The Journal of Research ANGRAU

1

The Journal of Research ANGRAU 

(Published quarterly in March, June, September and December) 

ADVISORY BOARD 

Dr. P. Gidda Reddy 

Director of Extension, 

Rajendranagar, Hyderabad. 

Dr. R. Sudhakar Rao 

Director of Research, 


Dr. P. Chandrasekhar Rao 

Prof. & University Head, 

Dept. of Soil Science & Agril. Chemistry 

& Dean of Agriculture i/c 


Dr. K. Veeranjaneyulu 

University Librarian 

ANGRAU, Rajendranagar, Hyderabad. 

Dr. T.V. Satyanarayana 

Dean of Agril. Engineering & Technology, 


Dr. A. Sharada Devi 

Dean of Home Science 


EDITORIAL COMMITTEE MEMBERS 

Dr. T. Pradeep 

Principal Scientist(Breeding), 

Maize Research Station, 

ARI Campus, Rajendranagar, 

Hyderabad. 

Dr. R. Sudhakar 

Senior Scientist (Plant Pathology), 

Seed Research & Technology Centre, 


Dr. M. V. Ramana 

Senior Scientist (Agronomy), 

AICRP on Integrated Farming Systems, 

Water Technology Centre, 

College of Agriculture, Rajendranagar, 

Hyderabad. 

Dr. G. Sravan Kumar 

Additional Controller of Examination & 

University Head, Department of English, 


Hyderabad. 

EDITOR 

Dr. P. Chandrasekhar Rao 

Dean of Agriculture i/c 


Dr. A. Mani 

Associate Professor 

Dept. of Agril. Engineering & Technology 


Hyderabad. 

Dr. T. Ramesh 

Associate Professor 

Dept. of Plant Physiology 


Hyderabad. 

Dr. I. Sreenivas Rao 

Professor and Head, Dept. of Extension Education, 


Dr. T. Neeraja 

Professor, Dept. of Resource Management and 

Consumer Sciences, 

College of Home Science, 

Saifabad, Hyderabad. 

MANAGING EDITOR 

Dr. K. Anand Singh 

Principal Agricultural Information Officer 

AI&CC and ANGRAU Press, Rajendranagar, 

Hyderabad. 

with effect from April, 2012: 

RESEARCH EDITOR 

Dr. A. Lalitha 

AI&CC and ANGRAU Press, Rajendranagar, Hyderabad 

SUBSCRIPTION TARIFF 

Individual (Annual) : Rs. 300/- 

Institutional (Annual) : Rs. 1200/- 

Individual (Life) : Rs. 1200/- 

Printing Charges : Rs. 100/- per page 

DDs may be sent to The Managing Editor, Journal of Research ANGRAU, Agricultural Information & Communication Centre 

and ANGRAU Press - Agricultural Research Institute, Rajendranagar - Hyderabad - 500 030 

2

CONTENTS 

PART I : PLANT SCIENCE 

Effect of foliar application of NPK nutrients on growth and yield of chilli 1 

(Capsicum annuum L.) 

A.KIRAN KUMAR 

Nutrient uptake by rice crop under long term integrated nutrient management in 5 

rice – rice cropping system in Alfisols 

V. MAHESWARA PRASAD and P. PRABHU PRASADINI 

Changes in maturity indices during vermicompsoting Vs conventional Composting 14 

of agricultural wastes 

CH. S. RAMA LAKSHMI, P.C. RAO, G.PADMAJA, T.SREELATHA, 

M.MADHAVI, P.V.RAO and A.SIREESHA 

Influence of integrated nutrient management on physical properties of Alfisols 20 

under rice –rice cropping system in southern telangana zone 


Genetic variability, heritability and character association studies in 30 

sweet Sorghum [Sorghum bicolor (L.) Moench] 

VEMANNA IRADDI, T. DAYAKAR REDDY, A. V. UMAKANTH, CH. RANI, 

D. VISHNU VARDHAN REDDY and M. H. V. BHAVE 

PART II : VETERINARY SCIENCE 

Estrus synchronization response and fertility rate following treatment 39 

with Pgf 2α And Gnrh in acyclic lactating ongole cows 

K.VENKATA RAMANA, K.SADASIVA RAO, K.SUPRIYA and N.RAJANNA 

A study on migration pattern of sheep flocks in telangana region of Andhra Pradesh 42 

N. RAJANNA, M. MAHENDAR and K. VENKATA RAMANA 

Utilization of poultry waste an un-conventional protein source in small ruminant rations 47 

J. NARASIMHA, V.CHINNI PREETHAM and S.T.VIROJI RAO 

Postpartum ovarian follicular dynamics and estrus activity in lactating ongole cows 51 

K. VENKATA RAMANA, K. SADASIVA RAO, K. SUPRIYA and N. RAJANNA 

PART III : RESEARCH NOTES 

Development and evaluation of fiber enriched khakra 56 

M. KIRTHY REDDY, UMADEVI, P.S.S SAILAJA and KUNA APARNA 

Influence of nitrogen and weed management on growth and yield of 61 

aerobic rice (Oryza sativa L.) 

K. SANDHYARANI, M. MALLA REDDY, R. UMA REDDY and P.V. RAO 

Effect of seed priming on biochemical changes during seed storage 66 

of Maize (Zea mays L.) hybrids 

M. RAM KUMAR, P. S. RAO, V. PADMA and K. V. RADHA KRISHNA 

3

An economic analysis of Blackgram in Gulbarga district of Karnataka 70 

DEEPAK HEGDE, D. V. SUBBA RAO, N. VASUDEV and K. SUPRIYA 

Gene action and combining ability studies in Chickpea (Cicer arietinum L.) 74 

B. REDDY YAMINI, V. JAYALAKSHMI, B. NARENDRA and P. UMAMAHESHWARI 

Genetic divergence in Brinjal (Solanum melongena L.) 79 

BALAJI LOKESH, P.SURYANARAYANA REDDY, R.V.S.K.REDDY and N.SIVARAJ 

Relationship between profile of beneficiary farmers and the socio-economic impact 83 

of irrigated agriculture modernization and water bodies restoration and management 

(IAMWARM) project in Pudukkottai district 

G. ABIRAMI, B.VIJAYABHINANDANA and T. GOPI KRISHNA 

Construction of selection indices for F 2 

population derived from crosses between 88 

grain Sorghum × sweet Sorghum [Sorghum bicolor (L.) Moench] 



Evaluation of performance of Dendrobium orchid hybrids 93 

B. GOPALA RAO, P.T.SRINIVAS and M.H.NAIK 

Profile characteristics of Sugarcane farmers in Chittoor district of Andhra Pradesh 96 

S. RAMALAKSHMI DEVI, P. V. SATYA GOPAL, V.SAILAJA and S.V. PRASAD 

A study on diffusion status of System of Rice intensification (SRI) in Andhra Pradesh 

