 5). The amount of labor used by adopters for weeding and fertilizer
application indicated better weed control and better application of fertilizer. Potato
ylelds for nonadopters were higher and resulted in a hlgher gross income. The costs
of cultivation for nonadopters were higher than for adopters by a small margin.
Therefore, nonadopters earned a substantially higher net income from the potato
crop.
Third-season vegetable clrltivatiol7. Preharvest labor for the third-season
vegetable crop was similar for the two groups, except for a few crop-care operations
(Table 6). Adopters used higher amounts of labor for weeding, pest and disease
control, and harvesting. This may be related to their significantly higher yields.
Nonadopters spent significantly more on seeds; whereas, adopters spent more on
agrochemicals. Although the total cost of cultivation was higher in the adopter
group than in the nonadopter group, the adopters earned higher net returns from
their higher yields.
An overall comparison of input use indicates that adopters often use fewer
inputs and have managed to lessen their cost of culti\lation. Yield levels of adopters
were higher for two of the three crops grown, which indicated that the average
productivity of*the inputs was high. This led to higher g~oss and net returns for
adopters (except in potato production). Returns to capltal and returns to labor were
higher for adopters. This provided further proof that the adopters were able to use
their resources more efficiently (Table 7).
Technological changes
Production functions with several independent variables were estimated separately
for the three cro ping seasons. The estimated production functions for all three
crops were signi P icantly different (structurally) between the two groups of farmers.
This indicates that the production functions of all three crops had undergone
structural changes because of the impact of the FSR technology. In fact, only the
rice crop underwent a radical change; the old traditional rice varieties were replaced
with improved varieties. The changes in potato and vegetable production resulted
from a readjustment of the cropping system to the first change. This secondary
change had a negative effect on the productivity of potatoes and a positive effect on
the productivity of vegetables. Early planting of potato, which was a secondary
change, exposed the crop to heavy winds and to deficient moisture during the period
of tuber formation. Farmers suggested these reasons for the lower yields. For
vegetables, sufficient time was saved to allow for a longer duration and betterplanned
vegetable crop, which increased yields.

Production functions for first-season rice
For adopters and nonadopters, rice output was mainly determined by the area of
land cultivated (Table 8). However, when land area and Iabor were included, both
variables yielded coefficients \vith high standard errors. This was attributed to
rnulticollinearity. The coefficient of correlation between these variables was 0.75 for
adopters. To circumvent this situation, labor use per unit area was entered in the
subsequent analysis. This produced stable coefficients for both land and labor.
Nevertheless, the coefficient of the Iabor variable cannot be interpreted as the
production elasticity of labor.
Althougll use of preharvest Iabor per unit area contributed significantly to
rice output for nonadopters, it was not significant for adopters. The cost of fertilizer
contribured significantly at the level of 0.01 for adopters and 0.1 for nonadopters.
Production functions for second-season potato
The area of land cultivated and the cost of fertilizers per unit area contributed
significantly and positively to potato production (Table 9). As in the case of rice,
fertilizer cost per unit area was used to avoid multicollinearity. The correlation
coefficients between land area and fertilizer cost were 0.64 for adopters and 0.85 for
nonadopters. The negative sign of the statistically significant coefficient of dunlrny
variable 1 (with = 1; without = 0) in the production function for aclopters indicates
that the farmers in the with site were technically less efficient than the farmers in
the without site. This indicated that the farmers, who voluntarily used the
technology after having seen it, applied the technology more effectively than farnlers
who were made adopters by persuasion. This dummy variable did not show any
significant difference in the productivity of nonadopters, which is to be expected.
The significant coefficient of dummy variable 3 (continuo~ls irrigation = 1;
irrigation once in 2 yr = (1) in rhe production function of nonadopters showed that
farmers who received continuous irrigation every year did better than farmers who
received water once in 3 yr for the first-season rice crop. Dummy varirtble 3 is
nonsignificant, however, in the production function for adopters. This cou Id be due
to low variability of the dummy variable in the sample. Only one farmer did not
have irrigation facilities in this group. Therefore, lack of continuous irrigation may
be considered a constraint to the adoption of new technology.
Dummy variable 4 (owner operators = l; tenants = 0) had a significant and
negative coefficient for adopters, but a significant positive coefficient for
nonadopters. Hypotheses and empirical evidence suggest that tenant farmers
produce more to ensure they have a substantial portion of their produce left after
paying a share to the landlord. However, there is also evidence that owner-operators
perform better because they invest in their land over time for soil conservation.
Nevertheless, there is inadequate information available to explain the contrast in
the behavior of the dummy variable for tenancy in adopter and nonadopter groups.

Production functions for third-season vegetables
Land area mainly determined the output of third-season vegetables for adopters
(Table 10). Although the estimated coefficients for area of land cultivated,
preharvest labor/ha, and dummy variable 4 for the nonadopter group were not
significant at conventional levels of significance, they were larger than their standard
errors. (Note that labor/ha was used to avoid the multicollinearity problem). The
correlation coefficients between land area and labor were 0.58 for adopters and 0.55
for nonadopters. The significant parameter estimates of dummy variable 1 in the
production function for vegetables grown by nonadopters indicated that the farmers
who were adopters by persuasion were better than the farmers who voluntarily
adopted the technology.
Preharvest labor per unit area contributed significantly and positively, but
dummy variable 4 had a coefficient with a negative sign in the production function
of adopters. This significant parameter estimate of dummy v:iriable 4 indicated that
the production of vegetables by tenant farmers was more efficient than production
by owner-farmers. The tenancy arrangement was leasehold; therefore, it is possible
that leased lands were cultivated with better care and intensity to obtain yields that
were high enough to cover land rent.
Functional and personal income distribution
Factor-share analysis. It is assumed that each factor of production is paid its
marginal-value product; therefore, the expenditures on all primary factors reflect
the value these factors add to total production. If long-term equilibrium prevails, the
total payments to each factor plus the payments on current inputs would exhaust the
total value of production. Nevertheless, because these situations do not commonly
prevail, there is a difference between the total value of the product and the total
cost, i.e., the net income or profit. Because management cannot be easily separated
as a factor of production in rural agriculture, this difference really contains
payments to management and profit. Therefore, it is more appropriately called a
residual.
Payments to all primary factors, the residual (value added), and payments to
purchase current inputs show the functional or factor-income distribution. Because
payments to current inputs go to the sectors that produce, the value added accrues
to the factor owners in agriculture. Accordingly, the distribution of personal income
of the various factor owners is determined by the levels of use of their resources.
The personal income of peasant farmers in the current setting most probably
consists of the residual, payments for farm-family labor, and payments to farmer-
owned capital items. This analysis was conducted on these basic principles.
Factor sllure in first-season rice. Except for factor income of labor and
residual, there were no marked differences between adopter and nonadopter groups
of farmers (Table 11). Adopters used more family and exchange labor, which are
not paid for, and less hired labor. The nonadopters used more hired labor and less
family and exchange labor. The negative values of the residuals for both adopters

and nonadopters indicate that there were no profits and that there were losses from
rice alone. However, the (absolute) residual was higher for adopters than for
nonadopters, which implies that the adopters suffered srnaller losses.
Fr~ctor .rllrcrc in srcond-scrrrorz pottrto. Because pot2 to production requires a
larger expenditure on current inputs, v;llue added amounts to only 65% of the total
value of production for adopters and 60% for nonadopters (Table 12). This is rather
low compared \\,ith the percentage of value added in the other two crops. Payments
for labor in potato were relatively higher for adopters. Payments to other factors
were approximately equal. As a result, nonadopters received a higher share of value
added as residual than adopters, but there were no large differences.
Frrctor ~lrarc: irz tliird-srr~.~orz vegrtahle. The value of output is remarkably high
in the case of aclopters. Expenditures on current inputs in absolute terms were
higher u.ith adopters, but not to an extent cornniensur:tte with the productivity
differences. As a result, the value added in absolute terms was higher for adopters.
In proportional terms, the value added was 78547 for adapters and 77% for
nonadopters (Table 13). Percentage factor incomes for labor, capital, and land were
less for adopters, v. hich caused :l higher percentage residual than for nonadopters.
Nonadopters hired niore Iallor t1i:in adopters and used more family and exchange
Iabor.
Fuctor sllrnrcls for tlle atlt~irtrl tl~t~~?e-crop cycle. Factor-s11are analysis for the
whole year showed that there wits only a slight difference in the factor incomes
between adopters and nonadopters (Table 14). The :t~ialysis for individual crops
showed that adopters used more family and exchange Iabor and less hired Iabor;
nonadopters used more hired labor than family and exchange Inhor. This is one of
the major differences t11:it occurred after ndop tion of new FSR technology. After the
shares of income gained by different factors were netted, 4170 for aclopters and 42%
for nonsdopters \%!ere left as residuals.
Distribution of personal inconle
First-sclr~son ricr. Because of the high productivity attained without a large increase
in current input use, the production process for adopters resulted in a substantially
higher percentage of value added than for nonadopters (Table 11). Rice production
was not capitrll-intensive; therefore, only 6-796 of the total valt~e of production was
obtained by the capital owner for both groups of farmers. The l~trgest portion of
income (40%) was earned hy hired labor on nonadopters farms; whereas, the
portion was only 21% for adopters. As :I result of the use of higher amounts of
family and exchange labor by adopters, they received 70% of the total income
generated by rice production as income, while nonadopters only received 50%. The
remaining 30% of income generated by adopters and 50% generated by
nonadopters accrued to others, like hired Iaborerc and capit:iI owners.
Second-scnron potuto. In the case of pot;tto, only about 1% of income went to
the capital owner from adopters and nonadopters while the largest proportion of
income (48% by adopters and 53% by nonadopters) accrued to the farmers as

