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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
Page 1 and 2: IRRl DISCUSSION PAPER SERIES NO. 15
Page 3 and 4: RECEIVED I RECU .- r b :'.i!~atlon
Page 5 and 6: Welcome address S .P.R. Weerasinghe
Page 7 and 8: Welcome Address S. P. R. Weerasingh
Page 9 and 10: Opening Comments After 15 yr of far
Page 11 and 12: increased as well, but only nlargin
Page 13 and 14: esult in high incomes for farmers,
Page 15 and 16: Investor concerns Usually investors
Page 17 and 18: WORKSHOP OBJECTIVES This workshop i
Page 19 and 20: Rice is the major food crop and die
Page 21 and 22: esource use and productivity varies
Page 23: Determination of ado,)tion factors
Page 27 and 28: At both sites, more than 73% of the
Page 29 and 30: Hossain A M, Nur-E-Elahi, Nazrul I
Page 31 and 32: Table 2. Crop varietal sequence sco
Page 33 and 34: Table 4. Correlation illatsix used
Page 35 and 36: - Table 6. Socioeconomic characteri
Page 37 and 38: Table 8. Extent of adoption and ave
Page 39 and 40: Table 10. Resource use and producti
Page 41 and 42: Table 12. Extent of adoption and di
Page 43 and 44: Table 14. Summary of per hectare ca
Page 45 and 46: IRlPACT OF FARMING SYSTEMS RESEARCH
Page 47 and 48: new information collected during FS
Page 49 and 50: average family owns seven heads of
Page 51 and 52: H Horticulture. To have a more regu
Page 53 and 54: improved varieties require higher l
Page 55 and 56: The types of the training provided
Page 57 and 58: extension agency in the district, t
Page 59 and 60: m Extension and other production-su
Page 61 and 62: Table 3. Farm characteristics of th
Page 63 and 64: Table 6. Farm practices and product
Page 65 and 66: Table 8. Major crops, crop varietie
Page 67 and 68: Table 10. Production and use of mil
Page 69 and 70: Table 13. Major problems and constr
Page 71 and 72: Table 15. Training undergone by the
Page 73 and 74: Table 17. Links between farmers and
Page 75 and 76:
----l CROP SUBSYSlLM rnurt L OTT tb
Page 77 and 78:
West Java provincial le~el BACKGROU
Page 79 and 80:
OBJECTIVES The specific objectives
Page 81 and 82:
Labor requirement Labor requirement
Page 83 and 84:
system models. This indicated that
Page 85 and 86:
Unit prices for all items were obta
Page 87 and 88:
Price elasticity. The demand for al
Page 89 and 90:
district fishery extension services
Page 91 and 92:
Table 2. Production of freshwater f
Page 93 and 94:
Table 4. Level of inputs used in ea
Page 95 and 96:
Table 6. Labor requirement for each
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able 8. Income analysis of each FS
Page 99 and 100:
Table 10. Nonfood expenditure patte
Page 101 and 102:
Table 12. The value of assets (IRP
Page 103 and 104:
Table 15. Nonfood expenditure patte
Page 105 and 106:
Table 17. Elasticities of food comm
Page 107 and 108:
l Oct k Jan Feb Mar Apr May Jun Jul
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From 1980 to 1986, the Integrated R
Page 111 and 112:
THE 1'\VO ;MATURE TECHNOLOGIES Dire
Page 113 and 114:
Conceptual framework STUDY METHODS
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Tai. Mungbean was introduced in Dok
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Land preparation for rice. The reac
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price of mungbean was high, some fa
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manufacturers. The earlier models (
Page 123 and 124:
Net farm income per household The a
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that although adopters were better
Page 127 and 128:
W It produced a good stand of rice
Page 129 and 130:
Table l. The promising technologies
Page 131 and 132:
Table 3. Mungbean before rice areas
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Table 5. Number of farm households
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Table 7. Area planted to mungbean,
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Table 9. Area planted to mungbean,
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Table 11. Area under dry seeded ric
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continued.. . Table 12. Socioeconom
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continued.. . Table 12. Socioeconom
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l~ndicative figures only. '~ature t
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composition, increases in income ca
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not be captured if the criteria for
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crops (rice, maize, and mungbean) a
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The explanatory Lwiable, nitrogen (
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of the ratio of actual intake and r
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Farming Systems Research and Extens
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Table 3. Input levels and productiv
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Table 5. Comparison of annual house
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Table 7. Comparison of annual nonfo
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Table 9. Comparison of percentage p
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Table 11. Log-linear models of impa
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INSTITUTIONALIZING THE FARILIIIVG S
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agricultural production system by i
Page 173 and 174:
In the midwest plain, where there a
Page 175 and 176:
Varietal irnprovernent. This compon
Page 177 and 178:
solutions to problems under the bas
Page 179 and 180:
Table 2. Rice farming systems in Ca
Page 181 and 182:
Table 5. Component-technology studi
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Wangwacharachul (1984) examined the
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household basis on an income and ex
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first crop. In 1989-90, the adopter
Page 189 and 190:
Nonfarm expenses constituted the bu
Page 191 and 192:
Herbicide is essential for DSR. How
Page 193 and 194:
o The classification of farmers on
Page 195 and 196:
Table 1. List of \,ariables idc~l~l
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Table 3. Conlparison of cash flow o
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Table 5. Level of input use for the
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Table 7. Production elasticities of
Page 203 and 204:
FROXl GREEN REVOLUTION TO FARhlING
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ainfed areas. The RIARS project app
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stability and sustainability. 1nsti
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o Limited feedback at all levels. A
Page 211 and 212:
Table l. Chronological sequcnce of
Page 213 and 214:
Table l. Chronological sequence of
Page 215 and 216:
Impact studies A number of studies
Page 217 and 218:
some simple statistical tests to as
Page 219 and 220:
assets). Patterns of food consumpti
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Production functions for first-seas
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and nonadopters indicate that there
Page 225 and 226:
E~zdowr~tcnt of l~ouselrol~f assets
Page 227 and 228:
variety, inadequate attention was p
Page 229 and 230:
Table 1. Farming system research si
Page 231 and 232:
Table 4. Comparison of levels of in
Page 233 and 234:
Table-6. Compariso~i of le\.els of
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Table 9. Estimated production funct
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Table 11. Factor shares of first-se
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Table 13. Factor slirlres of third-
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Table 15. Endownlent of farm assets
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IAIPACT ASSESShlEhT OF FARMING SYST
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Depending on the adequacy of rainfa
Page 247 and 248:
Demograpllic cllaractehtics. The co
Page 249 and 250:
The major farm implements owned by
Page 251 and 252:
Effect of RWCS on household cash fl
Page 253 and 254:
Table 1. Average cash expenses per
Page 255 and 256:
Table 5. Selected clia~~acteristics
Page 257 and 258:
Table 7. Comparative pcrforinance o
Page 259 and 260:
hiem bers Discussion and Recommenda
Page 261 and 262:
Guideline 4: FSR impact projects sh
Page 263 and 264:
hlem bers o The need to improve doc
Page 265 and 266:
Members what is right depends on po
Page 267 and 268:
Decentralization and farming system
Page 269 and 270:
o More program and less project fun
Page 271 and 272:
Bangladesh Mr. RaGqul Islam Banglad
Page 273 and 274:
Dr. N.F.C. Ranawecru Di\ision of .-
Page 275 and 276:
CFTSSF CLSU CSD CSSAC CVIADP CVRP-I
Page 277 and 278:
PIADP PCA PCARRD PHARLAP PSC PTA RA
Page 279 and 280:
Production Team Editor : Michael Gr
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