K. NIRMALA and R. VASANTHA 

```101 

Correlation and Path Coefficient analysis for yield and physiological attributes 105 

In Rice (Oryza sativa L.) hybrids under saline soil conditions 

M.SUDHARANI, P.RAGHAVA REDDY, G.HARIPRASAD REDDY and CH.SURENDRA RAJU 

Genetic divergence studies for yield and physiological Attributes in 109 

Groundnut (Arachis hypogaea L.) 

D. NIRMALA, V. JAYALAKSHMI, B. NARENDRA and P. UMAMAHESHWARI 

Influence of methods of irrigation on plant growth, yield, flower quality and 114 

vase life in Dendrobium orchid hybrid Sonia-17 under shade net 

B. GOPALA RAO, P.T. SRINIVAS and M.H.NAIK 

Study on pesticide residues of selected vegetables grown in north coastal 116 

zone of Andhra Pradesh 

Y. PUNYAVATHI and V. VIJAYALAKSHMI 

A study on the knowledge level of farmers on recommended Tea cultivation 121 

practices in Nepal 

KESHAV KATTEL, R. VASANTHA and M. JAGAN MOHAN REDDY 

An economic analysis of value addition to Cotton 124 

E. RADHIKA, R. VIJAYA KUMARI and D.V. SUBBA RAO 

Development of phytosterol enriched flavoured milk 127 

M. PENCHALA RAJU , ANURAG CHATHURVEDI and KUNA APARNA 

Correlation and path analysis for yield and its components in Rice (Oryza sativa L.) 132 

C.MANIKYA MINNIE, T.DAYAKAR REDDY and CH.SURENDER RAJU 

4

J.Res. ANGRAU 41(1) 1-4, 2013 

EFFECT OF FOLIAR APPLICATION OF NPK NUTRIENTS ON GROWTH AND 

YIELD OF CHILLI (Capsicum annuum L.) 

A.KIRAN KUMAR 

Fruit Research Station, Dr.Y.S.R.Horticultural University, Sangareddy, Medak-502001 

Date of Receipt : 03.07.2012 Date of Acceptance : 02.02.2013 

ABSTRACT 

A field trial was conducted on foliar application of NPK in randomized block design on chilli variety “Prakash 

(LCA 206)” at Jannareddy Venkatreddy Horticultural Research Station, Malyal, Warangal district of Andhra Pradesh 

(19.57 0 N and 78.66 0 E) with eleven treatment combinations from foliar sprays of 19:19:19 NPK @ 2.5 g l -1 , 5 g l -1 , 7.5 

g l -1 and 10 g l -1 ) and KNO 3 

@ 5 g l -1 and control. The results revealed that four foliar sprays of 19:19:19 NPK @ 7.5 g 

l -1 + KNO 3 

@ 5 g l -1 scheduled at monthly intervals starting one month after transplanting significantly enhanced the 

fresh (9820 kg ha -1 ) and dry (3320 kg ha -1 ) pod yield and resulted in significantly longer fruits (7.6 cm).There was no 

significant difference in plant height, plant spread (E-W and N-S), fruit girth and dry pod recovery percentage. 

Chilli (Capsicum annuum L.) belongs to the 

family, Solanaceae and originated from South 

America (Wikipedia, 2006). Chilli is rich in vitamin C 

and pro-vitamin A, particularly the red chilli (Sparkyby, 

2006). India is the largest producer, consumer and 

exporter of chilli and contribute to 25% of total world’s 

production. In India, chilli is grown in almost all the 

states across the length and breadth of the country. 

Andhra Pradesh is the largest producer of chilli in 

India, contributes about 30% to the total area under 

chilli, followed by Karnataka (20%), Maharashtra 

(15%), Orissa (9%), Tamil Nadu (8%) and other states 

contributing 18 % to the total area under chilli 

(Agrocrops, 2012). 

Recently, foliar feeding has been widely used 

and accepted as an essential part of crop production, 

especially on horticultural crops (Pace Gary, 1982). 

The purpose of foliar feeding is not to replace soil 

fertilization. Supplying a plant’s major nutrient needs 

(nitrogen, phosphorus and potassium) is most 

effective and economical via soil application. Foliar 

feeding can be an effective management tool to 

favorably influence pre-reproductive growth stages 

by compensating for environmentally induced 

stresses of adverse growing conditions and/or poor 

nutrient availability. Early foliar applications can make 

an already good crop better, either by stimulating 

more vigorous growth or maximizing the yield 

potential growth stage period. The advantages of foliar 

feeding in accomplishing the desired crop responses 

are two-fold. In order to enhance the effectiveness 

of any foliar application certain base solutions should 

be applied. Nitrogen should be present in any base 

solution. N-P, N-S or N-P-S base solutions are 

influential during early stages of growth utilizing 1:2 

or 1:3 N-P 2 

O 5 

ratios. N-P-K-S base solutions are 

suggested to influence the flowering /fruiting stages, 

utilizing 2:1:1 N-P 2 

O 5 

-K 2 

O ratio. The main objective 

of the present investigation was to study the effect 

of foliar applied nutrients i.e., NPK and ultimately to 

study the effect on growth and yield. 

MATERIALS AND METHODS 

The experiment was laid out in randomized 

block design with three replications on chilli variety 

“Prakash (LCA - 206)” at Jannareddy Venkatreddy 

Horticultural Research Station, Malyal, Warangal 

district of Andhra Pradesh (19.57 0 N and 78.66 0 E) with 

eleven treatment combinations of foliar sprays (19: 

19:19 NPK@2.5 g l -1 , 5 g l -1 , 7.5 g l -1 and 10 g l -1 ) and 

KNO 3 

@ 5g l -1 and control for three years. FYM was 

applied @ 25 t/ ha -1 , the NPK fertilizers were uniformly 

applied @ 220-60-80 kg ha -1 in all the experimental 

plots. One month old seedlings were transplanted at 

60 x 60 cm spacing. Four foliar sprays of 19:19:19 

NPK @ 2.5g l -1 , 5g l -1 , 7.5 g l -1 and 10 g l -1 (T 1 

to T 4 

), 

19:19:19 NPK@2.5g l -1 , 5g l -1 , 7.5 g l -1 and 10 g l -1 in 

email: adapakirankumar@gmail.com 

5

KIRAN KUMAR 

Table 1. Pooled analysis data for growth components of chilli as influenced by foliar spray 

Plant 

Plant 

Plant 

Treatments 

Height 

(cm) 

Spread 

E-W(cm) 

Spread 

N-S(cm) 

T 1-19:19:19 NPK @ 2.5 g l -1 90.3 57.7 55.1 

T 2 -19:19:19 NPK @ 5.0 g l -1 93.8 56.4 54.6 

T 3-19:19:19 NPK @ 7.5 g l -1 96.8 56.0 54.9 

T 4 -19:19:19 NPK @ 10.0 g l -1 96.2 56.7 54.4 

T 5 -19:19:19 NPK @ 2.5 g l -1 + KNO 3 @5 g l -1 92.7 54.5 53.5 

T 6 -19:19:19 NPK @ 5g/l + KNO 3 @ 5 g l -1 89.9 54.2 55.0 

T7-19:19:19 NPK @ 7.5 g/l + KNO3 @ 5 g l -1 98.4 57.4 55.2 

T 8 -19:19:19NPK @ 10 g/l + KNO 3 @ 5 g l -1 91.1 56.7 55.9 

T 9 -KNO 3 @ 5 g l -1 from one month after transplanting 94.4 57.5 56.3 

T 10 -KNO 3 @ 5 g l -1 at the time of flowering 91.6 54.4 52.7 

T 11-Control 89.9 53.9 52.8 

CD @ 5% NS NS NS 

SEm ± 

2.72 1.39 1.25 

application of 19:19:19 NPK and KNO 3. 

combination with KNO 3 

@ 5g l -1 (T 5 

to T 8 

) and KNO 3 

@ 5g l -1 (T 9 

) were scheduled at monthly intervals 

starting one month after transplanting. At the time of 

flower initiation two sprays of KNO 3 

@ 5g l -1 (T 10 

) 

was scheduled at monthly intervals and unsprayed 

control (T 11 

). Intercultural operations and Plant 

protection measures were uniform in all the 

experimental plots. For recording observations on 

plant height, plant spread, fresh weight, dry weight, 

fruit length and fruit girth, five plants in each bed 

were selected at random and labelled. The data thus 

recorded for three years was pooled and subjected 

to statistical analysis (Panse and Sukhatme, 1985). 

RESULTS AND DISCUSSION 

There was no significant difference in the 

plant height and plant spread (Table 1), fruit girth 

and percentage of dry pod recovery (Table 2). Fresh 

pod yield (9820 kg ha -1 ) and dry pod yield (3320 kg 

ha -1 ) were significantly maximum with four foliar 

6

EFFECT OF FOLIAR APPLICATION OF NPK NUTRIENTS ON GROWTH AND YIELD OF CHILLI 

Table 2. Pooled analysis data for yield components of chilli as influenced by foliar spray 

Treatments 

Fruit 

Length 

(cm) 

Fruit 

Girth 

(cm) 

Fresh pod 

yield (kg 

ha -1 ) 

Dry pod 

yield (kg 

ha -1 ) 

Recovery 

(%) 

T 1 -19:19:19 NPK @ 2.5 g l -1 7.3 0.9 8380 2650 31.6 

T 2 -19:19:19 NPK @ 5.0 g l -1 7.4 1.0 8380 2800 32.8 

T 3 -19:19:19 NPK @ 7.5 g l -1 7.6 1.0 8870 2910 33.4 

T 4 -19:19:19 NPK @ 10.0 g l -1 7.4 1.0 8330 2850 33.5 

T 5 -19:19:19 NPK @ 2.5 g l -1 + 

KNO 3 @5 g l -1 7.2 1.0 7970 2670 34.2 

T 6 -19:19:19 NPK @ 5g/l + KNO 3 

@ 5 g l -1 7.5 1.0 8590 2730 31.8 

T 7 -19:19:19 NPK @ 7.5 g/l + 

KNO 3 @ 5 g l -1 7.6 1.0 9820 3320 33.8 

T 8 -19:19:19NPK @ 10 g/l + 

KNO 3 @ 5 g l -1 7.5 1.0 8490 2720 32.0 

T 9 -KNO 3 @ 5 g l -1 from one 

month after transplanting 

T 10 -KNO 3 @ 5 g l -1 at the time of 

flowering 

7.5 0.9 8070 2730 33.8 

7.5 1.0 8310 2690 32.3 

T 11 -Control 7.1 0.9 6450 2240 34.7 

CD @ 5% 0.3 NS 1444 480 NS 

SEm ± 0.1 0.02 489 160 0.82 

application of 19:19:19 NPK and KNO 3. 

sprays of 19:19:19 NPK @ 7.5g l -1 + KNO 3 

@ 5g l -1 

scheduled at monthly intervals starting from one 

month after transplanting (Table 2). These results 

were supported by Lovatt (2005), who reported that 

foliar spray of 1% either 19:19:19 or KNO 3 

at 45, 60 

and 75 days after planting increased the crop yield 

by about 10% over unsprayed control. These results 

are in line with those of Patil and Biradar (2001), who 

applied NPK 19:19:19 as foliar application and found 

significant effect on fruit weight of chilli. Singh et al. 

(2002) reported that gross and marketable yield of 

Onion was highest with basal application of NPK and 

foliar application of 1% KNO 3 

at 30, 45 and 60 days 

after transplanting. 

Foliar application of 19:19:19 NPK@7.5 g l -1 

+ KNO 3 

@ 5g l -1 resulted significantly longer fruits 

(7.6 cm) (Table 2). Similarly, Baloch (2008) reported 

significant increase in fruit length by foliar application 

7

KIRAN KUMAR 

of Nitrophen 4%, Nitrogen compound 12%, Iron 2%, 

Magnesium 2%, Manganese 2%, Boron 2%, Copper 

4%, Molybdenum 2%, Potash 8%, P 2 

O 5 

12% and 

Calcium 8%. Similar studies have also been 

conducted by Jiskani (2005), who found that foliar 

application of zinc 3.0 ppm, copper 1.0 ppm and boron 

0.5 ppm produced the highest number of fruits per 

plant and increasing frequency of NPK (19:19:19) 

spraying from three to four times did not increase 

the number of chilli fruits per plant. Increased yields 

due to foliar spray could be attributed to the reason 

that foliar feeding is often effective when roots are 

unable to absorb sufficient nutrients from the soil and 

such a condition could arise from an infertile soil, a 

high degree of soil fixation, losses from leaching, 

soil temperatures, lack of soil moisture, or restricted, 

injured or diseased root system. Further, Silberbush 

(2002) also reported that foliar fertilization is a widely 

used practice to correct nutritional deficiencies in 

plants caused by improper supply of nutrients to roots. 

Improvement in yield of chilli was evident 

with increase in NPK 19:19:19 concentration. 

However, application beyond 7.5 g l -1 water was not 

effective and thus 7.5g l -1 water along with KNO 3 

@ 

5g l -1 was considered to be an optimum concentration 

for commercial production of Chilli. 

REFERENCES 

Agrocrops. 2012. Crop report 2011/12 Oilseeds & 

spices pp.6-7 

Baloch, Q. B, Chachar ,Q.I and Tareen, M.N. 2008. 

Effect of foliar application of macro and micro 

nutrients on production of green chillies 

(Capsicum annuum L.) Journal of Agricultural 

Technology, 4 (2):177-184 

Jiskani, M.M. 2005. Foliar fertilizers—fast acting 

agents. Daily DAWN, the Internet Edition, 

Monday December 5, 2005. 

Lovatt, C.J. 2005. Formulation of foliar phosphorus 

fertilize for chilli. www.freepatentsonline.com 

Gary, P.M. 1982. Foliar fertilization: some 

physiological perspectives. Paper presented 

to American Chemical Society, 13 th 

September, 1982. 

Panes, V.G and Sukhatme, G.V. 1985. Statistical 

methods for agricultural workers, Indian 

Council of Agrilcultural Research, New Delhi. 

Patil, R and Biradar, R. 2001. Effect of foliar 

application of essential nutrients on chillies. 

Agricultura Tecnica Santiago 51(3): 256-259. 

Silberbush, L.F. 2002. Response of maize to foliar 

vs. soil application of nitrogen-phosphoruspotassium 

fertilizers. Journal of Plant 

Nutrition. 25 (11): 2333-2342 

Singh, D.K, Pandey, A.K, Pandey, U.B and Bhonde, 

S.R. 2002. Effect of farm yard manure 

combined with foliar application of NPK mixture 

and micronutrients on growth, yield and quality 

of onion. News letter-National Horticultural 

Research and Development Foundation. 21- 

22(1): 1-7 

Sparkyby, F. 2006. Sparky Boy Enterprises. Planet 

Natural.1-6. 

Wikipedia.2006. Chillies: history, cultivation and 

processing pp.1-6. 

8


NUTRIENT UPTAKE BY RICE CROP UNDER LONG TERM INTEGRATED 

NUTRIENT MANAGEMENT IN RICE – RICE CROPPING SYSTEM IN ALFISOLS 


DAATT Centre, Krishna District, Machilipatnam – 521 002 


ABSTRACT 

Nutrient uptake by rice crop in different integrated nutrient management treatments at different stages of 

crop growth in rice-rice cropping system was studied in alfisols of Southern Telangana Zone of Andhra Pradesh for 

two consecutive years during 2005-06 and 06-07. The crop fertilized with increased level of nutrients accumulated 

more phytomass at every stage of sampling in kharif or rabi seasons during the two years. The uptake of NPK, Zn, Cu, 

Fe and Mn was also maximum in response to the application of recommended dose of fertilizers. There was no 

definite increase in the phytomass or uptake of major or minor nutrients consistently throughout the crop growth 

period during the two years by the integrated nutrient supply system compared to the application of recommended 

dose of fertilizers. 

India is one of the main countries producing 

Rice (Oryza sativa L.) in the world. Rice –Rice is the 

most predominant cropping system in southern 

telangana zone of Andhra Pradesh state. 

Deterioration of soil fertility and declining productivity 

due to indiscriminate application of nutrients through 

the fertilizers with the threat of the declining 

productivity has become major problem. Continuous 

cropping and long term fertilization are liable to 

change the soil properties and crop production, 

depending upon the type of management practices 

(Santhy et al, 1998). The micronutrient deficiencies 

are being recognized in soils intensively cultivated 

with cereals in several parts of the country. This is 

aggravated by the continuous application of high 

analysis fertilizers without replenishing the depleted 

micronutrients. Therefore, the incorporation of organic 

material is emphasized to supply the micronutrients 

and thereby maintain the nutrient balance. 

Hence, an investigation was made to assess 

the soil nutrient supplying capacity under different 

INM practices in a long-term fertilization experiment 

with continuous rice - rice cropping system. 


The present studies were conducted during 

two consecutive years 2005-06 and 2006-07 at 

Agricultural College Farm, Rajendranagar, 

Hyderabad. The experiment was conducted on a 

sandy clay loam soil on which only rice is grown 

continuously in both kharif and rabi seasons since 

1988. The experiment was laid out in randomized 

block design with 12 treatments (Table 1) in three 

replications. Rice variety RNR 23064 was planted 

adopting a spacing of 20 cm x 10 cm in 59.8 m 2 

sized plot. 

Sampling of plants was done by uprooting 

five hills per treatment at tillering, panicle initiation 

and harvesting stage of the crop in each season 

during the two years of the investigation for the 

nutrient removal studies. The samples were ground 

using Willey mill and extracted with triacid. The 

resultant extract was subjected to analysis of N.P 

and K as per the procedures outlined in Tandon 

(1995). 

Finally, the uptake of macro nutrients was 

calculated by using the following formula; Nutrient 

uptake (kg ha -1 ) = nutrient content (%) x dry matter 

(kg ha -1 ) divided by 100. Whereas the uptake of micro 

nutrients was calculated by using the formula; 

Nutrient uptake (g ha -1 ) = nutrient content (%) x dry 

matter (g ha -1 ) divided by 100. 


Major Nutrients 

a. Nitrogen 

The crop grown without the external input of 

manures and fertilizers removed lesser quantities of 