esiduals (Table 12). Ultimately, the income shares of farmers were 93% of the
value added for adopters and 90% for nonadopters. The farm income of adopters is
slightly less in absolute terms, although it is slightly more in terms of the proportion
of value added.
Tflird-season vegetable. Of the total value added in vegetable production,
proportional income earned by hired laborers, capital owner, land owner, and family
and exchanged labor were lower for adopters than nonadopters (Table 13). This led
to higher percentages of income as a resldual(58%), and ultimately, a higher
income share by the adopter farmers. In the production of vegetables, 90% of the
income generated by adopters and 78% of the income of nonadopters accrued as
personal income and only a small percentage was paid out. In absolute terms, the
Inconies accrued to various factor owners connected to the adopters were higher
because the value added for the same group is higher.
Annual three-crop cycle. The values added in the three-crop annual cycles
were very close in the two groups, with adopters having an additional SLR7,777/ha
(Table 14). This resulted from a cancellation of the positive gains in rice and
vegetable production by the negative gains in potato production. Only about 1-2%
of the value added went to the capital owners and 15% went to tlie land owners
from each group of farmers. Income from adopters to hired labor was 7% of value
added; whereas, family and exchange labor captured 12%. For nonadopters, 11%
went to hired Iabor and 8% to family and exchange labor. Except for proportions
accrued to tlie farm family as payments for family labor, there are no other salient
differences in distributions of personal income. Residuals that remained with the
farmers amounted to 42% for adopters and 41% for nonadopters. Ultimately,
adopters cry-ned a slightly higher percentage of value added (89%) as their personal
income froni the production of crops within a l-yr period. Nonadopters earned only
83 %.
The income of adopters froni rice production improved slightly as n result of
adopting tlie technology, but the effect was nullified by greater disadvantages to the
potato crop under the new farming system. The third crop of vegetables performed
well under the new system and managed to equalize (in fact exceed nonadopters by
a small margin) factor incon~es and personal incomes, with a slight reallocation of
the cost of labor in hvor of farmers.
\Velf;tre measures other than income
Elidowl?tent of fan71 ar.rcts. Changes in personal income can cause changes in tlie
endowment of farm and household assets. Table IS indicates that there were no
consistent differences in farm assets owned by the two groups of farmers. None of
the adopters owned two-wheeler tractors, but one of 18 nonadopters owned a two-
wheeler. Although 65 niammoties were owned by 19 adopters, only 13 were owned
by l8 nonadopters within the year under study. Milking cows were owned by 13
adopters, but only by 6 nonadopters. Storage boxes were owned by eight adopters
and by three nonadopters.

E~zdowr~tcnt of l~ouselrol~f assets. Of the household assets that \\.ere
considered, all adopters and 72% of nonadopters had radios (Table 16). More
nonadopters o\\lned television sets than adopters. None of the nonadopters owned
bicycles or motorbikes, but adopters did. A bus was owned by a nonadopter. There
was no definite pattern ofdifferences in ownership of household assets. These
findings are consistent with the marginally different personal incomes of adopters
and nonadopters.
hTzltritioti. Nutrition, which is one of the most important variables in
measuring social well-being, plays a major role in enhancing health conditions and
increasing the quality of labor. Calories and protein are the major components of a
balanced diet.
Each adopter consumed 2,126 cal/d; \\.hereas, each nonadopter consumed
2,080 cal/d. Per capita consumption of protein per d:~y was 55 g for adopters and
52 g for nonadopters. There \+.ere no significant differences in daily per capita
calorie consuniption or protein consumption between adopters and nonadopters. No
direct inipact of the technology on nutrition \\.;IS observecl.
E.vpcnriitiir.c ur~rf .rrr\linss. Expenditures on food by both categories of farniers
were very similar. Almost 40% of the total expenditure of adopters was spent on
food consumption; whereas, nonadopters spent nearly 33% of their total
expenditure 011 food (Table 17).
Adopters had higher average savings than non:ldopters, l~ut the difference
was not significant (Table 17). In the ahsence of any differe~ices in n~ltritional
intake, the expenclitures and s:~vings tally well with the niargin:ll income advantage
that farmers recei\.ed by adopting the new fClr~iiing sjJsterns technology.
Limitations of the study
The study, initiated in 1087-88, suffered :l break in d:itrl collection because of
unstable conditions in the countrv. Therefore, some issues pertaining to the stability
and sustainability of the te~Iiiiol6~~ could not be addressed. Howe\,er, the fact that
overall cropping intensities \{,ere high, which ensured high f:lrni incomes, indicates a
certain degree of stability o\.er time. The an;llysis of production functions for the
crops suffered from niulticolline:~rity. Therefore, input use per hectare had to be
used in some cases as a proxy for the theoretically perfect ir:put [Ice per far~ii. This
restricted the analysis to structural changes, but the cstirn;~tt.d coefficients could not
be interpreted as production elr~sticities of inputs, and the :lnalysis could not be
extended to determine returns to scale and factor shares. Therefore, the study of
factor and income shares was limited to an accounting analysis at the average level.
A more detailed analysis for above-average, average, and below-average farmers
would have been preferable, but could not be conducted bec:luse the samples were
limited to 19 adopters and 18 nonadopters.

CONCLUSION
o There appears to be a certain degree of success in the new farming
system because some farmers at a site where the farming system had not
been introduced, adopted the system after they observed its use.
o When the adopter and nonadopter groups were compared, many
practices were similar between the two groups. However, a major
difference was that adopters planted a 4.5-mo rice variety and 3 crops per
Y
o Production-function analysis of individual crops showed that the adoption
of the new technology caused structural changes in the production
processes of all three crops. However, this had a positive effect for
adopters only in rice and vegetables. Structural changes to potato
production after adoption indicated that there was a decrease in
productivity because of increased exposure to physiological stress.
o As a result of structural change, functional income distribution and value
added for all three crops changed. The most salient feature was that use
of family labor increased among adopters.
o The personal income distribution from each crop changed in favor of
adopters in rice and vegetable production and in favor of nonadopters in
potato production.
o When the three-crop annual cycle was considered as a system, there was
no significant difference in functional and personal income distribution
between the adopter and nonadopter groups. The positive effects on rice
and vegetable crops were canceled to a large extent by the negative
effects on potato cultivation.
o In the absence of income differences, changes in other related welfare
indicators (i.e.,, farm and household capital accumulation, nutritional
status, expenditures, and savings) were not observed.
o The farming systems technology introduced in Uva Paranagama did not
create an impact on the overall regional economy of Badulla and
Bandar:lwela. Consequently, there was no impact on the social welfare of
adopters during the relatively brief period after its adoption, although
there were stn~ctural changes observed in individual crop production
processes.
Of the original ol3jectives of the FSR program, only enhancement of the use
of family labor was achieved. During the introduction of the short-duration rice

variety, inadequate attention was paid to the possible negative effects on the
subsequent potato crop. The component teclinologies appear to have been
developed in isolation of the rest of the farm.
An important issue is whether research programs are adequately holistic to
encompass the probable ramification of an introduced technology on a rural
economy. How much disequilibrium and economic disarray can be caused by the
introduction of a certain innovation? It would be interesting to consider the effects
beyond the geographical limitations of the farm. The problems could be viewed in
the broader context of both farm and off-farm effects. This could lead to stronger
policy analysis in the context of the whole family farm.
REFERENCES CITED
Ministry of Agricultural Development and Research (1990) Agricultural
implementation programme: A working document. Sri Lanka.
Fernando G W E (1979) Sri Lanka cropping systems program. Report of Cropping
Systems Working Group Meeting, Nepal.
Hafi A A B, Ranaweera N F C (1990) Assessing productivity and household impact
of FSR/E in Uva Paranagama in Sri Lanka.
Herdt R W (1976) Costs and returns for rice production in Luzon. Paper presented
at the Conference on Economic Consecluences of New Rice Technology.
International Rice Research Institute, Los Barios, Laguna, Philippines.
Ranaweera N F C (1983) Case studies on impact of cropping production program
Sri Lanka. Paper presented at the International Rice Research Conference.
International Rice Research Institute, Los B:tfios, Philippines.
Ranaweera N F C, Siripala G D (1980). Assessment of the impact of the cropping
systems programme in Sri Lanka. In Report of Workshop on Cropping
Systems Research in Asia. 1nternation:tl Rice Research Institute, Los Baiios,
Philippines.
Sikurajapathy M S (1986) Systems approach to research and extension in Sri Lanka.
In Proceedings of the Farming Systems Research and Extension Workshop,
Sri Lanka.
Upasena S H (1981a) Progress report on cropping systems national programme in
Sri Lanka. Paper presented at the Cropping Systems Conference,
Bangladesh.

Upasena S H (1981b) Progress report, problems and future plans on cropping
systems project, Sri Lanka. Paper Presented at the 12th Cropping Systems
Working Group Meeting, Burma.

Table 1. Farming system research sites in Sri Lanka.
Locat ioll Zone Agroecological
region
1. Maha Illuppallama Dry zone, low country DL1
2. Makandura Intermediare zone. low ILl & IL3
counrry
3. Baiidara\vela Intermediate zone, up IU3
country
4. Kilinochchi Dr!. zone. low country DL3 & DL3
5. Karadian Aru Dry zone, low country D L2
6. Ansunakolapalessa Dry zone, low country DL1 & DL5
7. Galiiea~a Dry zone, lo\v country. DL 1
irrisated conditions
Table 2. Demo3rapIiic clinracteristics of adoprers and nonadopters.
-
Adoprers Nlnnadopters
Age of rhe farmer (years) 51 (23)l' 52 (3.5)
No cf !:ears of schooling (years) 3 (72) 7 (52)
Experience in farmins (years) 32 (11) 25 i51)
F:lmily size 6 (21) 6 (23;)
('~u~nhers in parentheses are coefficients 01' \.ariittion ( )
-

Table 3. Distribution of farmers by tenurial arrangement (1990).
Lowland
Adopter (%) Nonadopter (%)
Owner operator 42 (8) 44 (8)
Owner + other tenurial
arrangements
Other tenurial
arrangements only
Highland
Owner operator
Owner + other tenurial
arrangements
Other tenurial
arrangements
Note: Figures in parentheses refer to number reporting.