26, 35, and 63 kg N ha -1 in kharif 2005 at tillering, 

panicle initiation and harvesting stage of the crops 

email: vemulamadamp@gmail.com 

9

PRASAD and PRASADINI 

respectively. In the subsequent rabi, the crop 

removed 38, 33 and 65 kg N ha -1 at the respective 

stages (Table 2). In kharif 2006, rice removed 24 kg 

N ha -1 at tillering, 40 kg at panicle initiation and 40 kg 

N ha -1 at harvesting stage of the crop in T 2 

. In the 

rabi season, it removed 29, 31 and 27 kg ha -1 . The 

application of 50 % recommended dose of fertilizers 

continuously in the kharif and rabi season, 

significantly enhanced the quantity of N removed by 

the crop at every stage of its growth. This trend 

improved with increase in the quantity of nutrients 

applied upto the optimum schedule. The integrated 

supply of nutrients by substituting 25% N fertilizer 

with glyricidia and application of 75 % recommended 

dose of fertilizers in kharif significantly increased the 

uptake of nitrogen at tillering both in kharif and rabi 

during two years. 

b. Phosphorus 

The uptake of this nutrient increased from 

1.0 kg at tillering to 4.4 kg at panicle initiation and 

further to 8.0 kg ha -1 at harvesting stage of the crop 

during kharif 2005 (Table 3). The uptake of the nutrient 

was increased by the application of fertilizers in 

different proportions during kharif and rabi season. 

The adoption of integrated nutrient management 

options by substituting 50 % N fertilizer with FYM, 

paddy straw or glyricidia appreciably increased the 

P uptake compared to the effect of chemical fertilizers 

applied at recommended dose. The substitution of 

25 % N fertilizer with any one of these three organic 

sources in the kharif season and application of 75 % 

recommended dose of fertilizers in the rabi season 

also showed similar results. 

c. Potassium 

Rice removed more Potassium in response 

to the application of different levels of fertilizers in 

kharif and rabi season and their integration with the 

organic source of nutrients (Table 4). The unfertilized 

crop removed 32, 48 and 66 kg ha -1 in kharif and 38, 

62 and 71 kg K ha -1 in rabi at tillering, panicle initiation 

and harvesting stage of the crop during 2005-06. The 


in the kharif season increased the uptake significantly 

to 38, 77 and 71 kg K ha -1 at the respective stages 

of crop growth. The application of 50 % 


also increased the uptake significantly to 49, 70, 114 

kg K ha -1 . These trends repeated during the second 

year also. A large quantity of 60, 88 and 84 kg K ha - 

1 

in kharif and 62, 84 and 158 kg K ha -1 was removed 

in rabi during the first year (2005-06) by the 

application of recommended dose of fertilizers both 

in the kharif and rabi season. The uptake at tillering 

was 61 kg ha -1 in kharif 2006 and 63 kg ha -1 in rabi. 

The uptake was 61, 82 and 63 kg ha -1 at tillering, 

panicle initiation and harvesting in kharif while the 

crop removed 63, 82 and 100 kg ha -1 K during 

corresponding stages in the rabi seasons during 2006- 

07 in response to this optimum fertilizer schedule to 

rice-rice crop sequence. The integrated supply of 

nutrients by substituting 50 % N fertilizer either with 

FYM, paddy straw or glyricidia in the kharif season 

and application of recommended dose of fertilizers 

in the rabi season did not improve the uptake of K by 

rice compared to the crop supplied with nutrients 

continuously through the recommended dose of 

fertilizers. 

The role of any of these organics to substitute 

25 % N fertilizer in the kharif season and application 

of 75 % recommended dose of fertilizers in the rabi 

season was also not distinct to significantly increase 

the uptake of K compared to rice grown with fertilizers 

alone. 

B. Micronutrients 

a. Zinc 

The application of fertilizers with organic 

source of nutrients activated the crop to remove large 

quantity of Zn from the soil. The results showed that 

a low quantity of 29.2 g Zn was removed at tillering, 

56.5 g at panicle initiation and 88.3 g ha -1 at 

harvesting stage of rice in the kharif season while 

the uptake was 44.6, 53.7 and 77.93 g ha -1 from the 

unfertilized soil during the first year (Table 5). The 

application of 50 % recommended dose of fertilisers 

continuously in kharif and rabi season to the 

sequence crops significantly increased the uptake 

of this nutrient throughout the crop growth period. 

The crop was estimated to remove 43.6, 95.1 and 

135.6 g Zn ha -1 in kharif and 48.6, 85.5 and 160.4 g 

ha -1 in rabi at tillering, panicle initiation and harvesting 

during the first year. It removed 28.3, 63.5 and 174.9 

g Zn ha -1 in kharif and 40.6, 75.74 and 146.1 g ha -1 in 

the rabi season during the three corresponding growth 

10

NUTRIENT UPTAKE BY RICE CROP UNDER LONG TERM INM 

stages of crop in the second year. The uptake of this 

micronutrient in general tended to increase with the 

fertilizer schedule upto the optimum. Rice fertilized 

with the recommended level of nutrients through the 

fertilisers removed a large quantity of 50.1, 112.1 

and 210.7 g Zn ha -1 in kharif and 57.2, 104.3 and 

255.4 g Zn ha -1 in rabi at tillering, panicle initiation 

and harvesting stages respectively. During the second 

year rice removed 36.1, 92.2 and 250 g Zn ha -1 in 

kharif season and 46.3, 101.6 and 174.4 g ha -1 in the 

rabi season. The substitution of 50 % N fertilizer in 

kharif and application of recommended dose of 

fertilizers in rabi significantly increased the uptake 

of the micronutrient throughout the crop growing 

period compared to the supply of nutrients 

continuously through the chemical fertilizers only 

during the second year. 

The substitution of 50% N fertilizer with 

glyricidia in kharif and application of recommended 

dose of fertilizers in the rabi season was the best 

nutrient management strategy. It enabled the crop to 

remove significantly more quantity of Zn consistently 

at every stage of crop growth during kharif and rabi 

during the two year crop sequence. The substitution 

of 25 % N fertilizer with glyricidia in kharif and 


in rabi was also superior to the complete dependence 

on chemical fertilizers. However, the uptake of Zn 

by this treatment was not significantly different at 

panicle initiation in the first year and at harvest in 

the second year. 

b. Copper 

Rice removed 4.90, 10.29 and 19.22 g ha -1 

Cu in kharif and 7.57, 9.32 and 14.94 g ha -1 in rabi at 

tillering, panicle initiation and harvesting stage from 

the soil mineralized nutrients without the external 

supply during 2005-06 (Table 6). The uptake was 

4.14, 8.93 and 23.61 g Cu ha -1 in the kharif season 

while it was 5.08, 8.06 and 10.71 g ha -1 in the rabi 

season during the second cycle of the crop sequence. 

The fertilizer application triggered the uptake of this 

micronutrient. The crop fertilized with 50 % 

recommended dose of fertilizers invariable removed 

significantly larger quantity of Cu ha -1 throughout the 

growth period. The dressing of soil with optimum 

fertilizer schedule for rice in kharif and rabi season 

maximized the uptake of Cu compared to relatively 

high level of farmers schedule. Rice removed 8.86, 

19.92 and 44.75 g Cu ha -1 in kharif while it removed 

9.30, 18.30 and 54.37 g Cu ha -1 in rabi during 2005- 

06. Similarly, maximum uptake of 6.00, 15.26 and 

52.82 g Cu ha -1 was recorded at tillering, panicle 

initiation and harvesting stage in kharif while it was 

7.56, 17.28 and 38.47 g ha -1 in rabi during 2006-07. 

The substitution of 50 % N fertilizer in kharif with 

FYM, paddy straw or glyricidia and the application of 

recommended level of fertilizers in rabi were not 

significantly superior to enhance the uptake of this 

micronutrient significantly compared to the 

supplement of nutrients entirely through chemical 

fertilizers. The substitution of 25 % N fertilizer with 

any of the three organic sources in kharif and 


in the rabi season were also not distinguished as 

superior nutrient management practices to fertilizer 

treatments. 

c. Iron 

The uptake of nutrients was low by growing 

rice in sequence on the native soil fertility without 

external input of organic or inorganic source of 

nutrients in the kharif season. The crop removed 

156.9, 308.9 and 399.2 g Fe ha -1 at tillering, panicle 

initiation and harvesting during kharif 2005 (Table 7). 

In the subsequent rabi, rice removed 251.3, 302.9 

and 318.9 g ha -1 Fe. The application of fertilizers 

increased the uptake of this nutrient. The uptake was 

significantly more even by the application of 50 % 

recommended dose of fertilizers continuously in the 

kharif and rabi season. The crop fertilized with 50 % 

recommended dose of nutrients removed 152.2, 

314.2 and 984.3 g Fe ha -1 in kharif and 223.4, 461.1 

and 769.5 g Fe ha -1 in the rabi season. The uptake of 

this micronutrient further increased with the level 

fertilizer application to a maximum upto the 

recommended dose. 

The substitution of 50 or 25 % N fertilizer 

with FYM in the kharif season was beneficial. It 

increased the uptake of Fe significantly more at 

tillering stage of the crop both in kharif and rabi 

11


seasons during the two years over the crop grown 

entirely with chemical fertilizers. But, the substitution 

of 50 % N fertilizer with glyricidia was more beneficial. 

It increased the uptake of Fe by rice in significantly 

larger quantities upto panicle initiation both in kharif 

and rabi season during the two years. Such a 

beneficial effect of integrated nutrient management 

by substituting 25 % N fertilizer with glyricidia was 

on the other hand persistent only at tillering stage. 

d. Manganese 

Rice grown with different levels of fertilizers 

and integrated with organic source of nutrients 

removed larger quantities of this micronutrient than 

from the unfertilized soil. The crop removed 187.4 g 

ha -1 Mn at tillering, 384.9 g at panicle initiation and 

137.9 g ha -1 at harvesting stage during kharif 2005- 

06 (Table 8). The crop grown in the subsequent 

season removed 269.8, 328.5 and 324.69 g ha -1 Mn. 

During the second year rice removed 154.9, 351.9 

and 474.9 kg Mn ha -1 in kharif. In the rabi season it 

removed 192.1, 313.6 and 215.7 g Mn ha -1 at tillering, 

panicle initiation and harvesting stage. The 

continuous application of 50 % recommended dose 

of fertilizers increased the uptake of this micronutrient 

during the corresponding crop growth stages in kharif 

and rabi in both the years. The crop fertilized with 

this treatment dose removed 276.0, 629.9 and 574.9 

g Mn ha -1 at tillering, panicle initiation and harvesting 

stage in the kharif season, while it removed 287.4, 

525.1 and 676.8 g ha -1 in rabi 2005-06. The uptake 

was 183.1, 374.7 and 784.5 g Mn ha -1 in kharif, while 

it was 232.3, 483.3 and 643.7 g ha -1 in the rabi season 

during the three crop growth stages in the second 

year crop cycle. The contribution of FYM or glyricidia 

to substitute 50 % N fertilizer was superior to 

chemical fertilizers alone in enhancing the uptake of 

this micronutrient only at tillering stage during 2005- 

06. 

The available Zn and Cu in the fertilized soil 

was on par with the unfertilized soil at different stages 

of crop growth during the two year rice-rice cropping 

sequence. The co-application of 50 per cent 

recommended dose of NPK through fertilizers and 

FYM or glyricidia equivalent 50 per cent N fertilizer 

in the kharif season followed by the recommended 

dose of fertilizers in the rabi season significantly 

enhanced the availability of Fe both in the surface 0- 

15 and lower soil depth of 15-30 cm. The substitution 

of 25 per cent N fertilizer with these organic materials 

in the kharif season and application of 75 per cent 

recommended dose of fertilizers in rabi season also 

enriched the soil with more quantity of available Zn. 

But, this improvement was relatively less consistent 

at different stages of crop growth than their 

substitution for 50 % N fertilizer. This trend was also 

similar for the soil available Cu content. Additionally, 

its improvement was also recorded by substituting 

50 or 25 % N fertilizer with paddy straw only in the 

first year. The benefit of increased availability of Fe 

in the soil was recorded at the tillering stage during 

2005-06 by the substitution of 50 per cent N fertilizer 

with FYM in kharif season and application of 


only in the surface layer. On the other hand, the 

availability of Mn was not influenced by the 

application of fertilizers or the conjunctive use of 

nutrients through organic and inorganic sources. 

Rajeev Kumar et al., (1993), Singh et al., (1999) 

reported that the incorporation of organic sources in 

the soil along with the fertilizers increased the 

available micronutrients. The magnificent responses 

of integrated nutrient management treatments in 

leaving behind larger quantities of copper sustained 

the crop requirement in sufficient quantity. The 

availability of Zn increased by the co application of 

FYM by substituting 25 or 50% N fertilizer. 

Nonetheless, the site of present experiment 

continuously cropped with rice-rice cropping 

sequence for the past 17 years contained much higher 

quantities of Zn, Cu, Fe, Mn than the critical limit of 

0.6 mg kg -1 Zn, 0.2 mg kg -1 Cu, 4 mg kg -1 Fe, and 3 

mg kg -1 Mn even in the unfertilized control. Not 

complacent with the data so achieved, it would be a 

wise step to substitute 50 per cent N fertilizer with 

FYM or glyricidia to averse the likely depletion of 

these micro but essential elements for crop growth 

in the years to come 

12


Table 1. Details of the treatments 

Sl. No Kharif Rabi 

T 1 No fertilizers, No organic manures No fertilizers, No organic manures 

T 2 50 Rec. NPK dose through fertilizers 50 Rec. NPK dose through fertilizers 

T 3 50 % Rec. NPK dose through fertilizers 100 % Rec. NPK dose through OM 

T 4 75 % Rec. NPK dose through fertilizers 75 % Rec. NPK dose through fertilizers 

T 5 

T 6 

T 7 

T 8 

100 % Rec. NPK dose through fertilizers 100 % Rec. NPK dose through fertilizers 

120:60:60 kg ha -1 120:60:60 kg ha -1 

50 % Rec. NPK dose through fertilizers + 50 % N 

through FYM 


through FYM 


through paddy straw 

T 9 75 % Rec. NPK dose through fertilizers + 25 % 

N through paddy straw 

T 10 


through glyricidia 

T 11 75 % Rec. NPK dose through fertilizers + 25 % N 

through glyricidia 

T 12 Conventional farmers practice 80:50:20 kg ha -1 

NPK 

100 % Rec. NPK dose through fertilizers 






Conventional farmers practice 80:50:20 kg 

ha -1 NPK 

Table 2. Influence of integrated nutrient management practices on N uptake (kg ha -1 ) in rice-rice cropping 

system 

Treatments 

Tillering 

2005-06 2006-07 

Panicle 

initiation 

Harvesting Tillering Panicle 

initiation 

Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi Kharif 

Harvesting 

T 1 26 38 35 33 63 65 24 29 40 31 40 27 

T 2 47 45 77 73 100 114 31 39 51 63 60 59 

T 3 32 46 70 80 111 134 29 41 58 81 77 86 

T 4 49 49 82 84 105 173 35 43 80 78 75 68 

T 5 55 48 119 110 112 126 42 48 106 96 79 92 

T 6 39 51 94 104 115 128 39 42 89 95 72 74 

T 7 53 59 106 107 112 143 41 48 97 94 69 75 

T 8 30 45 88 81 108 179 37 42 85 82 61 75 

T 9 48 46 97 83 105 150 30 41 68 93 69 76 

T 10 59 66 121 119 121 181 45 54 109 118 91 80 

T 11 62 70 125 121 119 135 50 53 115 117 92 80 

T 12 42 52 85 79 103 123 35 43 69 82 68 72 

SE + 2.25 1.6 9.7 7.7 5.8 10.6 2.4 4.2 4.7 8.7 7.9 9.0 

CD at 5 % 4.6 3.4 20.2 16.0 12.0 22 5.0 8.6 9.8 20.2 16.4 18.6 

Rabi 

13


Table 3. Influence of integrated nutrient management practices on P uptake (kg ha -1 ) in rice-rice cropping 

system 

Treat 

ments 

Tillering 

2005-06 2006-07 

Panicle 

initiation 


initiation 

Harvesting 

Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi 

T 1 1.0 1.6 4.4 4.1 8.0 3.5 1.0 1.2 5.0 3.8 8.8 4.7 

T 2 1.6 1.7 6.9 6.7 10.0 10.6 1.1 1.4 5.1 5.7 12.9 10.5 

T 3 1.3 1.8 6.3 7.5 11.9 19.0 1.2 1.7 5.2 7.7 9.6 16.3 

T 4 1.6 1.8 6.7 7.2 10.7 17.4 1.2 1.5 6.8 6.7 12.1 12.4 

T 5 3.6 1.9 8.0 7.6 13.3 25.5 1.4 1.6 7.3 7.3 13.1 13.3 

T 6 2.9 2.0 7.1 7.9 13.7 28.7 1.3 1.7 7.0 7.4 11.9 15.0 

T 7 3.5 1.9 7.8 7.9 13.6 22.6 1.3 1.6 7.3 7.0 12.0 14.5 

T 8 3.4 1.8 6.3 7.3 11.6 28.1 1.1 1.7 6.1 7.4 11.1 13.6 

T 9 3.3 2.1 7.1 7.0 11.3 23.0 1.1 1.6 6.2 7.0 13.2 14.6 

T 10 3.7 2.2 8.1 8.3 14.9 27.4 1.4 1.7 7.5 8.2 16.7 17.5 

T 11 3.8 2.3 8.2 8.0 14.9 20.4 1.6 1.7 7.8 7.7 11.9 15.5 

T 12 3.5 1.8 7.0 6.5 10.6 15.9 1.1 1.4 5.5 6.5 11.3 16.5 

SE + 0.14 0.04 0.54 0.91 1.06 2.55 0.02 0.04 0.54 0.63 0.57 1.54 

CD at 

5 % 

0.30 0.08 1.12 1.88 2.20 5.30 0.05 0.09 1.12 1.30 1.18 3.20 

Table 4. Influence of integrated nutrient management practices on K uptake (kg ha -1 ) in rice-rice cropping 

system 

Treatment 

Tillering 

2005-06 2006-07 

Panicle 

initiation 


initiation 

Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi Kharif Rabi Kharif 

Harvesting 

T 1 32 38 48 62 66 71 34 39 48 42 49 65 

T 2 38 49 77 70 71 114 41 50 57 62 54 99 

T 3 34 51 70 82 84 114 38 52 59 86 62 90 

T 4 50 60 77 80 77 114 51 62 76 75 80 90 

T 5 60 62 88 84 84 158 61 63 82 82 63 100 

T 6 59 62 80 88 89 177 60 64 78 85 71 160 

T 7 49 60 86 86 87 149 51 62 80 80 80 157 

T 8 58 60 60 80 82 179 60 62 65 82 82 182 

T 9 60 63 78 76 77 149 62 65 70 80 91 160 

T 10 61 65 90 90 100 181 65 65 84 90 90 185 

T 11 60 63 92 88 94 152 61 65 86 88 90 180 

T 12 49 50 76 72 74 114 50 52 62 72 62 115 

SE + 2.1 4.4 1.1 3.3 0.5 10.6 2.3 3.1 1.6 8.8 1.4 1.1 

CD at 5 % 4.3 9.2 14.7 6.9 4.2 22.0 4.7 6.5 3.4 18.3 3.0 22.4 

Rabi 

14


Table 5. Influence of integrated nutrient management practices on Zn uptake (g ha -1 ) in Rice-Rice 

cropping system 

Treatment 

Tillering 

2005-06 2006-07 

Panicle 

initiation 


initiation 

Harvesting 


T 1 29.2 44.6 56.5 53.7 88.3 77.93 24.7 34.1 58.7 56.3 117.0 55.1 

T 2 43.6 48.6 95.1 85.5 135.6 160.4 28.3 40.6 63.5 75.74 174.9 146.1 

T 3 35.1 54.7 86.3 99.3 151.2 221.5 29.3 47.0 64.2 103.48 214.1 169.0 

T 4 45.60 53.9 96.7 96.9 171.2 220.5 33.2 42.6 84.3 90.60 220.8 145.0 

T 5 50.1 57.2 112.1 104.3 210.7 255.4 36.1 46.3 92.2 101.6 250.0 174.4 

T 6 46.3 67.8 114.3 124.2 174.0 307.9 41.0 56.3 106.8 117.0 293.8 197.9 

T 7 53.5 67.5 129.7 118.6 217.5 292.7 40.9 48.5 107.4 105.3 271.6 119.8 

T 8 35.7 55.7 80.7 110.3 163.0 251.3 32.7 51.0 68.3 112.5 195.4 179.5 

T 9 46.8 51.2 106.1 104.0 184.3 241.4 34.0 47.0 69.2 101.4 201.9 183.3 

T 10 56.57 65.0 128.2 127.8 242.6 312.8 44.0 55.3 109.9 123.8 294.6 206.5 

T 11 57.97 69.1 124.5 121.1 258.1 307.9 47.2 53.6 112.9 117.2 286.7 193.8 

T 12 49.3 46.3 90.8 87.1 178.7 199.0 34.2 41.8 72.1 91.8 195.6 151.6 

SE + 2.3 1.8 7.4 10.8 12.8 27.0 1.5 2.8 2.3 7.0 19.6 9.8 

CD at 5 % 4.8 3.8 15.4 22.4 26.5 56.4 3.2 5.8 4.7 14.5 40.6 20.4 

Table 6. Influence of integrated nutrient management practices on Cu uptake (g ha -1 ) in Rice-Rice 


Treat 

ments 

Tillering 

2005-06 2006-07 

Panicle 

initiation 


initiation 

Harvesting 


T 1 4.90 7.57 10.29 9.32 19.22 14.94 4.14 5.08 8.93 8.06 23.61 10.71 

T 2 7.49 8.23 17.07 15.31 29.10 33.43 4.90 6.26 10.37 12.37 37.23 31.35 

T 3 5.80 8.82 15.82 17.52 33.12 50.12 4.96 7.42 10.64 16.88 46.14 38.05 

T 4 7.82 9.29 17.48 16.91 76.25 46.30 5.50 6.93 14.14 15.36 47.75 31.79 

T 5 8.86 9.30 19.92 18.30 44.75 54.37 6.00 7.56 15.26 17.28 52.82 38.47 

T 6 7.44 11.02 19.56 19.97 38.75 59.38 6.28 8.89 16.57 18.52 55.07 39.97 

T 7 8.66 9.80 20.52 19.58 41.24 56.68 6.24 8.66 16.67 16.51 53.10 38.68 

T 8 5.60 8.98 13.73 17.47 32.34 48.38 4.90 8.10 11.53 17.25 39.14 36.55 

T 9 3.28 8.38 17.41 16.37 34.14 45.06 5.41 7.45 11.26 15.60 42.01 36.38 

T 10 9.16 10.86 19.44 20.61 50.01 58.68 6.65 8.95 17.11 19.15 58.08 41.07 

T 11 9.27 11.30 19.36 19.18 46.47 59.74 7.40 8.37 17.06 17.22 57.74 38.86 

T 12 7.85 8.67 16.10 15.42 37.20 49.27 5.15 6.85 11.97 14.66 41.77 32.53 

SE + 0.54 0.46 1.37 1.50 3.30 4.18 0.32 0.55 1.16 0.89 4.10 3.61 

CD at 

5 % 

1.12 0.96 2.84 3.12 6.84 8.68 0.66 1.14 2.42 1.86 8.50 7.50 

15


Table 7. Influence of integrated nutrient management practices on uptake of Fe (g ha -1 ) in rice-rice 


Treatments 

Tillering 

2005-06 2006-07 

Panicle 

initiation 


initiation 

Harvesting 


T 1 156.9 251.3 308.9 302.9 399.2 318.1 136.0 185.1 293.2 292.1 543.1 262.4 

T 2 239.4 277.8 578.2 510.6 658.2 671.0 152.2 223.4 314.2 461.1 984.3 769.5 

T 3 193.5 308.7 530.9 603.7 765.2 972.9 159.5 260.8 314.2 630.5 1240.3 893.3 

T 4 251.5 309.9 606.2 606.7 933.8 975.2 178.6 241.8 440.6 566.9 1274.9 746.7 

T 5 280.0 322.2 690.3 631.6 1152.6 1168.1 202.2 262.9 488.6 599.4 1479.5 977.4 

T 6 314.4 447.5 738.7 751.0 1055.9 1478.8 260.3 319.9 608.4 728.3 1665.0 1110.6 

T 7 349.9 393.8 781.5 711.3 1105.3 1297.5 251.1 290.5 593.0 623.5 1577.9 1073.2 

T 8 231.9 365.5 489.5 666.3 719.0 1193.9 208.3 287.0 412.0 667.9 1125.0 991.3 

T 9 287.3 330.3 597.8 566.2 707.4 1068.9 209.8 262.8 400.0 590.2 1107.6 908.2 

T 10 362.4 448.5 773.2 754.8 1099.0 1391.7 275.7 315.2 630.6 770.6 1721.6 1057.2 

T 11 355.7 457.1 756.0 704.9 1183.0 1382.3 306.5 303.6 618.2 656.8 1598.7 886.0 

T 12 274.8 320.8 569.5 546.7 798.0 870.5 199.4 241.1 390.8 534.0 1109.2 694.4 

SEM + 1.1 8.1 35.0 39.1 46.3 68.7 6.2 12.3 11.0 41.1 120.5 7.7 

CD at 

5 % 

22.6 18.8 72.6 81.2 96.0 142.6 12.8 25.4 22.8 85.2 250.0 160.8 

Table 8. Influence of integrated nutrient management practices on uptake of Mn (g ha -1 ) in rice-rice 


Treat 

ments 

Tillering 

2005-06 2006-07 

Panicle 

initiation 


initiation 

Harvesting 


T 1 187.4 269.8 384.9 328.5 137.0 324.6 154.9 192.1 351.9 313.6 474.7 215.7 

T 2 276.0 287.4 629.9 525.1 574.9 676.8 183.1 232.3 374.7 483.3 784.5 643.7 

T 3 222.8 312.9 618.8 616.2 767.5 940.5 191.7 270.3 381.9 660.8 993.9 746.9 

T 4 286.9 322.2 695.5 618.7 935.2 964.8 211.2 251.0 536.4 626.6 1099.3 647.2 

T 5 300.2 346.0 811.4 682.7 1222.4 1170.1 243.3 273.7 584.4 673.3 1343.0 845.1 

T 6 332.6 438.5 802.5 751.2 1009.2 1432.9 267.7 338.8 608.4 807.4 1516.4 965.6 

T 7 371.5 400.0 812.0 711.3 961.5 1270.3 261.7 290.3 576.1 713.8 1349.3 914.44 

T 8 225.7 373.9 519.5 670.3 729.0 1146.9 204.6 311.1 412.0 730.2 1011.6 867.4 

T 9 276.3 334.3 653.2 614.6 771.12 1060.3 208.7 273.5 399.6 656.2 1017.3 862.6 

T 10 354.5 436.7 859.7 780.8 1215 1423.6 274.1 334.7 630.6 843.6 1576.6 988.1 

T 11 355.7 449.6 802.1 736.2 1285.8 1347.4 293.8 322.8 613.9 756.9 1454.1 883.3 

T 12 266.9 318.8 628.4 572.11 791.1 894.2 202.1 249.4 421.8 545.0 928.4 807.1 

SEM + 13.6 7.7 61.0 45.8 90.3 106.5 12.7 29.8 35.7 58.0 66.2 112.8 

CD at 5 % 28.3 16.0 126.6 95.0 166.5 220.8 26.4 61.8 74.0 120.4 116.5 234.0 

16


REFERENCES 

Rajeev Kumar, Singh, K.P and Sarkar, A K 1993. 

Cumulative effects of cropping and fertilizer 

use on the status of micronutrients in soil and 

crop. Fertilizer News. 38(11): 13-17. 

Santhy, P., Jayashree Sankar, S., Muthuvel, P and 

Selvi, D. 1998. Long term fertilizer experiments 

– status of N, P and K fractions in soil, Journal 

of Indian Society Soil Science 46(3): 395-398. 

Singh, N.P., Sachan, R.S., Pandey, P.Cand Bisht, 

P.S. 1999. Effect of decade long fertilizer and 

manure application on soil fertility and 

productivity of rice – wheat system in a 

Mollisol. Journal of Indian Society of soil 

Science 48(1):72-79. 

Tandon, H.L.S. 1995, Methods of analysis of soils, 

plants, water and fertilizers FDCO, New Delhi, 

pp.143. 

17


CHANGES IN MATURITY INDICES DURING VERMICOMPSOTING VS 

CONVENTIONAL COMPOSTING OF AGRICULTURAL WASTES 

CH. S. RAMA LAKSHMI, P.C. RAO, G.PADMAJA, T.SREELATHA, 

M.MADHAVI, P.V.RAO and A. SIREESHA 

Regional Agricultural Research Station, ANGR Agricultural University, Anakapalle - 531001 


ABSTRACT 

The present investigation was carried out at Regional Agricultural Research Station, Anakapalle during 

2009 to monitor the changes in maturity indices i.e total organic carbon, total nitrogen, C/N ratio, humic substances 

and humification index during conventional method of composting and vermicomposting of different organic residues 

i.e sugarcane trash, weeds, vegetable market waste and paddy straw. The results revealed that the total organic 

carbon decreased with the passage of time during vermicomposting and conventional composting in all the organic 

residues. However the percent decrease was more in vermicomposting than conventional composting in a particular 

period of time. The total nitrogen content of different vermicomposts and conventional composts increased during 

composting process, high increase was observed in vermicomposting than conventional composting. Total Nitrogen 

content in both the composts was higher in vegetable market waste and lower in paddy straw. C/N ratio decreased 

with the passage of time during vermicomposting and conventional composting in all the organic residues, however 

paddy straw recorded the highest C/N ratio while vegetable market waste exhibited lowest C/N ratio. The humic and 

fulvic production increased with incubation in both the composting methods and in all the treatments, yield of humic 

acid was maximum from the vegetable market waste vermicompost followed by weed vermicompost. Minimum per 

cent of humic substances were recorded with cane trash and rice straw. A well known index for humification is the 

HA/FA ratio, in both the composts paddy straw compost recorded low ratio and high ratio was recorded in vegetable 

market waste compost. Thus, Vermicomposting offers a promising solution for the recycling of organic wastes into 

valuable organic manure with in a short period of time over conventional composting. 

The recycling of crop residues and organic 

wastes through composting is the key technology 

for production of organic manures. Vermicomposting 

offers a promising for the recycling of organic wastes. 

Present study is the comparative assessment of 

vermicomposting and composting for their maturity 

indices The study was carried out at Regional 

Agricultural Research Station, Anakapalle, 

Visakhapatnam district during 2009. 

The basic raw materials used for composting 

and vermicomposting were 

1) Sugarcane trash, 2) Weeds (Cyperus rot 

undus,Cynodon dactylon,Cleome viscosa, Com 

malina bengalensis and Trianthema portul acastrum) 

3) Vegetable market waste and 4) Paddy straw. In 

case of Earthworm species Eisenia foetida was 

used for vermicomposting @ 1 kg per ton of organic 

residue and 1 % N as urea and 2 % SSP were used 

as chemical additives for conventional composting. 

Both methods of composting were carried out in 

cement pits with 6 x 2 x 0.6 m size. The compost 

samples at 15, 30, 45 and 60 days interval for 

vermicomposts and 15, 30, 45, 60 and 110 days 

interval for composting composts were collected from 

each treatment for laboratory analysis. 

The organic residues used for vermi 

composting and conventional composting were 

analysed for their maturity indices by using standard 

procedures as pH and was Electrical Conductivity 

(dSm -1 ) determined in 1 : 50 organic material (dried 

and powdered) and water suspension by using 

combined glass electrode pH meter and EC meter 

(Jackson, 1973). Organic carbon content was 

determined by using dry combustion method 

(Jackson, 1973). The total nitrogen content (%) in 

the dried compost sample was determined by 

microkjeldahl distillation method after destroying the 

organic matter using H 2 

SO 4 

and H 2 

O 2 

(Piper, 1966). 

C/N ratio was calculated from the above parameters. 

Extraction, fractionation and purification of compost 

samples. The humic substances were isolated, 

extracted and purified by following Tyurin’s method 

email: sitaramalakshmi20@yahoo.com 

18

LAKSHMI et al 

Fig 1. Changes in C/N ratio during 

vermicomposting 

Fig 2. Changes in C/N ratio during 

conventional composting 

Fig 3. 

Changes in humic acid content 

(%) during vermicomposting 

Fig. 4 Changes in humic acid content 

(%) during conventional composting 

18 19A

CHANGES IN MATURITY INDICES DURING VERMICOMPSOTING VS CONVENTIONAL 

as described by Kononova (1966). Humification index 

was computed from ratio of humic acid to fulvic acid. 


The organic residues used in the study were 

neutral in reaction with non saline electrical 

conductivity. Total organic carbon and C/N ratio varied 

from 35.22 (vegetable market waste) to 37.05 % 

(paddy straw) and 22.29 : 1 (vegetable market waste) 

to 68.61 : 1 (paddy straw), respectively. Regarding 

macro nutrient status of the organic residues, 0.54 

(paddy straw) to 1.58 (vegetable market waste) % N, 

0.10 (paddy straw) to 0.81 (vegetable market 

waste) % P and 0.90 (weeds) to 1.10 (cane trash) % 

K was recorded. 

Changes in total organic carbon (TOC) 

during vermicomposting and composting 

The total organic carbon content (%) of all 

the organic residues showed decreasing trend during 

both the methods of composting i.e vermicomposting 

and conventional composting (Table 1 and 2). The 

total organic carbon content during vermicomposting 

varied from 32.28 (vegetable market waste) to 36.89 

(paddy straw) on 15 th day, while on 60 th day, it was 

varied from 23.88 (weeds) to 24.62 % (cane trash). 

In case of conventional composting, the total organic 

carbon content ranged between 32.45 (vegetable 

market waste) to 36.50 (paddy straw) on 15 th day, 

while on 110 th day, they varied from 23.05 (vegetable 

market waste) to 24.22 (cane trash). Total organic 

carbon decreased with the passage of time in all the 

organic residues and in both the composting methods. 

Total organic carbon content decreased with the 

decomposition during vermicomposting and 

composting in all the organic residues, might be due 

to total organic carbon is lost as carbon dioxide 

through microbial respiration and mineralization of 

organic matter causing increase in total nitrogen, part 

of the carbon in the decomposing residues released 

as CO 2 

and part was assimilated by the microbial 

biomass, microorganisms used the carbon as a 

source of energy and decomposing the organic matter 

(Swathi Pattnaik and Vikram Reddy, 2010). The 

reduction was higher in vermicomposting as compared 

to composting at a particular period of time, which 

may be due to the fact that earthworms have higher 

assimilating capacity and the earthworms affect the 

loss of carbon in the form of carbon dioxide through 

mineralization of organic carbon (Swathi Pattnaik and 

Vikram Reddy, 2010). 

Changes in total nitrogen during 

vermicomposting and conventional composting 

The changes in total nitrogen content during 

vermicomposting from 15 to 60 days were 0.62 to 

1.14 % (cane trash), 1.30 to 1.88 % (weeds), 1.58 to 

2.11 % (vegetable market waste) and 0.51 to 1.12 % 

(paddy straw). In case of conventional composting 

from 15 to 110 days, it was varied from 0.63 to 0.98 

% (cane trash), 1.34 to 1.68 % (weeds), 1.61 to 1.81 

% (vegetable market waste) and 0.53 to 0.96 % 

(paddy straw). The total nitrogen content increased 

during composting process, however more increase 

was observed in vermicomposting than normal 

composting. Irrespective of the composting methods, 

significantly higher and lower nitrogen content was 

recorded in vegetable market waste and paddy straw, 

respectively. 

The increase in nitrogen content during 

vermicomposting was due to decomposition of organic 

matter containing proteins and conversion of 

ammonical nitrogen to nitrate nitrogen. As the organic 

matter passes through the gut of the earthworms, 

the material gets digested by enzyme activity which 

results in breakdown of proteins and nitrogen 

containing compounds. Decrease in pH is another 

important factor in retention of nitrogen as it is lost 

as ammonia at high pH values. The increase in total 

nitrogen content during conventional composting may 

be due to direct manifestation of mass loss due to 