Table 4. Comparison of levels of inputs and outputs and the crop budget for the first rice crop
of adopters and nonadopters.
Inputs
seeda
Fertilizer cost
Agrochemical cost 0
Other costs
~abor~
Nursery preparation
Land preparation
Planting
Weeding
Fertilizin:
Pest and disease control
Water management
Hal-\.resting
Hauling to threshing floor
Threshing and wiru~owing
(Total labor)
Yield (kgld
Total cost'
Gross income"
Net income"
Adopter Nonadopter
Physical Values Physical Values
quantitieslha SLRIha quailtitieslha SLRIha
days
8.0
66.3
43.1
31.3
2.8
0.8
25.4
42.7
31.3
25.3
(267.0)
3.860
days
15.4
84.4
44.4
17.3
1.4
0.6
19.6
41.5
23.6
25.4
(276.6)
3,508
"seed price of rice SLR7.18lkg. b~ipnifican
at IOW level "Labor cost SLR6Oiday.
'significant at 15 70 level. 'Co~nputed horn samplc means and not tested for statistical
significance of differences.
*
*Pp
.v

Table 5. Comparison of levels of inputs and output and the crop budget for the second-season
potato crop of adopters and nonadopters.
-
Variable Adopter Nonadopter
Inputs
Seed costa
Fertilizer cost
Agrochemical cost b
Other costs
~abor'
Land preparation
Planting
Weeding
Fertilizing
Pest and disease control
Other operations
Harvesting
(Total labor)' '
Yield (kg)
Total costd
Gross income d
Net income d
Physical Values Physical Values
quantitieslha SLWha quantitieslha SLWHa
days
112.1
19.8
59.7
12.9
10.9
21.2
39.4
(276.1)
7,757
days
145.2
28.3
29.8
8.2
13.9
33.2
46.9
(305.5)
9,981
?rice of seed potato SLR50.00lkg. b~ignificant
at 1 % level. '~abor cost SLR60.00lday.
Computed from sample means and not tested for statistical significance of differences.

Table-6. Compariso~i of le\.els of inputs and outputs and the crop budget for the third-season
i.egetable crop of adopters and nonadopters.
Variable Adopter Nonadopter
Physical Values Physical Values
Quantitieslha SLRIha Quantitieslha SLRIha
Inputs
Seed cost"
Fertilizer cost
Agrochemical cost 0
Other costs
LaborC days days
Land prsparatio~i 81.9 1,916 78.4 4,705
Planting 15.9 956 16.4 986
Weedins 45.5 2,728 32.7 1,964
Fertilizing 8.4 506 6.1 383
Pest and disease control 19.0 9.0 537.0
Other operations 31.3 2,060 28.9 1,735
Harvesting 63.7 3,824 40.9 2,452
(Total labor) (968.6) (16,123) (212.7) (12,762)
Total costd 35.156 26,651
Gross income'^^ 80,557 49,698
Net iiicolne (sLRI~~)'~ 45.401 23,044
p-- -
"Significant at 5% level. '~i~~~ificnl~t at 108 level '~abor cost SLR60.00id d~omputed
from sample means and not tesred for statistical significance of differences, e~ignificant at
15% level.

Table 7. Returns to capital and labor for adopters and nonadopters.
Rice
Potato
Returns to capital Returns to labor
Adopter Nonadopter Adopter Nonadopter
Vegetable 2.3 1.5 168 108
Annual three-crop
cycle 1.8 1.5 168 161
Table 8. Estimated production functions for rice of adopters and
nonadopters.
Independent
variable
- -
Constant 6.029**+*
(5.52)
LAREA
LLB
LFRT
Adopt er Nonadopter
Notes: l. Dependent variable is the production (kg) of rice per farm.
2. Figures in parentheses are t-values of the estimated
coefficients.
3, "*** significant at l % level; *** significant at 5% level; **
significant at 10% level; and * significant at 15 % level.
4. Definition of independent variables: LAREA = log value of
land area in hectares; LLB = log value of days of prel~arvest
labor per hectare; and LFRT = log value of total fertilizer
cost in SLR.
5. F-value of the chow test is 5.9****.

Table 9. Estimated production functions for potato of adopters and nonadopters.
Independent
variable
Constant
LAREA
LFR
Dummy 1
Dummy 4 -0.514"
(-1.633)
= 0.62
Adopter Nonadopter
Notes: 1. The dependent variable is the potato production (kg) per farm.
2. Figures in Parenthesis are t-values of the estimated coefficients.
3. ****Significant at 1 % level; *** significant at 5% level; "*
significant at 10% level; and * significant at l5 % level.
4. Definitions of independent variables: LAREA = log value of land
area in hectares; LFR = log value of total fertilizer cost per hectal-e
in SLR; Dunlmy 1 = with site = 1; without site = 0: Dunlmy 3 =
irrigation once in 2 years = 0; continuous irrigation = 1; and
Dummy 4 = owner operator = 1; tenant = 0.
5. F-value of the chow test is 3.41***.
m,

Table 10. Estimated production functions for vegetable of adopters
and nonadopters.
Independent
variable
Constant
LAREA
LLB
Dummy 1
Dummy 4 -1.262***
(-2.26)
R2 = 0.60
Adopter Nonadopter
F = 5.03
Notes: i. Dependent variable is the yield value (SLR) per farm.
2. Figures in parentheses are t-values of the estimated
coefficients.
3. ****significant at 1 % level; *** significant at 5% level;
** significant at 10% level; and * significant at 15% level.
4. Definitions of independent variables: LAREA = log value
of area in hectares; LLB = log value of days of preharvest
labor per hectare; Dummy 1 = with site = 1; without site
= 0; and Duminy 4 = owner operator = 1; tenant = 0
5. F-value of the chow test is 3.39***.

Table 11. Factor shares of first-season rice for adopters and nonadopters.
Adopter Nonadopter Adopter Nonadopter
Variable (SLRIha) (SLRIha) (%) (%)
Ourput
Current inputs
Value added
All labor
Capital
Famill. + exchange
labor
Hired labor
Land
Residual
Farmers incomea
"Farmers income = income of landowners and family exchange laborers' income
and residual.

Table 12. Factor shares of second-season potato for adopters and nonadopters.
Variable
Output 152,724
Current inputs 53,100
Value added 99,624
All labor 16.561
Family + exchange
labor 10,222
Hired labor 6.339
Capital 872
Land 9,160
Residual 73,03 1
Farmers income 92,448
Adopter Nonadopter Adopter Nonadopter
(SLRIha) (SLRIha) (%l (%)

Table 13. Factor slirlres of third-season vegetables for adopters and nonadopters.
Variable
Output
Current inputs
Value added
All labor
Family + exchange
labos
Hired labor
Capital
Land
Residual
F~1-mers incoine
Adopter Nonadopter Adopter Nonadopter
(SLRIha) (SLRIha) (70) C%)

Table 14. Factor shares for the annual three-crop cycle of adopters and nonadopters.
Adopter Nonadopter Adopter Nonadopter
Variable (S LR/ ha) (S LRIha) (%) (%)
Output 260,982
Current inputs 72,591
Value added 188,391
All labor 48,707
Family + exchange
labor 3 1,064
Hired labor 17,640
Capital 3,715
Land 27,480
Residual 108,490
Farmers income 167,100

Table 15. Endownlent of farm assets of adopters and nonadopters.
T\i.o-wheel tractors
Plows
Sprayers
Water pumps
Rotary weeders
Mammoties
Milking cows
Storage boxes
Adopter
(n = 19)
Note: Fizures in parentheses refer to number reporting
Nonadopter
(n = 18)
Table 16. Household assets owned by adopters and nonadopters.
Televisions
Radios
Sewing machines
Bicycles
Motorbikes
Buses
Adoptes Nonadopter
(n = 19) (n = 18)
Note: Figures in parentheses refer to number reporting.

Table 17. Expenditures and savings of adopters and nonadopters
Farm expenses (cash) 16,526
Household expenses (17,984)
Total expenses
Savings
Expenditures on food 11,782
Other expenses
Adopter Nonadopter

IAIPACT ASSESShlEhT OF FARMING SYSTEMS RESEARCH AND
DEVELOPMENT AT THE FARM LEVEL: THE RICE - WATERMELON
CROPPING SYSTEhl IN PANGIL, LACUNA
V. T. ~illanciol, C. H. hlanalol, Al. L. ~ebulanan'
A. A. ~ris~ado', F. L. ~atienzo', and N. F. C. Ranaweera 2
The research site, situated in the municipality of Pangil, province of Laguna, was
part of a network of sites where technology verification trials and Barangay Pilot
Production Programs (BPPP) were implemented. This cropping systems work was
undertaken by the Regional Integrated Agricultural Research Systems (RIARS) of
the Department of Agriculture (DA). The Pangil site represented rice-based
cropping s!.stems under r:linfed conditions in Laguna.
The RIARS activities in Pangil started in 1983 and addressed the rice-based
and coconut-based farming systems in the area. Initial activities were conducted in
barangays (villages) Isla and Balian where there were three rice-based
environments: rainfed, irrigated, and seasonally inundated areas. The rainfed areas
are located in Isla and a part of Balian; whereas, the irrigated and seasonally
inundated areas were confined to Balian.
A rice - watermelon cropping system (RWCS) \\,as tested in the rainfed
areas, a rice - rice cropping pattern in the irrigated areas, and a deepwater rice - rice
cropping pattern in the seasonally inundated areas. Cropping systems trials on
coconut + citrus followed in 1981.
The RWCS was not very successful in Isla for 2 yr (1953-85) presumably
because of heavy rainfall during the critical stages of \\.atermelon cultivation,
especially during the fruiting stage. Six cooperators were selected for the initial
cropping systems study. Results showed a favorable performance of the RCWS
during the trial period (1986-85). In 1989, BPPP was launched to involve 28 farmers
on an aggregate area of 29 ha.
SITE DESCRIPTION
Dambo is a village in the eastern region of Pangil, Laguna. The village is about 1.1
km from the town and is accessible by a provincial road. Dambo consisted of 198
households and had a total population of 1,015 in 1989. The total land area was
armi in^ Systems and Soil Resources Institute, College of Agriculture, University of
the Philippines Los Bafios, Laguna, Philippines.
2~ocial Sciences Division, International Rice Research Institute, P.O. Box 933,
Manila, Philippines.
*

about 1,050 ha. Coconut occupied 46% of the area, and rice was planted on 38% of
the land. The rest of the area was under pasture, forest, grassland, and farms
planted with fruits (e.g., banana, lanzones, and citrus).
The wet season (WS) is from June to November and the dry season (DS)
from February to May. There are basically four land types that are characterized by
differences in land form, soil type, water regime, and cropping systems. Along
Laguna Lake is a seasonally inundated area called hot. This floodprone area has a
clay soil with a slope of 0-2%. During the WS, grass (locally known as tikiw) and
water lilies predominate. Rice is grown only in the DS.
The up er area of the lake site (called tuhigul~) has a slope of about 0-2%
and consists o p matala-tala clay soil. This is usually planted to rice - fallow, rice -
rice, and RWCS.
The upper region of the village has two distinct land types. The village is
located in a narrow strip of relatively flat (about 5% slope) area planted with
coconut and other fruit trees. The kaingin, which has a slope of about 25-65%, is
slightly eroded. This area is planted with coconut and citrus and has patches of
shrubs and grasslands.
The total rainfed rice area is about 400 ha. During the impact assessment
study, a large portion was planted with rice during the WS and left fallow during the
DS. In 1989,gthe RWCS was practiced on about 27 ha. The Laot area was confined
to a fallow - rice cropping system.
Coconut cultivation occupies a large area but, compared with rice
production, it is given little attention by farmers. Some farmers practice
intercropping with banana and fruit trees (e.g., lanzones and citrus). Shifting
cultivation is practiced in the kningin. Farmers plant root crops and vegetables in
this area.
Because the village is located along the lake, fishing is an iniportant activity.
Sniall-scale swine and poultry raising are the most common animal enterprises.
Handicrafts are the prime income-generating activity of women. Other nonfarm
income sources include jeepney driving, trading, logging, and carpentry.
THE RICE - WATERMELON CROPPING SYSTEM
The RWCS had been tested at Dambo since 1986. The favorable performance of
the technology was reflected in increased yields and economic returns during the
2 yr of experimentation. The first rice crop of RWCS was grown during June-July.