mineralization of organic fraction (Krishna Murthy et 

al., 2010). Lower nitrogen values during conventional 

composting than vermicomposting might be due to 

loss of nitrogen in the form of ammonia volatilization 

during thermophilic phase. Higher nitrogen values in 

vermicomposting might be due to high degree of 

decomposition and release of nitrogenous products 

through excreta, urine and mucoproteins (Kitturmath 

et al. 2007). 

20

LAKSHMI et al 

Changes in C/N ratio during 

vermicomposting and conventional composting 

The data presented in Table 1 and 2 revealed 

that the C/N ratio of cane trash, weeds, vegetable 

market waste and paddy straw at 15 days of 

vermicomposting was 57.74:1, 25.69:1, 20.43:1 and 

72.33:1, respectively. At the end of vermicomposting 

i.e at 60 days the C/N ratio was further reduced to 

21.60:1,12.70:1,11.34:1 and 21.57:1 in cane trash, 

weeds, vegetable market waste and paddy straw, 

respectively. Where as in conventional composting 

the C/N ratio at 15 days was 57.02:1, 24.87:1, 20.16:1 

and 68.87:1, respectively and 60 days after 

composting the reduction was 34.63:1, 16.56:1, 

14.19:1 and 36.08:1 and at the end of composting 

i.e. at 110 days it was further reduced to 24.71:1, 

13.76:1, 12.73:1 and 24.89:1 in cane trash, weeds, 

vegetable market waste and paddy straw, 

respectively. In both the composting methods paddy 

straw recorded the highest C/N ratio while vegetable 

market waste exhibited lowest C/N ratio, however 

the percent decrease was more in vermicomposting 

than conventional composting in a particular period 

of time (Fig.1 & 2). 

The decrease in C/N ratio during 

vermicomposting was due to respiratory activity of 

earthworms and microorganisms and increase in 

nitrogen by mineralization of organic matter and 

excretion of nitrogenous wastes. Similar results were 

reported by Alok Bhardwaj (2010). The reduction in 

carbon and lowering of C/N ratio in the 

vermicomposting and conventional composting could 

be achieved either by the respiratory activity of 

earthworms and microorganisms or by increase in 

nitrogen by microbial mineralization of organic matter 

in combination with addition of the worm’s nitrogenous 

wastes through their excretion. The rate of reduction 

of C/N ratio was high during vermicomposting than 

conventional composting. The duration of 

vermicomposting varied from 55 to 60 days for 

various organic residues under study, while it took 

almost 110 days for conventional composting (Auldry 

et al., 2009). During vermicomposting given optimum 

conditions of temperature and moisture, earthworms 

feed on organic component of organic residues which 

is ground into smaller particles in their gizzard. Later 

on the enzyme activity in the intestine brings about 

rapid conversion of cellulose and protenaceous 

materials. This may account for reduced time in 

vermicomposting than conventional composting. 

Changes in Humic Acid content (%) 


The humic acid production increased with progress 

of decomposition in both the composting methods. 

The increase in humic acid content in 

vermicomposting from 15 to 60 days varied from 7.50 

to 9.85 % in cane trash, 8.12 to 10.40 % in weeds, 

9.00 to 10.85 % in vegetable market waste and 7.12 

to 9.10 % in paddy straw. At the end of 

vermicomposting significant increase in humic acid 

content (10.40 %) was recorded in vegetable market 

waste than cane trash and paddy straw, however 

vermicomposting of weeds recorded on par result 

(10.40 %) with vegetable market waste, while 

significantly lowest humic acid (9.10 %) was recorded 

in paddy straw. At the end of conventional composting 

i.e 110 days high humic acid content of 10.22 % 

was observed in vegetable market waste, while 

minimum content of 9.75 % was recorded in cane 

trash. Vegetable market waste recorded 20 & 25 % 

increase of humic acid content from initial to maturity 

in vermicomposting and conventional composting, 

respectively. 

The humic acid production increased with 

incubation in both the composting methods and in all 

the treatments, Xiaowei et al. (2010) observed that 

increasing levels of humic acid represent high degree 

of humification. Humification was found to be 

dependent on biochemical characteristics and 

composition of raw material. The high humic acid 

content during vermicomposting implies good quality 

and maturity of compost. Vegetable market waste 

recorded highest humic acid content (10.85 %) 

followed by weeds (10.40%), cane trash (9.85 %,) 

and rice straw (9.10 %) during vermicomposting. This 

was probably due to variation in the amount, 

composition and differential degradation of lignins 

(Tejada, 2009) (Fig.3 & 4) 

Changes in Fulvic Acid content (%) 


21

CHANGES IN MATURITY INDICES DURING VERMICOMPOSTING VS CONVENTIONAL 

Table 1. Changes in contents of total organic carbon (TOC), total nitrogen (TN) and C/N ratio (vermicomposting) at different time intervals 

S.E.m+ 

CD at (5%) 

Table 2. Changes in contents of total organic carbon (TOC), total nitrogen (TN) and C/N ratio (conventional) composting at different time intervals 

CD at 

(5%) 

22

LAKSHMI et al 

Table 3. Changes in humic acid (HA), fulvic acid (FA) and humic acid/fulvic acid ratio during vermicomposting at different time intervals 

Table 4. Changes in humic acid (HA), fulvic acid (FA) and humic acid/fulvic acid ratio during conventional composting at different time intervals 

23

CHANGES IN MATURITY INDICES DURING VERMICOMPOSTING VS CONVENTIONAL 

During vermicomposting the change in fulvic 

acid content from 15 to 60 days varied from 2.58 to 

2.42 % in cane trash, 2.56 to 2.41 % in weeds, 2.61 

to 2.50 % in vegetable market waste and 2.11 to 

2.08 % in paddy straw. In conventional composting 

the changes in fulvic acid content from 15 to 110 

days were 2.18 to 2.16 % in cane trash, 2.28 to 2.22 

% in weeds, 2.29 to 2.26 % in vegetable market waste 

and 2.17 to 2.15 % in paddy straw. Higher fulvic acid 

content was recorded in vermicomposting than 

conventional composting. With the progress of 

decomposition fulvic acid did not followed any 

particular trend in both the methods of composting. 

Krishna Murthy et al. (2010) were of the opinion that 

low fulvic acid and high humic acid percentage were 

the indications that the compost has reached an 

advanced stage of maturity and also stated that the 

compost quality increased with increasing humic acid 

percentage. 

Changes in humic acid/fulvic acid ratio (HA/ 

FA ratio) during vermicomposting and composting 

The humification index (HI), which is the ratio between 

the humic acid and fulvic acid, is believed to be a 

good maturity and stability index. The changes in 

humic acid/fulvic acid ratio during vermicomposting 

and conventional composting were presented in Table 

3 and 4. During vermicomposting the HA/FA ratio 

varied from 2.91 (cane trash) to 3.45 (vegetable 

market waste) at 15 days and 3.72 (paddy straw) to 

4.34 (vegetable market waste) at 60 days, where as 

in conventional composting it was ranged between 

3.46 to 3.56 at 15 days and 4.23 to 4.55 at 110 days. 

In both the composting methods minimum HA/FA 

ratio was recorded in paddy straw and maximum ratio 

was recorded in vegetable market waste. The 

increase in humic acid to fulvic acid ratio reflects 

the formation of complex molecules (humic acids) 

from more simple molecules (fulvic acids). Similar 

increase in humic acid/fulvic acid ratio during 

incubation of organic residues was observed by 

Xiaowei et al., (2010). 

REFERENCES 

Alok Bhardwaj. 2010. Management of kitchen waste 

material through vermicomposting. Asian 

Journal of Experimental Biological Sciences. 

1 (1): 175-177. 

Auldry Chaddy Petrus., Osumanu Haruna Ahmed and 

Ab Majid Nik Muhamad. 2009. Chemical 

characteristics of compost and humic acid 

from sago waste. American Journal of Applied 

Science. 6(11): 1880-1884. 

Jackson ML. 1973. Soil Chemical Analysis. Prentice 

Hall of India Pvt. Ltd., New Delhi PP:1-485. 

Kitturmath, M.S., Giraddi, R.S and Basavaraj, B. 

2007. Nutrient changes during earthworm- 

Eudrilus eugeniae mediated vermicomposting 

of Agro-industrial wastes. Karnataka Journal 

of Agricultural Sciences. 20(3): 653-654. 

Kononova, M.M. 1966. Soil organic matter, its nature, 

origin and role in soil fertility. 2 nd Edition, 

Pergamon Press. Oxford. PP:400-410. 

Krishna Murthy, R., Sreenivasan, N and Prakash, 

S.S. 2010. Chemical and biochemical 

properties of Parthenium and Chormolaena 

compost. International Journal of Science and 

Nature. 1(2): 166-171. 

Manuel Tejada, Ana Maria Garcia-Martinez and Juan 

Parrado. 2009. Relationships between 

biological and chemical parameters on the 

composting of a municipal solid waste. 

Bioresource Technology. 100: 4062-4065. 

Piper, C.S. 1966. Soil and Plant Analysis. Hans 

Publishers, Bombay 

Swati Pattnaik and Vikram Reddy, M. 2010. Nutrient 

status of vermicompost of urban green waste 

processed by three earthworm species- 

Eisenia foetida, Eudrilus eugeniae and 

Perionyx excavatus. Applied and 

Environmental Soil Science. 

Xiaowei, Li., Meiyan Xing., Jian Yang and Zhidong 

Huang. 2010. Compositional and functional 

features of humic acid like fractions from 

vermicomposting of sewage sludge and 

cowdung. Journal of Hazardous material. 

185(2,3): 740-748. 

24


INFLUENCE OF INTEGRATED NUTRIENT MANAGEMENT ON PHYSICAL 

PROPERTIES OF ALFISOLS UNDER RICE –RICE CROPPING SYSTEM IN 

SOUTHERN TELANGANA ZONE 


DAATT Centre, Krishna District, Machilipatnam - 521002 

Date of Receipt :07.12.2012 Date of Acceptance : 31.01.2013 

ABSTRACT 

Studies were conducted to understand the influence of integrated nutrient management on physical properties 

of Alfisols under rice-rice cropping system during 2005-06 and 2006-07 at Agricultural College Farm, Rajendranagar, 

Hyderabad. The bulk density, porosity and water holding capacity did not change significantly by the application of 

different levels of fertilizers in both kharif and rabi season compared to the unfertilized soil. The application of 50% 

recommended dose of 120:60:60 kg ha -1 NPK integrated with 50% N fertilizer equivalent through FYM, paddy straw 

or glyricidia in kharif season followed by the application of recommended dose of 120:60:60 kg NPK ha -1 through 

fertilizers in rabi season significantly reduced the bulk density and porosity in the upper 0-15 cm and increased the 

water holding capacity upto 30 cm depth. Similar change in the physical properties was observed due to application 

of 75% recommended dose of fertilizers integrated with 25% N fertilizer equivalent through any one of the three 

organic sources in kharif season and application of 75% recommended dose of fertilizers in rabi. The improvement 

in the rate of infiltration of water and hydraulic conductivity was recorded only at the transplanting stage and was not 

consistent during the two seasons. 

The soil physical properties play an 

important role in determining its suitability for crop 

production. Soil should be physically fertile to provide 

a good crop growth medium. This is greatly influenced 

by several management practices. Soil physical 

properties such as water holding capacity, bulk 

density, total porosity, air-filled porosity, hydraulic 

conductivity, and soil-depth greatly influence root 

development which in turn influence plant growth and 

performance. Rice –rice is the most predominant 

cropping system in the Andhra Pradesh, particularly 

in southern telangana zone. The major problem is 

the deterioration of soil physical properties due to 

continuous puddling and impaired soil fertility due to 

indiscriminate application of nutrients through the 

fertilizers with the threat of the declining productivity. 

The use of locally available organic sources 

has higher potential to improve the soil physical 

properties that is in terms of water holding capacity, 

soil porosity and bulk density, soil fertility and there 

by soil quality as a whole sustain the level of crop 

productivity in the Rice –rice cropping system. 

Hence, an investigation was made to understand the 

influence of integrated nutrient management (INM) 

on physical properties of Alfisols under rice-rice 

cropping system. 


The Present studies were conducted in two 

consecutive years 2005-06 and 2006-07 at 

Agricultural College Farm, Rajendranagar, 

Hyderabad. The experiment was conducted on a 

sandy clay loam soil on which only rice was grown 

continuously in both Kharif and Rabi seasons since 

1988. The experiments were laid out in randomized 

block design with 12 treatments in three replications. 

Rice variety; RNR 23064 was planted adopting a 

spacing of 20 cm x 10 cm in 59.8 m 2 sized plot. The 

treatments comprised of control treatment with out 

fertilizers and organic manures (T 1 

), 50 % 

Recommended NPK dose through fertilizers (T 2 

), 50 

% Recommended NPK dose through fertilizers (T 3 

), 

75 % Recommended NPK dose through fertilizers 

(T 4 

), 100 % Recommended NPK dose through 

fertilizers 120:60:60 kg ha -1 (T 5 

), 50 % Recommended 

NPK dose through fertilizers + 50 % N through FYM 

(T 6 


fertilizers + 25 % N through FYM (T 7 

), 50 % 

Recommended NPK dose through fertilizers + 50 % 

N through paddy straw (T 8 

), 75 % Recommended 

NPK dose through fertilizers + 25 % N through paddy 

straw (T 9 


fertilizers + 50 % N through glyricidia (T 10 

), 75 % 

Recommended NPK dose through fertilizers + 25 % 

email: vemulamadamp@gmail.com 

25

INFLUENCE OF INM ON PHYSICAL PROPERTIES 

N through glyricidia (T 11 

) and Conventional farmers 

practice 80:50:20 kg ha -1 NPK (T 12 

) during kharif. While 

the treatments during rabi were; control treatment with 

out fertilizers and organic manures (T 1 

), 50 % 

recommended NPK dose through fertilizers (T 2 

), 100 

% recommended NPK dose through fertilizers (T 3 

), 

75 % recommended NPK dose through organic 

manures (T 4 

), 100 % Recommended NPK dose 

through fertilizers 120:60:60 kg ha -1 (T 5 

), 100 % 

recommended NPK dose through fertilizers (T 6 

), 75 

% recommended NPK dose through fertilizers (T 7 

), 

100 % Recommended NPK dose through fertilizers 

(T 8 


fertilizers (T 9 

), 100 % Recommended NPK dose 

through fertilizers (T 10 

), 75 % Recommended NPK 

dose through fertilizers (T 11 

) and Conventional 

(farmers) practice 80:50:20 kg ha -1 NPK (T 12 

). 

Sample Collection 

The soil samples were collected with soil 

auger at random from each treatment plot at 0-15 

and 15-30 cm depth before transplanting, panicle 

initiation and harvesting stages of the crop in each 

season. The soil samples were dried under shade, 

powdered using wooden mortar and pestle and then 

passed through a 2 mm sieve before taking up 

analysis. Soil samples were collected with core 

sampler of size 5.25 x 6 cm to determine soil bulk 

density by using the method suggested by Black 

(1965). Porosity was calculated by using the formula: 

Porosity = [1-BD/PD] x 100; Where, BD = Bulk 

density of soil (Mg m -3 ); PD = Particle density (Mg 

m -3 ) of soil. 

Undisturbed soil samples collected in 

cylindrical cores at different stages from 0-15 and 

15-30 cm depths were used for the determination of 

hydraulic conductivity using constant pressure head 

method as per the procedure outlined by Jalota et al. 

(1998). Infiltration rate was determined in situ, at the 

time of sowing, 60 DAS and harvest of the crop with 

double ring infiltrometer as suggested by Bertrand 

(1965) and described by Jalota et al. (1998) and the 

infiltration rate was reported as cm hr -1 . The Water 

Holding Capacity of soils was estimated by Keens 

Cup method (Black, 1965). Grain yield was recorded 

at the end of each season for two years. 


Bulk density 

The data on bulk density of soil in the surface 

layer upto 15 cm depth in response to different 

nutrient management treatments is furnished in Table 

1. The trend exhibited a progressive increase in the 

bulk density with advance in age of the crop from 

transplanting to panicle initiation and at harvest in all 

the treatments during the 2005-06 as well as 2006- 

07. The soil cultivated with rice without the application 

of fertilizer or manures had low bulk density of 1.53 

g cm -3 at the time of transplanting both during kharif 

and rabi seasons in 2005-06. No significant difference 

was recorded by the application of different 

proportions of fertilizers in kharif and rabi seasons 

compared to un fertilized soil. But the integrated 

supply of nutrients by substituting 50 or 25 % N 

fertilizer with FYM in the rainy season dropped down 

the bulk density significantly. The substitution of 50 

or 25 % N through paddy straw or glyricidia in kharif 

season and application of recommended or 75 % 

recommended N P K dose in rabi after the respective 

kharif season treatments significantly reduced the 

bulk density of the soil at transplanting compared to 

control both during 2005-06 and 2006-07. The 

reduction in the bulk density of the soil was also 

recorded at the panicle initiation and at harvesting of 

the crop due to the integrated nutrient management 

in kharif season and fertilizer application in rabi 

season compared to the fertilized or unfertilized soil. 

The layer at 15 - 30 cm invariably recorded higher 

bulk density than the top layer irrespective of the 

treatment (Table 2). Unlike in the top layer, the 

substitution of 50 or 25 % N through organic sources 

had no significant influence on this variable at any 

stage of the crop growth either in kharif or rabi season 

during 2005-06 or in 2006-07. 

The bulk density of the soil was relatively 

low at transplanting, but it increased at panicle 

initiation and harvesting stage of the crop consequent 

to the settlement of the soil and trafficking by human 

labour for cultural operations both during kharif and 

rabi in the two years. As a result, the porosity and 

water holding capacity reduced from transplanting to 

harvesting stage of the crop. This inverse relationship 

26


of bulk density with these two parameters is an oft - 

cited phenomenon (Tripathi et al., 2003). Chawla 

and Chhabra (1991) also reported that the continuous 

application of N fertilizer had no significant influence 

on this soil physical parameter. However, the present 

study confirmed that the co application of organic 

source of nutrients by partly replacing the chemical 

fertilizers had a subtle advantage to improve the soil 

physical properties. The substitution of 50 % N 

fertilizer through FYM, paddy straw or glyricidia in 

kharif and the application of recommended dose of 

fertilizers in rabi or the substitution of 25 % N fertilizer 

with any one of the three organic sources in kharif 

and the application of 75 % recommended dose of 

fertilizers in the rabi season significantly reduced the 

bulk density at transplanting, panicle initiation and 

harvesting stage of rice continuously during the four 

seasons in the biologically active rooting depth of 0- 

15 cm. This reduction in bulk density could probably 

be assigned to the reason that the addition of organic 

matter increased the volume of the soil per unit 

weight. Such benefit of reduction in bulk density of 

the soil through the incorporation of organic matter 

has been well documented by Vasanthi and 

Kumarswamy (1999). 

Porosity 

The soil was more porous at 0-15 cm soil 

depth in all the treatments at transplanting than at 

panicle initiation stage both in kharif and rabi seasons 

(Table 3). It reduced further at harvest. The porosity 

was 42.64 and 41.89 % at transplanting in kharif 2005 

and 2006, respectively by growing rice without the 

application of manures or fertilizers. The 

corresponding values were 42.26 and 41.89 % in rabi 

season of 2005 and 2006 respectively. The 

continuous application of recommended dose of 

fertilizers to rice-rice cropping system had no 

significant influence and substitution of 50 % N 

through the organics i.e. FYM, paddy straw and 

glyricidia in kharif season and the application of 

recommended dose of NPK through fertilizers in rabi 

season significantly increased the porosity of the soil 

during both the seasons. The application of 25 % N 

through the organics in the kharif season and 75 % 

recommended NPK through fertilizers in the rabi 

season also made the soil more porous than the 

unfertilised soil. 

The porosity was significantly more than in 

unfertilized soils due to the carry over effect of 

integrated nutrient management treatments. The 

trends were persistent at transplanting, panicle 

initiation and harvest. The porosity was relatively low 

in the lower layer of 15-30 cm soil depth (Table 4). 

The porosity increased significantly at transplanting 

by the substitution of 50 % recommended level of N 

with FYM compared to continuous fertilizer 

application at recommended level in the kharif and 

rabi season during both the years. This improvement 

also persisted at panicle initiation and harvesting 

stage in kharif and rabi seasons during the second 

year. The trends with the other sources of organic 

nutrients substituted with 25 or 50 % of the 

recommended level of N were highly irregular. 

The porosity of the fertilized soil was similar 

to the unfertilized soil. But, a magnificent 

improvement in the volume fraction of pores was 

evident due to the integrated nutrient management 

of rice in kharif followed by fertilizer application in 

rabi season during the two year rice-rice cropping 

sequence. This trend was obviously due to an 

increase in the volume of pore space because of the 

addition of organic matter to the total volume of the 

soil. But, Katele et al., (1992) observed that the 

addition of FYM in an alfisol did not bring a significant 

change in this parameter. Bhagat et al. (2003) and 

Tripathi et al (2003) also observed that the 

incorporation of Lantana camera into the soil reduced 

the bulk density and increased the porosity which in 

turn improved the retention of water. 

Infiltration 

There was a distinct response of significant 

improvement in infiltration of water at transplanting 

due to substitution of 25 or 50 % recommended level 

of N with FYM compared to the practice of 

recommended level of fertilizer application both in 

kharif and rabi season during the two years (Table 

5). The substitution of 25 % recommended level of N 

with glyricidia also established similar trend. The 

response due to the integration of organic nutrients 

through paddy straw was irregular. The differences 

in infiltration due to fertilizer application and the 

integration of organic nutrients were not apparent 

during the panicle initiation and harvesting stage of 

the crop in either of the two years. Among the organic 

27


sources FYM, had a consistent response to improve 

the infiltration of water significantly atleast during the 

part of rice growing period. Kumar et al., (1992) also 

recorded significant improvement in infiltration rate 

of water due to integrated nutrient management of 

nutrients in rice-wheat cropping system. 

Hydraulic conductivity 

The hydraulic conductivity of the soil supplied 

with different levels of fertilizers ranged from 0.25 to 

0.27 cm h -1 at transplanting in kharif season during 

2005-06 and from 0.23 to 0.25 cm h -1 in the 

subsequent rabi (Table 6). A significant improvement 

in this physical property of the soil was recorded both 

in kharif and rabi due to the substitution of FYM @ 

25 % N fertilizer equivalent in kharif. But the 

substitution of 25 or 50 % recommended level of N 

through glyricidia significantly improved the hydraulic 

conductivity both in kharif and rabi seasons during 

the second year. The hydraulic conductivity was 

significantly low in the kharif season in the fertilizer 

treatments than in integrated nutrient management 

treatments by substituting 25 or 50 % recommended 

level of NPK through FYM or glyricidia only in the 

second year. Such improvement was not recorded 

in the rabi season during both the years. No significant 

variation in the hydraulic conductivity in the surface 

soil upto 15 cm depth was recorded either in kharif or 

rabi season at harvest stage of the crop during 2005- 

06 or 2006-07. 

The hydraulic conductivity was invariably low 

in the lower (15 – 30 cm) depth than upper layer of 

the soil in all the treatments at different stages of 

crop growth (Table 7). It ranged from 0.20 to 0.22 cm 

h -1 at the time of transplanting in kharif 2005 and from 

0.19 to 0.21 cm h -1 during 2006 due to different levels 

of fertilizer application. During the subsequent growth 

phases of panicle initiation and harvesting, hydraulic 

conductivity was similar in unfertilized, fertilized and 

integrated nutrient management treatments during 

both the years. 

Water holding capacity 

The maximum water holding capacity of the 

soil was reduced consistently with advance in age of 

the crop from transplanting to panicle initiation and 

at harvest in all the treatments (Table 8). The soil 

supplied with different levels of nutrients through the 

fertilizers held 42.04 - 42.14 % water at transplanting 

in kharif and 41.26 – 41.41 % in rabi during 2005-06. 

The water retention of the soil improved significantly 

by substituting 25 or 50 % recommended level of N 

with FYM. This effect was long lasting until harvest 

both during kharif and rabi in the first year. Paddy 

straw and glyricidia were also effective sources to 

retain more moisture at different stages of crop growth 

during the two years. The water holding capacity was 

relatively low at 15-30 than 0-15 cm soil depth 

irrespective of the treatment during both the years 

(Table 9). Unlike in the top layer, the substitution of 

organics at 25 or 50 % fertilizer N equivalent was 

distinct with significantly higher moisture content than 

in the fertilized or unfertilized plots from transplanting 

to panicle initiation stage in the kharif season. 

The water holding capacity was also best 

improved by the substitution of 50 or 25 per cent N 

fertilizer with FYM in the Kharif season. The 

improvement in this soil physical property was long 

sustained until harvest due to the cumulative 

influence of reduced bulk density, increased porosity 

vis –a- vis an increase in the infiltration and hydraulic 

conductivity of the soil during the early periods of 

crop growth. The substitution of 50 or 25 per cent N 

fertilizer with rice straw or glyricidia also in general 

had a long lasting effect in better water retention for 

good crop management. The lower 15-30 cm soil layer 

was not influenced by organic matter additions. An 

improvement in water holding capacity of the soil by 

the combined application of organic and inorganic 

source of nutrients was also recorded by Vennila and 

Muthuvel (1998). 

Grain yield 

The unfertilized crop produced low grain yield 

of 2475 and 2199 kg ha -1 in kharif and 2025 and 1545 

kg ha -1 in rabi during 2005-06 and 2006-07, 

respectively (Table 10). The fertilizer application 

benefited the crop to produce more yield. The 

production increased to 3739 and 3920 kg ha -1 in two 

seasons during 2005-06, while it increased to 2911 

and 2801 kg ha -1 in kharif and rabi in 2006-07. The 

strategy to apply 50 % recommended dose of 

fertilizers in kharif and recommended dose of 

fertilizers in rabi maintained the proportion of 

production in consonance with the increase in level 

of nutrients added. The production raised enormously 

28


to as high as 5405 kg ha -1 in rabi 2005-06 and 4105 

kg ha -1 during 2006-07 due to the high dose of 

recommended level of fertilizers. The application of 

recommended dose of fertilizers continuously in kharif 

and rabi seasons invariably produced significantly 

more grain yield. High produce of 4676 and 5890 kg 

ha -1 was realized by this treatment in the kharif and 

rabi seasons during 2005-06. Similarly, maximum 

grain yield of 3983 kg ha -1 in kharif and 3801 kg ha -1 

in rabi was realized from the optimum fertilizer 

schedule in the second year. 

The substitution of 50 % N fertilizer with 

paddy straw in kharif season reduced the grain yield 

compared to the production realized by application 

of recommended dose of fertilizers during both the 

years. The substitution of 25 % N fertilizer with paddy 

straw in kharif season reduced the grain yield 

significantly only during the second year. The 

substitution of 50 % N fertilizer with glyricidia in kharif 

season and application of recommended dose of 

fertilizers in rabi season were the best integrated 

nutrient management strategies. The substitution of 

25 % N fertilizer with glyricidia in kharif season and 


in rabi season was also highly productive. 

The results of the present investigation 

showed that the physical properties of the soil were 

influenced by different nutrient management practices. 

These effects were highly distinguished in the upper 

0-15 cm depth and were less distinct in the lower 15- 

30 cm depth. This layer wise differentiation was 

probably due to the more weathered and 

microbiologically intensive portion within which the 

organic and inorganic sources of nutrients were 

incorporated for their reactions than in the lower layer. 

Table 1. Influence of integrated nutrient management treatments on bulk density (g cm -3 ) of soil in 

rice-rice cropping system at 0-15 cm depth 

Treat 

2005-06 2006-07 

ment Transplanting Panicle Harvesting Transplanting Panicle 

initiation 

initiation 

Harvesting 


T 1 1.53 1.53 1.56 1.56 1.59 1.60 1.54 1.54 1.57 1.57 1.60 1.61 

T 2 1.54 1.54 1.57 1.56 1.60 1.60 1.55 1.55 1.58 1.58 1.61 1.62 

T 3 1.53 1.54 1.57 1.56 1.60 1.61 1.54 1.55 1.58 1.58 1.61 1.61 

T 4 1.53 1.54 1.57 1.56 1.60 1.61 1.54 1.55 1.58 1.58 1.61 1.61 

T 5 1.53 1.54 1.57 1.56 1.60 1.61 1.54 1.55 1.58 1.58 1.61 1.62 

T 6 1.43 1.45 1.45 1.47 1.61 1.49 1.44 1.43 1.46 1.45 1.48 1.47 

T 7 1.45 1.47 1.47 1.49 1.49 1.51 1.46 1.45 1.48 1.47 1.50 1.53 

T 8 1.45 1.47 1.47 1.49 1.49 1.51 1.46 1.45 1.48 1.47 1.50 1.52 

T 9 1.47 1.49 1.49 1.51 1.51 1.53 1.48 1.45 1.50 1.50 1.52 1.53 

T 10 1.46 1.48 1.49 1.50 1.51 1.52 1.47 1.45 1.50 1.47 1.52 1.54 

T 11 1.47 1.49 1.48 1.51 1.50 1.53 1.48 1.47 1.49 1.49 1.51 1.53 

T 12 1.53 1.53 1.50 1.56 1.59 1.59 1.54 1.54 1.57 1.57 1.60 1.61 

SEm + 0.03 0.03 0.03 0.02 0.03 0.03 0.02 0.02 0.03 0.02 0.30 0.30 

CD at 

5 % 

0.06 0.05 0.07 0.04 0.05 0.07 0.04 0.05 0.06 0.05 0.07 0.07 

29


Table 2 . Influence of integrated nutrient management treatments on bulk density (g cm -3 ) of soil in 

rice-rice cropping system at 15-30 cm depth 

Treatment 

Transplanting 

2005-06 2006-07 

Panicle 

initiation 

Harvesting Transplanting 

Panicle 

initiation 

Harvesting 


T 1 1.56 1.57 1.59 1.59 1.64 1.63 1.57 1.58 1.60 1.61 1.64 1.65 

T 2 1.57 1.58 1.60 1.57 1.65 1.61 1.58 1.59 1.61 1.62 1.65 1.66 

T 3 1.56 1.58 1.59 1.57 1.64 1.61 1.57 1.58 1.60 1.61 1.64 1.65 

T 4 1.56 1.58 1.59 1.57 1.64 1.61 1.57 1.58 1.60 1.61 1.64 1.66 

T 5 1.56 1.58 1.59 1.57 1.64 1.61 1.57 1.58 1.60 1.61 1.64 1.65 

T 6 1.49 1.48 1.51 1.49 1.55 1.52 1.48 1.47 1.50 1.49 1.55 1.54 

T 7 1.51 1.50 1.53 1.51 1.57 1.54 1.50 1.49 1.52 1.51 1.57 1.56 

T 8 1.51 1.50 1.53 1.51 1.57 1.54 1.50 1.49 1.52 1.51 1.57 1.56 

T 9 1.53 1.52 1.55 1.53 1.57 1.56 1.52 1.51 1.52 1.51 1.57 1.55 

T 10 1.52 1.51 1.54 1.52 1.58 1.55 1.51 1.50 1.53 1.52 1.58 1.57 

T 11 1.53 1.52 1.55 1.53 1.59 1.56 1.51 1.50 1.53 1.52 1.58 1.58 

T 12 1.56 1.57 1.59 1.60 1.64 1.64 1.57 1.58 1.60 1.60 1.65 1.66 

SEm + 0.04 0.05 0.04 0.06 0.50 0.07 0.08 0.10 0.08 0.06 0.09 0.07 

CD at 

5 % 

NS NS NS NS NS NS NS NS NS NS NS NS 