Depending on the adequacy of rainfall, land preparation could be done as early as
May. Seedlings were grown using the modified wet-bed method (dalakduk) as early
as May to early June. Pregerminated seeds were sown on the seed bed at a thicker
rate. Seedlings were not uprooted. Instead, the existing practice of Il~plup (cutting
the seedlings in the form of turf) was used.
The recommended seeding rate for high-yielding varieties (e.g., BPI-RI 10
and IR62) was 75 kg/ha. Fertilization for rice was at the rate of 45-60-60 kg of
NPK/ha. Insect control was recommended only when the economic threshold level
was reached. The first rice crop was usually harvested in October-November.
Dzcember is a rainy month; therefore, watermelon is not planted
immediately after the rice crop is harvested. Farmers must wait until January to
plant watermelon. Sugar Baby is the preferred variety. No elaborate lrmd
preparation is done to cultivate waternielon. The recommended seeding rate is
1 kg/ha spaced at 1.5 m along rows.
A basal fertilizer (14-14-14) is applied at the rate of about 25 g/hill, and 1
liter of poultry manure is used. A solution that contained 1 liter of urea for every 20
liter of water was used for 12 to 16-d-old seedlings. The rate was gradually increased
to 1 liter of urea, 2 liters of 14-14-14, and 0.5 liter of 0-0-60 mixed with 20 liter of
water for 57 to 62-d-old plants. Watering was done daily. Insecticide was applied
about 5 times during the growth period. Handweeding was done 1 nlo after planting.
The first fruit was pruned and the next 2-3 fruit sets w.ere allowed to continue.
hlelons \\.ere harvested in late March or April.
METHODOLOGY
Several data collection methods were used in this study: collection of secondary data
from published and unpublished sources; hrm surveys; record keeping; case studies;
and key-informant surveys. Data collected from secondary sources were those
related to the characteristics of the site, the management recluirements, and the
performance of the R\VCS.
Descriptive survey
A survey of the rice-based cropping system was conducted in Dnrnbn, Pangil, in May
1989. A list of farmers was provided by the agricult~iral technician and village
officials. Fifty-one respondents were identified ancl intervie~ved. Farmers who
adopted the RWCS were classified as adopters (26 farmers) and the rest (25
farmers) were classified as nonadopters. Interviews were conducted using structured
questionnaires designed to obtain information on existing farming systems,
resources, problems, and constraints.

A comparative description of the two groups was made on their basic
characteristics, resources, farming systems, perceptions, problems, and constraints.
Direct observation in the field was employed on parameters that would describe the
standard of living (e.g., the quality of housing and the availability and accessibility of
community facilities).
Case study
The sunrey results were used to select the 10 farmers who will participate in the
study. Five were adopters of the RWCS and the other five were nonadopters.
Data collection was done by requesting the farmer-participants to record
their weekly farm and household activities. Monitoring forms were provided. These
were collected every Tuesday. During the collection of forms, interviews with
housewives or other members of the family were conducted to gather and clarify
information that were not properly recorded. The form was usually maintained by
the housewife.
The minimum data collected for the case study were biophysical and
socioecono~nic characteristics, cash and noncash transactions, household and
nonfarm related activities, a diary of events that included reports on the state of
farm enterprises and problems with farm management, and other information
derived from direct field observation.
The weekly monitoring forms were edited and coded. At the end of every
cropping seasbn, the farmers' crop production was summarized to assess the
performance of the crop components and the cro ping systems. A resourceassimilation
matrix was prepared to indicate the 1 ow of resources from one activity
to another. For exa~nple, income derived from the cultivation of watermelon was
spent on watermelon cultivation as well as on rice and livestock production. The
information in the resource-assimilation matrix was plotted in a resource-flow
diagram. This diagram reflected the extent of financial integration that took place
between activities.
Cash-flow analysis was aggregated on a monthly basis. Cash inflow and cash
outflow were categorized according to farm and nonfarm activities to examine the
role of RWCS. Household expenditure was considered as a nonfarm expense.
Descriptive survey
RESULTS AND DISCUSSION
The major objective of the descriptive survey was to determine the degree of
adoption of the RWCS introduced by the DA-RIARS at Dambo. The RWCS was an
improvement on the existing rice - fallow cropping system.

Demograpllic cllaractehtics. The comparative study of the adopters and the
nonadopters showed there were no significant differences in their general
demographic characteristics. The average age of farmers was 46 yr, and they had 6
yr of formal schooling. Farm households had an average of 6 members. The average
size of rice farms in the area was 1.4 ha. The farms of adopters were 0.6 ha larger
than the farms of nonadopters.
Fanning systems. Aside from the existing rice-based farming systems, some
farmers practiced hilly land and coconut-based farming systems. Hilly land
cultivation included perennial crops (e.g., coffee, citrus, banana, and other fruit).
Other important cropping systems practiced by the farmers were coconut
intercropped with citrus, coffee, and vegetables. Of the 26 adopters, 61% practiced
pure rice-based farming systems, 31% had a combination of rice-based and hilly
land systems, and 8% had rice-based and coconut-based farnis. Adopters had more
diversified farnis than nonadopters.
Source of lahor aild po~~r. Labor for crop production was provided by the
farmer, family members, and hired and exchange laborers. Most of the farm
operations (e.g., fertilizer and insecticide application) were carried out by the
farmer but activities such as planting and harvesting were mostly performed by
family members. Lnbor for land preparation was usually hired.
Hired labor and machinery were important resources in the community.
Generally, farmers used small power tillers for land preparation. Only 37% of the
respondents owned draft animals. For watermelon production, hired or contract
Iabor was the most common source of labor.
The wage rate for hired labor varied according to the type of farm operation.
The wage rate for land preparation using draft animals was P50/d. Hand tractors
were rented at P700/ha.
The inadequate number of tractors was identified as one of the farmers'
constraints to rice farming. Only three tractors were available for rent. These were
rented only when the tractor owners had completed their own land preparation.
This affected the timely establisliment of crops.
Source of capital. Local credit facilities were the most important sources of
capital in the area. About 72% of the farmers were dependent on informal sources
of credit; whereas, 18% derived capital from forms1 sources. Adopters used the
formal sources of credit because large amounts of capital were required for the
watermelon enterprise. The rural bank was the only source of formal credit of
adopters, but it was the least important source for nonadopters. Furthermore, the
adopters had a viable farm enterprise, which enabled them to pay for their loans.
On the other hand, the nonadopters often obtained zero-interest loans from their
relatives. Other credit sources were friends, other farmers, and private money
lenders. Some farmers did not obtain 1o:lns for fear of not being able to repay. Only

25% of the farmers generated savings from crop production. Earnings from
livestock production were a common source of income among adopters.
Production costs and incorne fro171 rice-based cropping glstem. The average
cash expenditure in rice production during the first crop was P4,048/ha (Table 1).
The highest capital outlay was spent on hired labor for both adopters (57%) and
nonadopters (62%). Expenditures on fertilizer and seeds were relatively high. Other
expenses included hauling fees, insecticides, and herbicides.
The average cost of watermelon production was P5,480/ha (Table 2).
Fertilizer cost accounted for 43% of the total production cost, hired labor for 28%,
and insecticides for 23%. Contract buyers bore the cost of harvesting, hauling, and
transportation. Net returns were shared equally between the owner and the labor-
contractor. The labor-contractor was given a cash advance that was deductible from
the sale of the produce.
The net income of the RWCS adopters was P33,036 while nonadopters
gained P17,113 only (Table 3). Not all farmers could adopt the transplanted rice -
watermelon cropping pattern because of its high capital requirement. Therefore,
credit facilities and financial support programs are important components of the
project.
Housetrold inconze and expenses. Income from on-farm, off-farm, and
nonfarm activities were the major sources of capital for crop production. However,
in most cases, the farmers could not meet the financial requirement of the
technology. Rice and watermelon were the two major crops that provided income
and capital for household and farming activities. Income from coconut and hilly land
cultivation also contributed to overall income.
Fishing was a major source of income for 46% of the adopters and 52% of
the nonadopters. Other nonfarm activities included hog raising, tricycle driving,
"sari-sari" store operation, coconut selling, rattan furniture manufacturing,
carpentry, hiring out of labor, renting out hand tractors, and cottage industries.
In terms of average monthly household expenditures, the adopters spent 16%
more than the nonadopters. The estimated household expenses of adopters was
P4,305; whereas, nonadopters S ent P3,620. The highest expenditure for both types
of farmers was on food (40%), P ollowed by education of children (20%).
Fann and housetiold assets.The adopters had more assets than nonadopters.
About 35% of the adopters owned residential lands compared with only 16% of the
nonadopters. Regardless of their categories, all farmers had appliances (e.g.,
refrigerators, radio cassettes, television sets, video recorders, stereo, sewing
machines, and electric fans). One adopter owned a tricycle.

The major farm implements owned by the farmers were plows and harrows.
More adopters owned farm assets and draft animals. However, two of the three
hand tractors available in the area belonged to nonadopters. In general, adopters
were financially more stable than nonadopters.
Case study of farm households
A case study of 10 farms was conducted to determine the impact of the rice -
watermelon technology. The study focused on crop production and patterns of
household income and expenditure. Selected demographic characteristics of the
farmers are. presented in Table 4.
Fanuing.~~.~tcnzs. Among tlie farmers involved in the case study, adopters
appeared to have cultivated more plots than nonadopters. The average farm size of
the adopters (6.9 ha) was larger than the farms of nonadopters (1.7 ha). The farming
systems practiced by the adopters were more diversified than those practiced by
nonadopters. The adopters used both rice and coconut-based farming systems
(Table 5). The nonadopters primarily used rice-based farming systems.
In 1989-90, adopters of rice - \ipatermelon used 8-7894 of their land for this
system and the rice - rice cropping pattern on 20-50% of their land (Table 6). Most
of the area devoted to rice-based farming systems by nonadopters was planted with
the rice - rice cropping pattern (54-100%). Six farniers planted fallow - rice in hot.
In 1990-91, almost all of the rice-based farming area was planted using the rice - rice
cropping pattern. The only exception was a 3.0-ha plot planted with fallow - rice by
one farmer in Laot. After the irrigation system becr~rne operr~tional in the early part
of 1991, farmers planted rice instead of watermelon as the second crop.
In 1989-90, the average area planted to R\VCS among the ~~dopters was
0.65 ha; whereas 0.75 ha was devoted to the rice - rice and 1.20 ha was planted to
fallow - rice. Nonadopters had an average area of 0.79 ha under the rice - rice
cropping system. Three of the nonadopters implemented the fallow - rice pattern on
an average of
0.3 ha.
The period of adoption of the technology varied among RWCS adopters.
One farmer had been using this cropping pattern since the first experiment in 1987.
Two others had been planting RWCS since 1988 while another started in 1989. One
nonadopter implemented the rice - waternielon cropping pattern during the study.

Performance of RFYCS compared with rice-based cropping systems
In 1989-90, the study farmers planted 4 rice-based cropping patterns (i.e., RWCS,
rice - rice, rice - fallow, and fallow - rice). However, in 1990-91, the only cropping
patterns used were rice - rice and fallow - rice. The change in cropping pattern was a
result of the restoration of the irrigation system during the later part of the second
crop.
The adopters planted a larger area to rice-based cropping systems than the
nonadopters. In 1990-91, adopters planted the rice - rice cropping pattern on an
average of 2 ha; the nonadopters allocated 1 ha. However, in 1989-90, nonadopters
planted a larger area to the rice - rice cropping pattern than the adopters (Table 7).
On average, adopters obtained higher yields of rice and higher net returns than
nonadopters. The nonadopters had higher input costs primarily because they had to
pay rent for the land.
The costs (up to P3 1,353/ha) associated with waternlelon were purchased
labor and material inputs. Contract labor wages varied depending on the net returns
from the production of watermelon. The labor-contractor was paid 50% of net
returns.
In 1990-91, only two farmers practiced the fallow - rice cropping system in
Laot. They gained a return above variable cost (RAVC) of P22,333.
Contribution of R\VCS to household income and expenditures
The adopters appeared to have more diverse sources of income. They posted a
higher income from both farm and nonfarm sources. Farm income was derived
mainly from the sales of rice, watermelon, coconut, and livestock. It contributed
about 37-88% to the household income of adopters and 3549% for nonadopters in
1990. The cultivation of watermelon contributed at least 21% to the household
income of adopters and rice sales contributed a maximum of 37% (Table 8).
Nonadopters apparently depended on the sale of rice, coconut, livestocl

Effect of RWCS on household cash flow
Monthly cash-flow analysis included the farm and nonfarm economic activities of
the household. Positive net cash flows were observed for all adopters except one,
whereas, nonadopters had negative net cash flows.
The favorable net cash flows of the adopters was attributed to the income
gained from the production of watermelon. An improvement in the cash inflow was
observed during April 1990 from the sale of watermelon and in November 1990
because of the high yield of rice.
The case of Ka Arturo
To illustrate the adoption of the RWCS and its impact on the pattern of resource
transfer among farm enterprises, the case of Ka Arturo was selected. He planted
0.60 ha using the RWCS in 1959-90. From this cropping pattern, he harvested 1.6 t
of rice (value P7,200) and 5.8 t of watermelon (P32,000). The value of production
from the RWCS represented about 40% of the total value of his farm produce.
In 1990, he earned approximately P20,000 from rice sales. About 44% of the
gross receipt was spent on household requirements, 20% on the production of rice,
and 20% on livestock production. About P400 were spent on watermelon
production. The expenditure on the production of watermelon included the share
paid to the labor-contractor. Income from sales of watermelon was distributed as
27% for household expenditure, 71% for watern~elon production, and the rest for
livestock production.
At the whole-farm level, Ka Arturo had diverse sources of income. Sale of
crops and livestock appeared to be the dominant source. Children contributed about
7% to the total household income. Proceeds from his informal credit financed about
20% of his household expenditure.
This case suggests that the integration of watermelon cultivrltion in the
farming system contributed enormously to overall resource use, income, and
expenditure of the household. However, it appears that watermelon can only be a
second alternative crop to rice. When conditions became favorable for rice, priority
was given to the cultivation of a second crop of rice.

CONCLUSION
The farmers in Pangil did not adopt the RWCS technology. They adopted
watermelon as an alternative to rice during the DS. When there was adequate
rainfall, they substituted rice for watermelon. Although the adopters practiced the
RWCS technology, almost all cultural practices and the management involved were
carried out by a labor-contractor who had experience in watermelon production.
The results suggest that the RWCS improved farm income. When the
adopters phased out the production of watermelon in 1991, there was an apparent
reduction in income. Farmers, however, were able to compensate for the losses
through other sources. One of the farmers focused his effort on rice production and
cultivated a larger area to make up for the loss of income from watermelon. This is
most likely to happen if farmers have large farms. However, if farm size is a limiting
factor, farmers will be inclined to plant watermelon after rice.
The impact of watermelon production on income and expenditure patterns
cannot be generalized. The case study revealed that income from the sale of
watermelon was not necessarily reinvested in farm enterprises, but was spent on
unproductive household items. The case study also revealed that farmers had other
sources that could be used to augment their income if watermelon was not included
in the farming system.
Rice remained a stable component of the farming system with or without the
irrigation system. Citrus, however, has the potential to increase income. The RWCS
is a very promising alternative only while the irrigation system is not operating.
The experience in Dambo has implications for future development.
Agricultural research should not merely focus on cropping systems work or deal only
with rainfed agriculture. Research must focus on finding ways to integrate water
management into the system. In Dambo, for example, years of cropping systems
research could be wasted because of the presence of an irrigation system.
Consequently, farmers in the rainfed areas will pay more attention to the provision
of the required water and will spend excessively on water-resource facilities. This
situation has been experienced by farmers in the KABSAKA project where
investments in costly water pumps have been made to guarantee adequate water
supply. The money spent on these facilities could have been invested in a much
more profitable venture. Therefore, it is vital to establish cropping systems that will
use limited water resources in the rainfed areas while providing reasonable income.

Table 1. Average cash expenses per hectare for rice production by type of farmer, first
crop, 5 1 farmers, Dambo, Pangil, Laguna, Philippines (1989).
Type of farm
Adopters Nonadopters All farmers
Value % Value % Value %
Hired labor 2,281 57 2,544 6 2 2,413 60
Fertilizer 5 84 15 469 11 5 27 13
Insecticide 23 3 6 303 7 268 7
Herbicide 132 3 192 5 162 4
Seeds 525 13 46 1 11 493 12
Hauling fee 22 1 6 150 4 186 4
Total 3,976 100 4,119 100 4,048 100
Table 2. Average cash expenses of 25 adopters per hectare
for watermelon production. Dambo, Pangil, Philippines (1989).
Hired labora 1,556
Fertilizer 2,340
Insecticide 1,273
Planting material 311
Total 5,480
Value (P) Percentage
a~ired
laborers were paid on a monthly basis. Activities
included crop establishment, fertilizer and insecticide
application, cultivation, and watering of plants. Hauling
and harvesting costs were shouldered by the contract buyers.

Table 3. Average net income per hectare by type of farmers, 5 1 farmers, Dambo,
Pangil, Laguna, Philippines (1989).
Adopters Nonadopters
1st 2nd Total 1st Total
crop crop crop crop
rice watermelon rice
Total yield (t) 4.8 3.94 4.3 4.3
Average price
4,250 5,596 4,940 4,940
Total income 20,43 1 22,050 42,48 1 21,232 2 1,232
Total costs 3,976 5,469 9,445 4,113 4,119
Net income 16,455 16,581 33,036 17,113 17,113
Table 4. Selected demographic characteristics of 12 farmers used in the case study of
farm household, Dambo, Pangil, Laguna, Philippines (1991).
Farmer Age Residence Farming Educational Household
number (Y r) (Y r) (Y r) background size
Grade V1
High School
3rd year HS
Grade V1
2nd year HS
High School
High School
Grade I11
Grade V1
Grade IV
High School
Elementary
'Farmers 10, 11 and 12 took turns in farming the 10th case study farm during the
period of the study.

Table 5. Selected clia~~acteristics of 10 case-study farms. Dambo, Pangil. Laguna.
Pliilippines.
Farmer No. or No. of Total fal-m Percentage of area planted
nuii~ber pa see l plots area
(113) RBFs" CBFS~ Others
ice-bad Pal-min, tr . y. stems.
b~ocnliu~-hased f.lstning s!xstems.
'~a~itan .4co also se~\~ed as caretakes for a 35-ha coconut plantation.

Table 6. Percentage of area under various rice-based cropping systems planted by 10
case-study farmers, Dambo, Pangil, Laguna, Philippines (1989-90).
Farmer Total area Percentage of area planted
number in RBFS RWCS Rice - rice Fallow - rice rice - fallow
(ha)

Table 7. Comparative pcrforinance of various rice-bascd cropping sysleins by calegory of 10 case-study farmers, Dambo, Pangil, Laguna,
Philippines (1989-91).
Croplcropping Avei-agc Value of Total lictur~l above Average Value of Total Return above
pattern area production variable variable area production variable variable
planted cost cost planted cost cost
Rice - fallow
Fallow - rice
Rice - rice
l st crop
2nd crop
Rice - wateilnelon
l st crop
N
P 2nd crop
0
1990-1991
Fallow - rice
Rice - rice
1st crop
2nd crop
a~ncrease In area due to a parcel acquired by one fanner during the second crop.