Table 3 . Influence of integrated nutrient management treatments on porosity (%) of soil in ricerice 

cropping system at 0-15 cm depth 

Treatment 

Transplanting 

2005-06 2006-07 

Panicle 

initiation 


Panicle 

initiation 

Harvesting 


T 1 42.64 42.26 41.51 41.13 40.00 39.62 41.89 41.89 40.75 40.75 39.62 39.24 

T 2 42.26 41.89 41.31 41.13 39.62 39.62 41.51 41.51 40.38 40.28 39.24 38.87 

T 3 42.64 41.89 42.26 41.13 40.75 39.24 41.51 41.89 40.38 40.28 39.24 39.24 

T 4 42.64 41.89 42.26 41.13 40.75 39.24 41.51 41.89 40.38 40.28 39.24 39.24 

T 5 42.64 41.89 42.26 41.13 40.75 39.24 41.51 41.51 40.38 40.28 39.24 39.24 

T 6 44.98 45.28 44.15 44.53 43.02 43.77 45.66 46.04 44.91 40.28 44.15 44.13 

T 7 44.15 44.53 43.40 43.77 42.26 43.02 44.91 45.28 44.15 44.53 43.40 42.26 

T 8 44.15 44.53 43.40 43.77 42.26 43.02 44.91 45.28 44.15 44.53 43.40 42.64 

T 9 43.40 43.77 42.64 43.02 41.51 42.26 44.15 44.15 43.40 43.40 42.64 42.26 

T 10 43.77 44.15 43.02 43.40 41.89 42.64 44.53 45.28 43.40 44.53 42.64 41.89 

T 11 43.40 43.77 42.64 43.02 41.51 42.66 44.15 44.53 43.77 44.53 43.02 42.26 

T 12 42.64 41.89 41.51 41.13 40.00 39.62 41.57 41.89 40.38 40.28 39.24 38.17 

SEm+ 0.17 0.79 0.12 0.76 0.26 1.04 1.10 1.36 1.30 1.32 1.37 1.14 

CD at 5 % 0.31 1.65 0.25 1.58 0.54 2.16 2.31 2.83 2.69 2.73 2.85 2.37 

30


Table 4 . Influence of integrated nutrient management treatments on porosity (%) of soil in rice-rice 

cropping system at 15-30 cm 

Treatment 

Transplanting 

2005-06 2006-07 

Panicle 

initiation 


Panicle 

initiation 

Harvesting 


T 1 41.13 40.75 40.00 10.00 38.11 38.49 40.75 40.38 39.62 39.27 38.11 38.00 

T 2 40.75 40.38 39.62 40.75 37.74 39.24 40.78 40.00 39.24 38.87 37.74 37.74 

T 3 41.33 40.38 40.00 40.75 38.11 39.24 40.38 40.38 39.62 39.24 38.11 37.26 

T 4 41.33 40.38 40.00 40.75 38.11 39.27 40.38 40.38 39.62 39.24 38.00 37.74 

T 5 41.33 40.38 40.00 40.75 38.11 39.27 40.38 40.38 39.62 39.24 38.11 37.74 

T 6 43.77 44.18 40.00 43.17 41.51 42.64 44.40 44.53 43.40 43.77 41.51 41.89 

T 7 43.02 43.40 43.02 43.02 40.75 44.89 43.40 43.77 42.64 43.02 40.75 41.13 

T 8 43.02 43.80 42.26 43.02 40.75 41.89 43.40 43.77 42.64 43.02 40.75 41.13 

T 9 42.26 42.64 42.26 42.26 40.75 41.13 42.64 43.02 42.64 43.02 40.75 41.51 

T 10 42.64 43.02 41.51 42.64 40.38 41.51 43.02 43.40 42.26 42.64 40.38 40.75 

T 11 42.26 43.64 41.51 42.26 40.00 41.13 43.02 43.40 42.26 42.64 40.38 40.75 

T 12 41.13 40.38 40.00 40.75 38.11 39.24 40.38 40.300 39.62 39.24 38.11 37.28 

SEm + 0.92 1.30 1.43 1.35 1.52 2.00 1.33 1.01 1.52 1.45 1.56 1.46 

CD at 5 % 1.87 2.68 2.95 NS 3.16 4.15 2.74 2.11 3.15 3.00 3.22 3.02 

Table 5 . Influence of integrated nutrient management treatments on infiltration (mm h -1 ) of soil in 

rice-rice cropping system 

Treatment 

Transplanting 

2005-06 2006-07 

Panicle 

initiation 

Harvesting Transplanting Panicle initiation Harvesting 


T 1 6.56 6.45 6.36 6.25 6.96 6.88 6.35 6.25 6.15 6.00 6.75 6.65 

T 2 6.58 6.47 6.37 6.26 6.98 6.85 6.37 6.27 6.17 6.06 6.77 6.67 

T 3 6.59 6.46 6.33 6.27 7.00 6.87 6.35 6.26 6.15 6.06 6.75 6.66 

T 4 6.58 6.48 6.36 6.28 6.97 6.88 6.37 6.27 6.10 6.07 6.77 6.67 

T 5 6.56 6.46 6.35 6.26 6.95 6.86 6.36 6.26 6.15 6.06 6.76 6.66 

T 6 6.75 6.66 6.55 6.46 7.01 6.85 6.56 6.46 6.47 6.26 6.97 6.86 

T 7 6.95 6.80 6.75 6.60 7.35 6.80 6.72 6.62 6.52 6.44 7.12 7.02 

T 8 6.61 6.50 6.40 6.30 7.01 6.70 6.40 6.30 6.25 6.10 6.80 6.90 

T 9 6.70 6.60 6.50 6.45 7.10 6.75 6.55 6.45 6.35 6.25 6.95 6.85 

T 10 6.62 6.52 6.42 6.35 7.00 6.75 6.42 6.32 6.22 6.14 6.82 6.75 

T 11 6.72 6.65 6.52 6.30 7.12 6.70 6.55 6.45 6.35 6.26 6.95 6.85 

T 12 6.55 6.40 6.35 6.20 6.85 6.60 6.30 6.20 6.10 6.00 6.80 6.60 

SEm + 0.07 0.09 0.08 0.07 0.17 0.16 0.09 0.09 0.21 0.15 0.31 0.24 

CD at 5 % 0.14 0.18 0.17 0.14 NS NS 0.19 0.17 NS NS NS NS 

31

INFLUENCE of INM on PHYSICAL PROPERTIES 

Table 6 . Influence of integrated nutrient management treatments on hydraulic conductivity (cm h -1 ) of 

soil in rice-rice cropping system at 0-15 cm 

Treatment 

2005-06 2006-07 

Trans Panicle Harvesting Trans Panicle Harvesting 

planting initiation 

planting initiation 


T 1 0.26 0.25 0.24 0.22 0.30 0.29 0.24 0.24 0.22 0.22 0.28 0.28 

T 2 0.25 0.24 0.23 0.21 0.29 0.28 0.23 0.23 0.21 0.21 0.27 0.27 

T 3 0.25 0.24 0.23 0.21 0.29 0.28 0.23 0.22 0.21 0.20 0.27 0.26 

T 4 0.26 0.25 0.27 0.22 0.30 0.29 0.24 0.24 0.22 0.22 0.28 0.28 

T 5 0.27 0.26 0.25 0.23 0.31 0.30 0.25 0.25 0.23 0.23 0.29 0.29 

T 6 0.29 0.28 0.27 0.25 0.33 0.32 0.27 0.26 0.25 0.24 0.31 0.30 

T 7 0.31 0.30 0.29 0.27 0.34 0.34 0.29 0.29 0.28 0.27 0.33 0.33 

T 8 0.28 0.27 0.26 0.27 0.32 0.31 0.26 0.26 0.24 0.24 0.30 0.30 

T 9 0.29 0.28 0.27 0.25 0.33 0.32 0.27 0.27 0.25 0.25 0.31 0.31 

T 10 0.29 0.28 0.27 0.25 0.33 0.32 0.28 0.27 0.25 0.25 0.32 0.31 

T 11 0.30 0.29 0.28 0.26 0.33 0.33 0.28 0.28 0.26 0.26 0.32 0.32 

T 12 0.26 0.25 0.24 0.22 0.30 0.29 0.24 0.24 0.22 0.22 0.28 0.28 

SEm + 0.01 0.01 0.22 0.18 0.19 0.16 0.02 0.08 0.09 0.21 0.15 0.17 

CD at 5 % 0.02 0.03 NS NS NS NS 0.021 0.015 0.16 NS NS NS 

Table 7 . Influence of integrated nutrient management treatments on hydraulic conductivity (cm h -1 ) of 

soil in rice-rice cropping system at 15-30 cm 

T re a tm e n t 

2 0 0 5 -0 6 2 0 0 6 -0 7 

T ra n s - P a n ic le H a rv e s tin g T ra n s - P a n ic le 

H a rv e s tin g 

p la n tin g in itia tio n 

p la n tin g in itia tio n 

K h a rif R a b i K h a rif R a b i K h a rif R a b i K h arif R a b i K h a rif R a b i K h a rif R a b i 

T 1 0 .2 1 0 .2 0 0 .1 9 0 .1 8 0 .2 5 0 .2 4 0 .2 0 0 .1 9 0 .1 8 0 .1 7 0.2 4 0.2 3 

T 2 0 .2 0 0 .1 9 0 .1 8 0 .1 7 0 .2 4 0 .2 3 0 .1 9 0 .1 8 0 .1 8 0 .1 6 0.2 3 0.2 2 

T 3 0 .2 0 0 .1 9 0 .1 8 0 .1 7 0 .2 4 0 .2 3 0 .1 9 0 .1 8 0 .1 7 0 .1 6 0.2 3 0.2 2 

T 4 0 .2 1 0 .2 0 0 .1 9 0 .1 8 0 .2 5 0 .2 4 0 .2 1 0 .1 9 0 .1 9 0 .1 7 0.2 4 0.2 3 

T 5 0 .2 2 0 .2 1 0 .2 0 0 .1 9 0 .2 6 0 .2 5 0 .2 1 0 .2 0 0 .1 9 0 .1 8 0.2 5 0.2 4 

T 6 0 .2 4 0 .2 3 0 .2 2 0 .2 1 0 .2 8 0 .2 8 0 .2 3 0 .2 1 0 .2 1 0 .1 9 0.2 8 0.2 5 

T 7 0 .2 6 0 .2 5 0 .2 4 0 .2 3 0 .3 0 0 .2 9 0 .2 5 0 .2 4 0 .2 3 0 .2 2 0.2 8 0.2 8 

T 8 0 .2 3 0 .2 2 0 .2 1 0 .2 0 0 .2 7 0 .2 6 0 .2 2 0 .2 1 0 .2 0 0 .2 0 0.2 6 0.2 5 

T 9 0 .2 4 0 .2 3 0 .2 2 0 .2 1 0 .2 8 0 .2 7 0 .2 3 0 .2 2 0 .2 1 0 .2 0 0.2 7 0.2 6 

T 1 0 0 .2 4 0 .2 3 0 .2 2 0 .2 1 0 .2 8 0 .2 7 0 .2 3 0 .2 2 0 .2 1 0 .2 0 0.2 7 0.2 6 

T 1 1 0 .2 5 0 .2 4 0 .2 3 0 .2 2 0 .2 9 0 .2 8 0 .2 4 0 .2 3 0 .2 2 0 .2 1 0.2 8 0.2 7 

T 1 2 0 .2 1 0 .2 0 0 .1 9 0 .1 8 0 .2 5 0 .2 4 0 .2 0 0 .1 9 0 .1 8 0 .1 7 0.2 4 0.2 4 

S E + 0 .0 1 0 .0 1 0 .0 2 0 .0 3 0 .0 5 0 .0 6 0 .0 2 0 .0 1 0 .0 4 0 .0 3 0.0 4 0.0 3 

C D a t 5 % 0 .0 3 0 .0 3 N S N S N S N S 0 .0 4 0 .0 2 N S N S N S N S 

32


Table 8. Influence of integrated nutrient management treatments on water holding capacity (%) of soil 

in rice-rice cropping system at 0-15 cm 

Treatment 

Transplanting 

2005-06 2006-07 

Panicle 

initiation 


Panicle 

initiation 

Harvesting 


T 1 42.04 41.74 41.00 40.51 39.02 38.25 41.63 41.21 40.20 40.05 38.11 39.00 

T 2 41.76 41.38 40.65 40.31 38.53 38.52 41.26 41.00 39.75 39.52 37.42 38.44 

T 3 42.14 41.33 41.65 40.31 39.26 38.14 41.59 41.34 39.331 39.50 38.16 38.52 

T 4 42.14 41.41 41.66 40.25 39.24 38.29 41.54 41.30 39.44 39.50 38.25 38.52 

T 5 42.10 41.26 41.55 40.28 39.28 38.42 41.63 41.05 39.39 39.50 38.14 38.38 

T 6 44.48 44.72 43.74 43.83 42.00 42.65 43.81 45.28 42.67 39.50 41.00 38.21 

T 7 43.65 44.03 42.78 43.06 41.19 42.01 43.16 45.31 41.86 44.00 40.09 43.05 

T 8 43.25 44.00 42.63 42.29 41.02 42.02 42.72 43.46 41.56 44.00 40.00 43.10 

T 9 42.95 43.20 41.98 42.81 40.14 41.16 42.44 43.21 40.00 42.95 39.24 41.00 

T 10 43.17 43.84 42.21 42.91 40.25 41.54 42.64 44.33 41.34 44.05 39.21 43.11 

T 11 42.90 43.19 41.88 42.35 40.16 41.36 42.69 43.47 40.92 44.00 39.18 42.93 

T 12 42.00 41.35 40.72 40.74 39.06 38.54 41.37 41.08 39.88 39.76 38.08 38.02 

SEm + 0.53 0.90 0.47 0.59 0.72 0.77 0.57 1.04 0.65 0.89 1.01 1.05 

CD at 5 % 1.10 1.87 0.98 1.22 1.50 1.86 1.18 2.15 1.36 1.85 2.11 2.18 

Table 9. Influence of integrated nutrient management treatments on water holding capacity (%) of soil 

in rice-rice cropping system at 15-30 cm 

Treatment 

Transplanting 

2005-06 2006-07 

Panicle 

initiation 


33 

Panicle 

initiation 

Harvesting 


T 1 40.73 40.18 39.29 39.19 38.26 37.33 40.12 39.74 38.84 38.15 37.19 36.09 

T 2 40.26 39.83 39.08 40.00 38.16 38.14 39.83 39.19 38.49 37.92 36.67 36.57 

T 3 40.79 39.80 39.17 40.02 38.21 38.21 39.80 39.45 38.46 37.92 37.15 36.00 

T 4 40.72 39.81 39.23 40.10 38.34 38.19 39.85 39.48 38.51 37.81 37.18 36.54 

T 5 40.10 39.85 39.20 40.15 38.19 38.16 39.81 39.45 39.39 37.84 37.20 36.50 

T 6 42.68 43.64 39.18 42.05 38.05 41.46 43.72 43.42 42.81 42.95 40.44 40.30 

T 7 42.34 42.86 42.29 42.18 41.05 40.75 42.61 42.67 41.72 42.06 39.86 41.00 

T 8 42.48 42.85 41.51 42.14 40.44 40.71 42.64 42.47 41.46 42.06 39.79 40.29 

T 9 41.65 42.05 41.64 41.19 40.26 40.11 41.96 42.21 41.40 42.00 39.81 40.25 

T 10 42.06 42.56 40.25 41.21 39.08 40.28 42.21 41.20 41.51 41.46 39.25 40.25 

T 11 41.84 43.10 40.36 41.20 39.17 40.19 42.36 41.20 41.59 41.46 39.18 40.30 

T 12 40.69 39.43 39.24 40.00 38.30 38.22 39.55 39.19 38.73 38.37 37.10 37.00 

SEm + 0.45 0.90 1.02 1.86 1.35 1.20 0.96 1.04 0.91 1.53 1.35 1.42 

CD at 5 % 0.94 1.86 2.12 NS NS NS 2.00 2.16 1.87 3.18 NS NS


Table 10. Influence of integrated nutrient management treatments on yield in Rice - Rice cropping 

system 

Grain yield (kg ha -1 ) 

Treatment 2005-06 2006-07 

Kharif Rabi Kharif Rabi 

T 1 2475 2025 2199 1545 

T 2 3739 3920 2911 2801 

T 3 3676 5405 3111 4150 

T 4 3891 5200 3601 3397 

T 5 4676 5890 3983 3801 

T 6 4140 5795 3782 3889 

T 7 4649 5665 3856 3582 

T 8 3856 5375 2444 3815 

T 9 4411 5230 2980 3546 

T 10 4973 6070 4052 4480 

T 11 4977 6915 4251 4244 

T 12 4371 4745 3244 3333 

SEm + 236 91 149 375 

CD at 5 % 492 191 311 783 

REFERENCES 

Bertrand, A.R. 1965. Rate of water intake in the field 

in: Measures of soil analysis by Black, C.A. 

part I Agronomy 9 : 374-390. 

Bhagat, R.M., Bhardwaj, A.K and Pradeep, K., 

Sharma. 2003. Long term Effect of Residue 

Management on soil physical properties, water 

use and yield of rice in north – western India, 

journal of the Indian Society of Soil Science, 

51 : 111-117. 

Black, C.A. 1965. Methods of soil analysis Part, 

American Society of Agronomy, Wisconsin, 

USA. Density, water contents and microbial 

population of soil. Journal of Indian Society of 

soil science 40 :553-555. 

Chawla, K.L and Chabra, R. 1991. Physical 

properties of gypsum amended sodic soils as 

affected by long term use of fertilizers. Journal 

of Indian Society of Soil Science 39 :40-46 

Jalota, S.K., Ramesh Khera and Ghuman, B.S. 1998. 

Measures in soil physics Narosa publishing 

house, New Delhi 

Katele, P., Leinweber, P and Menning, P. 1992. On 

the influence of soil organic mater on physical 

properties of soil. Agrobiological Research 

45 : 18-27 

Kumar, K., Meelu, O.P., Singh, Y and Singh, B. 1992. 

Effect of continuous application of organic 

manures on the physical properties of soils in 

rice-wheat cropping system. International Rice 

Research news Letter. 17 : 4-16. 

Tripathi, R.P., Gaur, M.K and Rawat, M.S. 2003. 

Puddling Effects on soil physical properties 

and rice performance under shallow water table 

conditions of tarai. Journal of the Indian Society 

of Soil Science, 51: 118-124 

Vasanthi, D and Kumarswamy, K. 1999. Efficacy of 

vermicompost to improve soil fertility and rice 

yield. Journal of the Indian society of soil 

science 47 : 268-272 

Vennila, R.K and Muthuvel, P. 1998. Effect of long 

term fertilization on physical properties of soils. 

Madras Agricultural Journal 85 : 290-292. 

34


GENETIC VARIABILITY, HERITABILITY AND CHARACTER ASSOCIATION 

STUDIES IN SWEET SORGHUM [Sorghum bicolor (L.) Moench] 



Department of Genetics and Plant Breeding 

Acharya N.G. Ranga Agricultural University, Hyderabad – 500 030 


ABSTRACT 

The present investigation on genetic variability, heritability and character association in large F 2 

population 

of sweet sorghum was carried out at Directorate of Sorghum Research, Rajendranagar, Hyderabad. F 1 

was generated 

during 2010 kharif and second filial generation in the following season. The mean and variance in respect of 14 

quantitative characters in F 2 

population indicated wide range of variability for most of the traits. However, variability 

range was low for the traits like nodes per plant, stem girth, brix per cent and total soluble sugars. The distribution 

pattern of this F 2 

population revealed complementary interaction in the inheritance of days to 50% flowering, days to 

maturity, plant height, total biomass, fresh stalk yield, grain yield, brix per cent, juice yield, juice extraction per cent, 

total soluble sugars, sugar yield and bioethanol yield, while inheritance of nodes per plant and stem girth exhibited 

duplicate type of epistasis. Most of these characters except days to 50% flowering and days to maturity exhibited 

high heritability coupled with moderate to high genetic advance as per cent of mean indicating predominance of 

additive gene action in their genetic control. Further, correlation studies in F 2 

generation revealed significant and 

positive correlation of fresh stalk yield with total biomass, grain yield, plant height, nodes per plant, stem girth, days 

to 50% flowering and days to maturity, while sugar yield with juice yield, fresh stalk yield, total biomass, grain yield, 

total soluble sugars, brix per cent, bioethanol yield and juice extraction per cent. These correlated traits can be 

effectively utilized in formulating indirect selection schemes. While path analysis studies revealed maximum positive 

direct effect of total soluble sugars and juice yield on sugar yield. 

The genetic improvement of quantitative 

characters in a crop species depends upon heritability 

pattern of the trait in question, nature and amount of 

variability present in the existing germplasm. 

Moreover sweet sorghum is also not an exception. 

Knowledge on the genetic advance that is expected 

by applying selection pressure to a segregating 

population is useful in designing effective breeding 

programme. Evaluation of these segregating 

progenies helps in estimation of various genetic and 

non-genetic components of variance. The study of 

variability provides an opportunity for selecting the 

desirable genotypes. Heritability is a fraction of 

variance in phenotypic expression that arises from 

genetic effects. The nature of the selection units 

and sampling errors also influences greatly the 

magnitude of heritability. The estimates of heritability 

in segregating generations help to know genetic 

variance, genotype - environment interaction and the 

progress expected from selection. 

The fresh stalk yield and sugar yield in sweet 

sorghum, as in other crops, is a complex quantitative 

character and its expression depends upon its 

component characters. The knowledge on the 

relative contribution of different yield components and 

their direct and indirect impact towards sugar yield 

is of immense value in selection of superior 

genotypes. Keeping the situations present in the 

foregoing paragraphs in view, the present investigation 

was under taken to study genetic variability, 

heritability and character association in sweet 

sorghum. 


The material for this experiment comprised 

of F 2 

population of a cross derived from parents (27 

B with SSV 84) having low and high sugar content 

developed at Directorate of Sorghum Research, 

Rajendranagar, Hyderabad during kharif 2010. The 

F 1 

plants of this cross were grown during rabi 2010 - 

11 and selfed to produce the F 2 

seeds, which were 

evaluated during summer 2012. The F 2 

segregating 

generations were grown in plots with twenty rows each 

in three separate blocks. These plants were sown in 

plots of twenty rows spaced 45 cm apart with a plant 