Table 8. Percentage contribution of rice and watermelon to household income of nine
case-study farmers, Dambo, Pangil, Laguna (1990).
Farmer Total household
~iumbee income Farm income Rice Watermelon
reported (70) (%l
aFal-mer 10, l1 and 12 were not included in this table.

hiem bers
Discussion and Recommendations
Group 1: Methodology
R. Shand - Sri Lanka (convenor); R. Islam - Bangladesh; C. Barba - Philippines;
V. Villancio - Philippines; M. Ahmed - ICLARM; J. Graham - IDRC;
D. M. Ramiaramanana - Madagascar; R. Gonzaga - Philippines; P. A. Samaratunga
- Sri Lanka; and G. K. Renuka - Sri Lanka.
This group reviewed the lessons learned about methodology to suggest guidelines
for future impact studies. The group agreed that the formulation and application
of FSR impact methodology was readily distiriguishable from its predecessor, i.e.,
comporient research with a systems perspective. The former included a range of
impact variables. The challenge of developing a suitable methodology was raised
frequently during the discussioris. The attempt at a comprehensive measurement
of all impact variables was made in only one of the studies (Sri Lanka).
Setting objectives
In this project, seven objectives were agreed on at the initial workshop. Teams
represented in the discussion group were unanimous in the view that attaining their
targets, although a laudable objective, was far too ambitious, at least within the
structure of the project.
A major reason was that, although the measurernent of impact was to focus
on income levels and variables influenced by changes in income levels rather than
on adoption, accurate measurement of adoption levels of the new technologies was
a necessary precursor to further analysis. Adoption measurement not only absorbed
time and resources but, in many cases, produced problems because there was no
single or even several methodologies for this measurement. This had an impact on
three studies in particular, but was a concern for all.
Guideline 1: Do not set objectives for an FSR impact study on the assumptiori
that a satisfactory location-specific methodolojg exists for mensu ring technology
adoption.
This particular issue was instrumental in reducing the number of objectives that the
teams attempted to achieve. There was full agreement on the basic need to
measure the impact of technological change on productivity and income, but there

was considerable doubt cast, in the absence of any evidence, that resultant income
changes would have a significant impact on the income-dependent variables
originally listed. This was argued on the basis that there was a wide range of other
variables, both short- and long-term, that might frequently relegate the indirect
influence of technological change to an insignificant role. This was not suggested as
an excuse for not attempting these tests. Rather, it was felt that the study of the
interrelationships between income changes with technology and these other
variables was complex and would be a study in itself. It was generally agreed that a
study such as the present one might best be restricted to impact on income levels
and distribution. This should not dampen enthusiasm toward broader aims.
Guideline 2: Objectives should be achievable within the normal limits of time and
project resources.
To achieve all of the original objectives, the projects would have to be expanded in
time, finances, and team size. It might be preferable to confine this type of study to
a single site on a pilot basis to enable methodological alternatives to be tested.
Formulating hypotheses
The discussion on the need to formulate explicit hypotheses for FSR impact studies
was lively. Some argued that setting objectives was sufficient; others argued that
they were implicit in their studies; others said that the objectives were hypotheses.
There was also a view that if hypotheses were established and subsequently rejected
by the analysis, then the studies would lose value. Contrary arguments were put
forward that objectives and hypotheses were not synonymous. Hypotheses, although
difficult to formulate, added great potential value to the studies because they
epitomized mainstream questions. Finally, it was argued that rejection of evide~ce
could often be as valuable as acceptance.
Guideline 3: Future FSR impact studies should formulate explicit important
hypotheses for testing.
Identification of new technologies
The studies showed the difficulties in identifying the newness of the technologies
under study. Some were new in the study locatlon but were not necessarily new
elsewhere. One was not new in time, but it had been recently adapted in various
ways and needed definition. Another found that the composition of the new
technology had evolved under the influence of farmer adaptation in the course of
the 3-year study. Another study involved elements of social differentiation and
evaluation.

Guideline 4: FSR impact projects should define a new technology selected for
study in spatial and historical terms, and in its technical composition, social
evolution, and adaptation.
Selection of analytical techniques
Selection of analytical techniques, as in any project, will be guided by the number
and nature of hypotheses and associated objectives. The issues of adopter and
nonadopter arose several times. This required ingenuity by the individual research
teams to resolve the issue in the best way possible. Although open to some
challenge, each technique proved useful under particular circumstances. Techniques
for relating adoption, productivity, income, and household expenditures were more
conventional and posed no great problems.
Cash-flow analysis was used, and simple comparisons of a range of
characteristics of adopter and nonadopter groups provided useful information. In
several instances, choice of techniques was limited by sample size, which varied
considerably between studies.
Given the exploratory and pioneering nature of these studies and the lack of
an accepted FSR impact study methodology, no general guidelines have emerged
for analytical techniques. The diversity of techniques actually applied in different
circumstances shows the flexibility needed at this stage. The greatest versatility and
sophistication was shown in the Sri Lankan study, which attempted the most
comprehensive analysis. However, its results were restricted by small sample size
and by the civil unrest in the country, which limited data collection to only l yr. No
results, for example, were obtained on the relations between technology and welfare
attributes.
Key constmints. In this and any multilocation research project, there are
unanticipated random constraints that lower performance limits. The constraints are
diverse and numerous and defy classification. They include (not exhaustively):
o lack of baseline data on which to design surveys and comprehend the
socioeconomic and institutional setting of technological introduction
and adoption;
o unsatisfactory primary and secondary data, typically collected by
agencies unrelated to the project unit (i.e., exteiision officers who
aggregate data from the survey location);
o the usual problems of household income management;

o restricted sample size, related to high number of drop-outs, or to
unexpected statistics on adopters and nonadopters;
o civil unrest that limit field surveys;
o natural calamities such as drought, floods, and earthquakes that
hamper field work and distort data (e.g., price);
o complexities of allocation of land to crops (e.g.? the third-season crop
in Bangladesh is divided into several plots of different crops, has
mixed crops per plot, and has different crop mixtures per plot); and
o changes in cropping systems during the course of the study, which
amounted to an unanticipated induced technological change (private
sector).
Scope of methodolog for future impact studies on farming systems research
The issue of matching the scope of future impact study objectives to time and
resources was examined. Agreement was reached on the following few additional
points:
o The need for a restatement of the value of forms of ex-ante analysis.
These might include partial budgeting with explicit assumptions with
regard to the impact of new technology on adoption, yields, projected
costs, and prices. These assumptions can be made with transferable
baseline data or, if necessary, with educated guesses. Sensitivity analysis
may be added. Other sources are rapid rural appraisal and the use of
secondary sources of data.
o The need for concurrent development of methodology to fulfil1 the needs
created by designation of hypotheses and objectives. This process was
exemplified by the Sri Lanka study, hamstrung though it was in
application.
o The need to give serious consideration to the incorporation of additional
assessments. These include equity and gender consequences at the
household level, the sustainability of benefits of technological adoption,
and macro impacts (e.g., net capital flows and changes in input flows to
the industry concerned).

hlem bers
o The need to improve docunlentation to further understand the processes
and attendant costs of FSR impact studies.
o The need to give careful consideration to the con~position of the FSR
impact team, by bearing in mind the need for farmer participation
throughout these studies (i.e., there must be an appropriate mix of
biological and social scientists).
o The need to emphasize the partnership that is required between farming
systems researchers and extension officers to ensure that the extension
staff are available and ready to cooperate in promoting the adoption of
new technologies. The studies showed too often that these links did not
exist, especially when the two groups were in separate departments. In
Thailand, the required links arose from personal contacts. In Isabela,
Philippines, extension workers were diverted from FS researchers by
technological change promoted by the private sector.
Group 2: Policy
V. T. Xuan - Vietnam (convenor); F. A. Bernardo - Philippines; S. A. Miah -
Bangladesh; S. B. Mathema - Nepal; M. 0. Adnyana - Indonesia; J. Hardie - IDRC;
R. Kirithaveep - Thailand; B. Shinawatra - Thailand; M. Agalawatte - Sri Lanka;
and W. D. Dar - Philippines.
Issues related to policy implications of the FSR approach were discussed at length.
Based on these discussions and the FSR lessons learned from the participating
countries, several issues were raised and corresponding recommendations were
made.
Institutionalizing the FSR approach
o To institutionalize the approach at both the national and grassroots
levels, there is an urgent need to sell and promote FSR-based ideas to
policymakers. This can be achieved by acquainting the policymakers with
the results of the FSR programs (i.e., impact studies and information and
data on returns to investments). Various other advocacy efforts must also
be pursued. A strong political will is a must.
o The FSR approach must be adopted on a broader perspective. It is not
sufficient to concentrate on the horizontal dimension; there must be a
focus on the vertical dimension as well. The vertical dimension would
allow promotion of rural agri-based industries and provide opportunities

to accelerate the rural economy. Another dimension that must be
considered is sustainability.
o FSR-based master plans are lacking in the participating countries.
Therefore, master plans are needed to extrapolate FSR-based
technologies into various country-specific policy recommendations.
o The FSR approach is not a cure-all approach. Therefore, the commodity
approach must be integrated into FSR.
o Institutionalization of the FSR approach should take cost effectiveness
into consideration. Countries have done this by following either a soft or
hard approach or a combination of these two approaches. Furthermore, it
is necessary to analyze the FSR approach in relation to social costs and
profitability.
o Extrapolation of FSR technologies should consider regional comparative
advantages. It should also consider existing biophysical and
socioeconomic environments across the regions to extrapolate FSR
technologies.
o The FSR approach is participatory and adopts a balance between a
bottom-up and a top-down approach. To streamline and use the FSR
approach in various environments, an attempt should be made to
categorize these environments. The FSR approach should be directed to
a given environment on the basis of the suitability of available FSR-based
technologies.
Support services in a policy context
Most parts of the policy context are a given, and FSR must be aware of this and
adapt accordingly.
o Resource maps, developed through geographical information systems and
other means, are available to different zone environments for effective
land use. These maps can be used to identify potential areas in which to
extrapolate FSR technologies. Proper use of these maps will speed up the
extrapolation process. Strong links and coordination among different
agencies are needed to use these maps effectively.
o The supply of production inputs should be efficiently managed to ensure
that they are available in the right amount, at the right price, in the right
quality, at the right time, in the right type, and in the right place. This will
enhance and sustain the production system in any environment. However,

Members
what is right depends on policies in the other areas (e.g., health,
environment, and financing).
o Accessibility of credit is important in the adoption of FSR-based
technologies. However, most farmers do not have adequate collateral to
get credit from institutions. To mitigate this problem, farmers should be
encouraged to group themselves to show their joint liabilities for access to
credit. Risk-distribution strategies should be used. Provision of crop
insurance is also needed to secure and sustain production systems.
o A congenial marketing environment must be provided to allow producers
to dispose of their products. Lack of an organized marketing system in the
rural sector puts farmers at a disadvantage. Groupings of farmers help to
strengthen their bargaining power. Vertical links through the
development of rural agri-based industries create better marketing
systems, employment, and distribution of marketing margins.
o Infrastructure support to FSR-based technologies is part of the analysis of
site conditions. Extrapolation to areas without an equivalent
infrastructure is irresponsible. Development of FSR-based technologies
in less advantaged and less favored areas will be more difficult because
these areas are likely to be Inore heterogeneous. However, social equity
demands that the attempt be made.
o Extension, education, and training are very important support systems.
Active involvement of a11 major actors (e.g., researchers, extension
workers, farmers, and the private sector) should be ensured from the
initial to the last stages of the FSR approach. Institutionalization of the
FSR approach must be encouraged in various educational institutions.
Informal training in the FSR approach should be intensified and provided
to extension workers, subject matter specialists, and middle-level
managers.
o Policy research on the impact and return on investment of FSR should be
given priority.
Group 3: Institutions
S. Biggs - England (convenor); V. R. Carangal - Philippines; T. Bottema - Indonesia;
M. Siddique - Bangladesh; D. K. S. Su~vastika - Indonesia; S. W. Almy -
Madagascar; C. Sukapong - Thailand; A. Mandac - Philippines; J. M. K. P.
Jayasinghe - Sri Lanka; W. Ratnayake - Sri Lanka; and K. A. Mettananda - Sri
Lanka.

Institutionalization is used in a broad sense to reflect the need for the creation of
long-term programs on FSR rather than short-duration projects. The word
institution in its sociological sense refers to the relationships between actors to
achieve certain things.
FSR means many things to many people. However, FSR claims and aims to
serve the farmer through assistance in problem solving. Impacts are by definition
location-specific; however, the justification for FSR is often couched in terms of
contributing to the achievement of national goals. It is often said that FSR is a way
to get researchers into the field or a way to get the researchers to reach senior
officials. It is acce ted that FSR is adaptive in nature, yet it is recognized that the
adaptive nature o its organizational form and management is less strong.
F
The macro - micro context
The major strength of FSR is that it gives priority to the farmer and seeks to help
solve the problems encountered by farmers. It addresses area-specific problems, the
solutions for which cannot necessarily be applied to larger areas. Given the fact that
FSR is practiced and funded in the context of national development plans and
research and development programs, it is hardly surprising that the goals of FSR
activities are fitted into national objectives. This may carry a contradiction between
FSR, which focuses on individual problem solving, and national programs that seek
to reach national targets.
Most cbuntries represented at this workshop adhere to national self-
sufficiency goals with regard to major staples (Indonesia, Thailand, Sri Lanka,
Bangladesh, and the Philippines). As the majority of cases show, FSR activities
fitted national goals to expand production of rice as well as individual goals of
farmers, which could be stated as expansion of income. Therefore, the existence of
national targets is not necessarily in contradiction with individual goals and the
derived goals of FSR. However, it remains questionable whether on-farm research,
as presented, can really be termed FSR in the pure sense because, by necessity, a
priori project goals were derived from national goals. However, several successful
adoptions, notably those in Indonesia and Thailand, benefited the farmers by
increasing nonrice income and cutting cost, respectively, but they did not expand
rice production.
Tl~e
need to justify location-specific activities such as FSR in national terms
is clear, but it is equally clear that attempts to pinpoint expected impact in national
terms are by necessity somewhat forced. In fact, even location-specific impacts are
difficult to substantiate. These observations point to the need for a priori
recognition of the consequences and complexities accompanying FSR in the context
of national plans and programs.

Decentralization and farming systems research
In most countries represented at the workshop, several shifts have occurred in
research and development. First, by the late 1980s, the allocation and use of
national resources became a dominant theme in research and development
throughout the region. Rather than focus on comniodities per se, more attention
was devoted to adaptive research in specific agroecological areas. This shift was
accompanied by agroecological zoning and the creation of regional research
institutes, each with a specific mandate.
Although this points to a form of decentralization, it should not be forgotten
that in most countries this process was accompanied by a considerably strengthened
role for coordinating institutes and the creation of national apex agencies that were
responsible for planning, budget allocation, and donor re1:ltions. This was the
second major shift.
Decentralization and regional specialization of research into specific areas
provided significant institutional opportunity for FSR. This is reflected in the
emergence of loosely structured FSR networks (e.g., in Vietnam) ;ind more
formalized systems (e.g., in Thailand). An encouraging feature of this development
is that government institutes, nongovernment organizations, and universities
participate in these networks and systems. Although these structlires tend to emerge
In response to somewhat inflexible government procedures, it is not unthinkable
that such approaches, creative as they are, could hinder long-term interest in the
practice of FSR because they reduce the short-term need to properly institute
programs.
The situation in the region, however, is not uniform. In severai countries,
FSR has become part and parcel of outreach institutes and even central research
agencies (e.g., in Indonesia and Sri Lanka). The success reported in the Indonesian
case relates clearly to the existence of a well-defined FSR program and the
willingness of senior officials to take FSR activities seriously. However, a possible
drawback could be that this FSR would be subject to national targets and plans,
which \vould not automatically be beneficial to effective FSR. In view of the
variability in the organizational structure of research and development in the region,
it is not possible to make sweeping statements and present firm conclusions. It is,
for example, not :lt all certain that the prevalent shift to rewurce rn:inagement will
indeed lead to more efficient use of resources and expanded private and social
benefits. At the same time, the reduced emphasis on long-term, commodity-focused
programs may hamper the creation of basic technology. Whatever ~ilill happen, it is
to be foreseen that the resource-focused drive will continuz because of the
increased importance that society gives to environmental factors.

The interface role of farming systems research
Almost every country uses different terms for FSR and its component methods
(rapid rural appraisal, on-farm trials, and pilot production projects). Each country
has important political reasons for its choice of terms. For example, "production
programs can only be done by the Indonesian Extension Service, so the FSR team
does a Development Research Project", or FSR in the Francophone scientific
community means the systematic political analysis of the national agricultural
economy, therefore, the FSR program becomes an "on-farm research program"; or
multilocation tests have been done on rented farmland because of a lack of regional
stations; therefore, "on-farm trials" become "participatory trials" to underline the
difference in methods.
Most of these terminological variations relate to the fact that FSR as a
distinct institutional entity is a newcomer to national scenes and is an interface
between well-established bureaucracies. Its aim is to solve problems, not to carry
out a predetermined set of actions, although it has a core methodology of its own.
Successful programs have been seen to act as intermediaries between the station-
based research establishment and extension services, marketing boards, and
irrigation authorities. Although they are usually based in the research service, they
do not confine themselves to traditional scientific research methods and sometimes
find themselves under attack for encroaching on the turf of another agency or
operating outside their research mandate.
Management of farming systems research: pulling strings and straws
A number of issues have emerged concerning the organization and management of
FSR project and programs:
o Flexibility in the application of FSR principles. In many cases, it was
observed that successful projects changed the technologies and the
emphasis of the FSR activities as they proceeded. In cases where a
staged approach appeared to have been followed, it was found that the
program had continuously monitored and reformulated its program in
accordance with the changes in policy, development, and context.
o Clarification and agreement on FSR objectives. Most of the FSR projects
had a wide range of differing and sometimes conflicting objectives. The
expectations of many projects were over-ambitious. A management
lesson from the case studies was that greater emphasis should be given
during FSR planning to the projection of expected outcomes and to the
methods of monitoring and assessing these outcomes. These issues should
include how to assess the extent of FSR influence on research station
priorities and on the strengthening and monitoring of farmer
experimentation.

o More program and less project funding of FSR. In many successful FSR
projects, it was found that research managers had additional funds and
resources from other sources. Some successful FSR cases were the result
of support after the project had been completed. A lesson from these
experiences was that FSR projects should not be seen in isolation from
other research and developnlent activities. A second lesson was that
some FSR projects Livere terminated at the time when the group or project
was becomlng most useful.
o Farmer reszarch: the need for monitoring and strengthening. The country
studies reveal an important and somewhat trivial fact. The issue is that in
several cases, FSR interventions and improved technologies were based
on already existing practices and commodity choices of farmers. The
cases of rlce in Thailand, fish in ricefields in Indonesia, and potato in Sri
Lanka illustrate that activities were defined and executed on the basis of
esisting trends.
It is noticeable that in Indonesia and Thailand, interventions were
successful, although the courses of the events leading to success were
quite different. In Sri Lanka, the suggested technological change was not
accepted because the fdrmers had already esperimented with, and
rejected, the component technology.
Another observation was made with regard to the diversity of actual
iinprovenients. In Thailand, the shift in the factor market and increased
labor costs determined the viability of mechanized direct seeding, in fact,
a move toward intensification. In Indonesia, in contrast, the inclusion of
fish with rice could be considered as a type of intercropping, which
intensified prodi~ction and increased land productivity.
Efforts in Thailand and Indonesia led to improvement in component
technolow; whereas, in Sri Linka, FSR confirmed the experience of the
farmers, G-hich was based merely on observing existing practices and
trends. The importawe of monitoring and strengthening farming
practices is underlined.
o The outgoing approach. FSR is a ~nultidisciplinary approach to solve farm
problen~s. But shortage of skilled labor in different disciplines may inake
it difficult to form a FSIi group in many developing countries.
Sometimes, national institutes have governn~ent permission to conduct
research on a particular crop or enterprise. In such a case, FSR can only
be conducted by using resource persons. The host institute should
therefore go to other organizations to find the required resource persons
and divide the work responsibilities anlong them. Opportunities should
also be divided among the collaborators. The implementing organization
should not try to show that they are in charge. This approach has been
quite successful in FSR in Bangladesh, Thailand, and Indonesia. Other
organiz:itions that are conducting FSR can follow this outgoing approach
to include other institutions in their FSR process.

o Assessing the outcomes of FSR. Most of the analytical tools used to
assess the impact of FSR were biased toward evaluating income
generation. There was no uniform relation between adoption of
technology and expanded income. This suggests the need to look beyond
hard indicators of welfare. If only hard ind~cators are observed, less
obvious but important benefits could be missed. This was reflected in
many of the impact studies. Some benefits may not be totally reflected in
the incomes of the direct recipient, and some benefits may take longer to
show results. There could also be indirect benefits that are difficult to
quantify. Therefore, when starting a project or activity, a conceptual
framework should be developed to capture the expected benefits in terms
of specific objectives of the components of the FSR technology package.
All activities should contain a self-evaluation mechanism.

Bangladesh
Mr. RaGqul Islam
Bangladesh Rice Research Inslitute
Gazipur, Joydebpur
Dhaka
Dr. Siddique Ali Miah
Bangladesh Rice Reseafrch Institute
Gazipur, Joydehpur
Dhaka
Mr. Mohinur Siddique
Bangladesh Rice Research Institute
Gazipur, Joydcbpur
Dhaka
England
Dr. Stephen Biggs
School of Development Studies
Universi~y of East Anglia
Norwich h'R 4715
Indonesia
Dr. Made Oka Adnyana
Agency for Agricultural Research and
Development
BORIF, P.O. Box 368/Boo, J1. Tentara
Pelajar, No. 3A, Bogor 16114
(d/h jl. Cimanggu)
Ir. Taco Boltema
CGPRT Centre, Jalan Merdeka
135 Bogor 16111
Ir. Dewa Ketut Sadra Swastika
Agency for Agricultural Research and
Development
BORIF , P.O. Box 36S/Boo, J1. Tentara
Pelajar, No. 3A, Bogor 161 14
(d/h jl. Cimanggu)
Participants
Madagascar
Dr. Sussn Almy
Madagascar-IRRT Rice Research Projcct
B.P. 4151
Antananariva (101)
Ms. Daniele Marie Ramiararnanana
Interna~ional Rice Research Institute
P.O. Box 933, Manila
Philippines
Nepal
Dr. Sudarshan Ma~herna
Central Socio-Economic Research Division
National Agricultural Research Council
Khumaltar, Lalipur
Philippines
Dr. Corazon Barba
College of Human Ecoloby
University of rhe Philippines Los Baiios
College, Laguna
Dr. William Dar, Director
Bureau of Agricultural Research
Department of Agriculture
Diliman, Quezon Ciry
V. Villa~lcio
Farn~ing Systems and Soils Research Insriru~e
University of rhc Philippines Los Barios
Collcge, Laguna
Thailand
Dr. Benchaphun Shi!lawatra
Chiang Mai University
Chisng Mai 50002

Mr. Chalerm Sukapong
Farming Systems Research Institute
Department of Agriculture
Bangkok 10900
Mr. Rasamee Kirithaveep
Farming Systems Research Institute
Department of Agriculture
Bangkok 10900
Vietnam
Dr. Vo-Tong Xuan
University of Cantho
Mekong Delta Farming Systems Research and
Development Centre, Cantho
Haugiang
IDRC
Dr. John Graham
Agriculture, Food, and Nutrition Sciences
Division
IDRC, Tanglin P.O. Box 101
Singapore 9124
Dr. John Hardie
Agriculture, Food, and Nutrition Sciences
Division
IDRC, P.O. Box 8500, Ottawa
Canada KIG 3H9
Dr. Mahfuzudin Ahmed
First Floor, House No. 363, Road 27
New DOHS, Mohakhali
Dhaka, Bangladesh
Dr. Clive Lightfoot
International Center for Living Aquatic
Resources Management,
MC P.O. Box 1501, Makati, Metro Manila
Philippines
IRRI
Dr. Virgilio Carangal
Asian Rice Farming Systems Network
International Rice Research Institute
P.O. Box 933, Manila
Philippines
Mr. Raymundo Gonzaga
Social Sciences Division
International Rice Research Institute
P.O. Box 933, Manila
Philippines
Mr. Abraham Mandac
International Programs Management Office
International Rice Research Institute
P.O. Box 933, Manila
Philippines
Sri Lanka
Dr. Fredrick Abeyratne
Resource Management Division
AR&TI Wijerama Mawatha
Colombo 7
M. Agalawatte
Division of Agricultural Economics and
Planning
Department of Agriculture
Peradeniya
Mr. N.K. Atapattu
Division of Agricultural Economics and
Planning
Department of Agriculture
Peradeniya
Ms. J.M.K.P. Jayasinghe
Division of Agricultural Economics and
Planning
Department of Agriculture
Peradeniya
Mr. K.A. Mettananda
Agricultural Research Station
Maha Illuppallama

Dr. N.F.C. Ranawecru
Di\ision of .-lgricul[l~ral Econo~nics and
Planning
Department of Agriculture
Pcradeniya
Mr. W. Rarnayakc
Diiision of Technolag Transfer
Department of Agriculture
Peradeniya
hls. G.K. Rcnuka
Diikion of Xgricul~ural Econoniics and
Planning
Dcpartmcnt of Agricullure
Peradeniya
hlr. P.A. Ssmaratu~lga
Division of Agricultural Economics and
Planning
Dtpnrtmcnt of Agriculture
Prradeniys
Dr. Rick Slla~~d
Residence oi thc Australia High Conlniissioner
S5 Horron Placc
Colon~bo 7
DI-. M. Sikurajnpatliy
Division oi Sccd and Plant h.la~erials
Dcpartmenl of Agriculture
Peraclc~li!,:i
Dr. D.E.F Surawecra
Division of Agricultural Economics and
Pla~i~iing
Dcparlmc~lt of Agriculture
Peradeniya
Dr. N. Vignarnjah
Addl. DD (Research) Division of Research

AAPP-ROS
ABC Project
ACIAR
ACSN
ADB
ADS
AIDAB
ANU
ARFSN
ARO
ASES'
ASSP
AT1
AUDP
BAEX
BAR
BP1
BRBDP
BS
BSU
CAP
CECAP
Appendix: Acronyms
Accelerated Agricultural Production Project
Research and Outreach Sub-Project
Agusan, Bukidnon, Capiz Settlement Project
Australian Centre for International Agricultural
Research
Asian Cropping Systems Network
Asian Development Bank
Agricultural Development Specialist
Australian Development Assistance Bureau
Australian National University
Asian Rice Farming Systems Network
Agricultural Research Office
Agricultural Suitability and Evaluation Systems
Agricultural Support Services Project
Agricultural Training Institute
Antique Upland Development Project
Bureau of Agricultural Extension
Bureau of Agricultural Research
Bureau of Plant Industry
Bicol River Basin Development Project
Bureau of Soils
Benguet State University
Countryside Action Program
Central Cordillera Agricultural Project

CFTSSF
CLSU
CSD
CSSAC
CVIADP
CVRP-I
DA
DA-V
DENR
DOH
DPWH
DSWD
EEC
FARM1
FS
FSA
FSDP-EV
FSDP-Bicol
FSR&D
FSRDN
FSR&E
FSSRI
Comprehensive Far~rring Technology Support to
Small Farmers
Central Luzon State University
Cropping Systems Division
Camarines Sur State Agricultural College
Cagayan Valley Integrated Area Development
Project
Central Visayas Regional Project-I
Department of Agriculture
Department of Agriculture - Visayas
Department of Environment and Natural
Resources
Department of Health
Department of Public Works and Highways
Departnrent of Social Welfare and Development
European Econolnic Community
Farm and Resource Management Institute
Farming Systems
Farming Systems Approach
Farming Systems Development Project-Eastern
Visayas
Farming Systems Development Project-Bicol
Farming Systems Reser~rcl~ and Development
Farming Systems Research and Development
Network
Farming Systems Research and Extension
Farming Systems and Soil Resources lnstitu te

GIS
GOP
GSK
HADP -
HYV
IAPMP
IDRC
IMPAS
IRRI
KABSAKA -
KASATINLU -
LGU -
MAF -
MBLRC
MCEPP
R'ICS
NFA
NFAC
NGA
NGO
NI A
NIST
NMCPP -
OFR -
geographic information systems
Government of the Philippines
Gulayan Sa Kalusugan
Highland Agricultural Development Project
high-yielding varieties
Integrated Agricultural Production and
Marketing Project
International Development Research Centre
impact assessment
International Rice Research Institute
Kabusogan sa Kaumahan
Kasaganaan sa Tigang na Lupa
local government unit
Ministry of Agriculture and Food
Mindanao Baptist Livelihood and Rural Center
Multiple Cropping Extension Pilot Production
Program
Multiple Cropping Section
National Food Authority
National Food and Agriculture Council
National Grains Authority
nongovernment organization
National Irrigation Administration
National Institute of Science and Technology
National Multiple Cropping Production Program
on-farm research

PIADP
PCA
PCARRD
PHARLAP
PSC
PTA
RADIP
RADOS
RBFS
R&D
R&E
RIARR
RRA
RRDP
SCO
SCUs
SFS
SIRDP
SMAP
SRMU
TA
TD
Philippine Australian Development Assistance
Program
Palawan Integrated Area Development Project
Philippine Coconut Authority
Philippine Council for Agriculture, Forestry and
Natural Resources Research and Development
Philippine Australian Rainfed Lowland Antique
Project
Philippine Sugar Commission
Philippine Tobacco Administration
Rainfed Agricultural Development (Iloilo) Project
Rainfed Agricultural Development Outreach Sites
rice-based farming system
research and development
research and extension
Regional Integrated Agricultural Research
System
rapid rural appraisal
Rainfed Resources Development Project
Special Concerns Office of DA
state colleges and universities
small farm systems
Samar Integrated Rural Development Project
Southern Mindanao Agricultural Project
Site Research Management Unit
technology adaptation
technology dissemination

TG
TV
UPLB
USAID
VISCA
\m
- technology generation
- technology verification
- University of the Philippines Los Baiios
- United States Agency for International
Development
- Visayas State College of Agriculture
- World Bank

Production Team
Editor : Michael Graham
Cop!.editors : Liza Gel isan
Tess Rola
Sheila Siar
Publication Coordinator : Anly Quintos
Typesetting : Arlene dela Cruz
Lourd Ann Erasga
Ruth Funtanilla
Amy Quintos
Gebs Quintos

IRRl Discussion Paper Serles
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NO, 4.
No. 5.
NO. 6.
NO. 7.
No. 8.
No. 9.
NO. 10..
NO. 11.
No. 12.
No. 13.
No. 14.
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