spacing of 15 cm with 2 - 3 seeds per hill in each row 

of 4 mt length. Thinning was done to retain one 

healthy plant per hill at 15 and 25 days after sowing. 

All the recommended package of practices was 

followed to raise a good and healthy crop. 

email: vemanraddi@gmail.com 

35

GENETIC VARIABILITY, HERITABILITY AND CHARACTER ASSOCIATION STUDIES 


The descriptive statistics and genetic 

variability parameters with respect to fourteen 

quantitative characters in F 2 

population of the cross 

‘27 B × SSV 84’ is presented in Table 1. These 

descriptive statistics, unravels basic idea of the 

breeding material. The characteristics of this F 2 

population in respect of various quantitative 

characters as indicated by these first and second 

degree statistics are discussed below. 

Wide range of variability was present for the 

traits such as plant height, total biomass, fresh stalk 

yield, grain yield, juice yield, juice extraction per cent, 

sugar yield and bioethanol yield of this cross of sweet 

sorghum studied as indicated by their respective 

mean and variances. Existence of moderate 

variability was observed for days to 50% flowering 

and days to maturity. However, the variability range 

was low for the traits like nodes per plant, stem girth, 

brix per cent and total soluble sugars. 

The study of distribution properties such as 

co-efficients of skewness (third degree statistic) and 

kurtosis (fourth degree statistic) provides insight about 

the nature of gene action and number of genes 

controlling the traits, respectively. All the studies 

reported nature of genetic control of quantitative traits 

in sorghum is based on first degree (gene effects 

through generation mean analysis) and second degree 

(components of genetic variances through diallel, line 

× tester analysis, etc.) statistics. Skewness and 

kurtosis are greater than first and second degree 

statistics which reveal interaction genetic effects. The 

skewed distribution of a trait in general suggests that 

the trait is under the control of non-additive gene 

action, especially epistasis and influenced by 

environmental variables (Kimberg and Bingham, 1998 

and Roy, 2000). Positive skewness is associated 

with complementary interaction and negative 

skewness is associated with duplicate (additive × 

additive) gene interactions predominantly in the same 

directions. Complete ambi-directional epistasis 

however produces kurtosis while distribution stays 

symmetrical around mean. The genes controlling the 

trait with skewed distribution tend to be predominantly 

dominant irrespective of whether they have increasing 

or decreasing effects on the expression of the trait. 

The traits with leptokurtic and platykurtic 

distribution are controlled by fewer and a large number 

of genes, respectively. Kurtosis is negative or close 

to zero in the absence of gene interactions and is 

positive in the presence of gene interactions. The 

inference on the relative number of genes and nature 

of genetic control of different traits in F 2 

generation 

of this sweet sorghum cross is discussed below. 

Platykurtic and positively skewed distribution 

suggested the involvement of relatively large number 

of segregating genes with dominance based 

complementary type of interaction in the inheritance 

of days to 50% flowering, days to maturity, plant 

height, total biomass, fresh stalk yield, grain yield, 

juice yield, juice extraction per cent and sugar yield 

in ‘27 B × SSV 84’ cross. Maximizing the genetic 

gain in respect of these traits with positively skewed 

distribution requires intense selection from the 

existing variability. 

The inheritance of nodes per plant and stem 

girth recorded negatively skewed platykurtic 

distribution which indicates that these traits are 

governed by large number of dominant genes with 

duplicate type of epistasis. These traits have evolved 

with dominance and dominance based duplicate 

epistasis which helps to protect the individual plants 

from deleterious alleles arising from existing 

variability (Roy, 2000). 

The leptokurtic and positively skewed 

distribution for traits such as brix per cent, total 

soluble sugars and bioethanol yield suggested the 

involvement of relatively fewer number of segregating 

genes with dominance based complementary 

interaction in the inheritance of these traits. To 

achieve maximum genetic gain in respect of these 

traits needs intense selection. 

Estimation of variability parameters in a 

population is a pre-requisite for breeding programme 

aimed at improving yield, quality and other important 

characters under consideration. Unless a major 

portion of variation is heritable, attempts to improve 

characters by selection would be futile. Therefore, it 

is necessary to have information on both PCV and 

GCV, so that the heritability, which helps the breeder 

to predict the expected genetic advance possible by 

selection for characters, can be computed. According 

to Johnson et al. (1955), heritability estimates along 

with genetic gain would be more useful than the former 

alone in predicting the effectiveness of selection. 

Therefore it is essential to consider the predicted 

genetic advance along with heritability estimate as a 

tool in selection programme for better efficiency. 

36

VEMANNA et al 

The range in mean values does not reflect 

the total variance in the material studied. Hence, 

actual variance has to be estimated for the characters 

to know the extent of existing variability. However 

absolute values of phenotypic and genotypic variance 

cannot be used for comparing the degree of variability 

in different characters because the characters differ 

in the unit of measurement. Hence, the co-efficient 

of variation (PCV and GCV) which is calculated by 

considering the respective means have been used 

for the comparisons. 

In the present study, the range of variability 

was quite high for most of the characters studied 

except days to 50% flowering, days to maturity, 

nodes per plant, stem girth, brix per cent and total 

soluble sugars, which exhibited low to moderate 

amount variability. This indicates ample scope for 

the improvement of highly variable characters, which 

were generated by segregation and recombination, 

whereas, it may not be equally effective for a 

character, which exhibited narrow range of variability. 

In general, PCV values were relatively higher 

than GCV values which is coupled with negligible 

differences between them, indicates less 

environmental influence on most of the traits except 

nodes per plant, stem girth, grain yield, brix per cent, 

total soluble sugars, sugar yield and bioethanol yield. 

Days to 50% flowering and days to maturity 

exhibited lower values of GCV and PCV. This was in 

conformity with the reports of Rajappa (2009). High 

heritability coupled with low genetic advance as per 

cent of mean exhibited by this cross, indicated 

predominant role of non-additive gene action for these 

traits and this result is in accordance with the reports 

of Sankarapandian (2002). Patil et al. (1996), 

Sankarapandian (2002), Unche et al. (2008a) and 

Kachapur and Salimath (2009) also reported high 

heritability for this trait. 

Plant height exhibited high values of GCV 

and PCV but differences between them was relatively 

narrow indicating less influence of environment in the 

expression of this trait. The high broad sense 

heritability (97.42%) coupled with high genetic 

advance as per cent of mean (48.37%) indicated 

predominant role of additive gene action in its genetic 

control. The results of heritability and genetic advance 

in the present study is in total agreement with the 

reports of Sankarapandian et al. (1996), Umakanth 

et al. (2004), Sandeep et al. (2009a) and Rajappa 

(2009). 

37 

Nodes per plant and stem girth registered 

moderate PCV and GCV values with negligible 

difference between them indicating less influence of 

environment on these traits. The results of PCV and 

GCV were in agreement with earlier report of Rajappa 

(2009). These traits exhibited high heritability coupled 

with moderate and high genetic advance expressed 

as per cent of mean, respectively indicating role of 

additive gene action in there genetic control. Results 

of the present study are in corroborative with the 

earlier reports of Sankarapandian et al. (1996), 

Krishnakumar et al. (2004), Rajappa (2009) and 

Sandeep et al. (2009a). Reliability can be placed on 

these traits for selection of segregants owing to its 

high heritability coupled with high genetic advance. 

Total biomass per plant recorded higher 

values of PCV and GCV with negligible difference 

between them indicating less influence of environment 

on the expression of trait of interest. The high 

estimates of broad sense heritability (97.04%) and 

genetic advance expressed as per cent of mean 

(93.74%) in this cross indicating preponderance of 

additive gene action in the genetic control of this trait. 

Similar results were earlier reported by Unche et al. 

(2008a) with respect to heritability and genetic 

advance indicating efficiency of simple selection in 

deriving desirable segregants. 

Fresh stalk yield registered higher values of 

PCV and GCV with negligible difference between 

them, indicating less influence of environment on the 

expression of this trait. Higher values for this trait 

were earlier reported by Sankarapandian et al. (1996) 

and Rajappa (2009). The broad sense heritability and 

genetic advance estimates were also higher 

indicating usefulness of this trait in selection of 

desirable segregants due to its genetic control by 

additive gene action. This is in accordance with the 

earlier observations made by Sankarapandian et al. 

(1996), Krishnakumar et al. (2004), Patel et al. (2006), 

Unche et al. (2008a), Sandeep et al. (2009a) and 

Rajappa (2009). 

Grain yield registered higher values of PCV 

and GCV with conspicuous difference between them 

indicating high environmental influence. Higher values 

for this trait were earlier reported by Sankarapandian 

et al. (1996) and Rajappa (2009). The broad sense 

heritability and genetic advance estimates were also 

higher indicating usefulness of this trait in selection 

of desirable segregants due to its genetic control by 

additive gene action.


Brix per cent registered has considerable 

environment influence. However, high heritability and 

moderate genetic advance expressed as per cent of 

mean was recorded revealing the major role of 

additive gene action in genetic control of this trait. 

These results were in accordance with the reports of 

Sankarapandian (2002), Sandeep et al. (2009a) and 

Rajappa (2009) for heritability and genetic advance, 

but contradicts with the results obtained by 

Sankarapandian et al. (1996) and Rajappa (2009) with 

respect to GCV and PCV estimates who reported 

relatively higher values. Higher heritability and 

genetic advance for this trait indicate effectiveness 

of simple direct selection in improvement 

programmes. 

Juice yield registered higher PCV and GCV 

values with negligible difference between them, 

indicating less influence of environment on the 

expression of this trait. This also recorded high broad 

sense heritability (98.27%) coupled with high genetic 

advance as per cent of mean (123.06%) indicating 

predominant role of additive gene action in the genetic 

control of this trait. Higher values for this trait was 

earlier reported by Rajappa (2009) for PCV and GCV 

values and by Sankarapandian et al. (1996), 

Sankarapandian (2002), Kachapur and Salimath 

(2009) and Rajappa (2009) for heritability and genetic 

advance. This trait can be considered as a potential 

for improvement by simple selection owing to high 

heritability and genetic advance. 

Juice extraction per cent exhibited higher 

values of PCV and GCV with narrow difference 

between them, indicating less influence of 

environment on the expression of the trait. This is 

coupled with high heritability (95.03%) and genetic 

advance as per cent of mean (43.80%) indicating 

predominant role of additive gene action. Similar 

results with respect to heritability and genetic 

advance were reported earlier by Sankarapandian 

(2002) and Sandeep et al. (2009a). 

Total soluble sugars exhibited moderate 

value of PCV and low value of GCV with negligible 

differences between them indicating less influence 

of environment on the expression of this trait. Broad 

sense heritability and genetic advance estimates were 

also higher. Moderate variability of this trait coupled 

with high heritability and genetic advance indicate 

higher scope for further improvement through simple 

selection procedures. 

Moderate value of PCV and low value of GCV 

were registered by bioethanol yield coupled with high 

broad sense heritability and moderate genetic 

advance expressed as per cent of mean indicating 

major role of additive gene action in the genetic 

control of this trait. 

Sugar yield registered higher values of PCV 

and GCV compared to all other traits under study 

with considerable difference between them indicating 

substantial environmental influence on the expression 

of this trait, which is reflected in relatively higher broad 

sense heritability (95.16%) and high genetic advance 

expressed as per cent of mean (123.47%) indicating 

major role of additive gene action in the genetic 

control of this trait. Result of the present study is in 

conformity with the earlier reports of Krishnakumar 

et al. (2004) and Patel et al. (2006) with respect to 

heritability and genetic advance. Though heritability 

and genetic advance indicate scope for simple direct 

selection to be effective for this trait, actual gain would 

entirely depend on its intrinsic association with its 

attributing traits. 

Correlation Coefficients 

The correlation co-efficients among the 

selected characters related to fresh stalk yield and 

sugar yield in F 2 

population of ‘27 B × SSV 84’ sweet 

sorghum cross were estimated; results were 

tabulated in Table 2 and 3 and briefly described in 

the following paragraphs. 

Association of fresh stalk yield with its 

component characters Fresh stalk yield per plant 

was significantly and positively associated with total 

biomass per plant, grain yield per plant, plant height, 

nodes per plant, stem girth, days to 50% flowering 

and days to maturity. Similar trends were evident 

from the studies of Hapase and Repale (1999), Nahar 

et al. (2002), Krishnakumar et al., (2004), Singh and 

Khan (2004), Kadian and Mehta (2006), Patel et al. 

(2006) and Unche et al. (2008b). 

Among the fresh stalk yield attributing 

characters, positive and significant association was 

noticeable between days to 50% flowering with days 

to maturity, plant height, grain yield per plant, nodes 

per plant, total biomass per plant and stem girth; plant 

height with nodes per plant, total biomass per plant, 

stem girth and grain yield per plant; nodes per plant 

with total biomass per plant, grain yield per plant and 

stem girth; stem girth with total biomass per plant 

and grain yield per plant; total biomass per plant with 

38

VEMANNA et al 

grain yield per plant. These findings were in 

confirmation with the findings of Manickam and Das 

(1994), Ganesh et al. (1995), Verma et al. (1999) and 

Kachapur and Salimath (2009). However, positive and 

significant association of days to flowering and plant 

height observed in the present study contradicts with 

the report of Manickam and Das (1994) who observed 

negative significant correlation of days to flowering 

with plant height and plant height with stem girth. 

Thus, to improve the fresh stalk yield in 

sweet sorghum it is important to select the plants 

with relatively higher plant height, total biomass, stem 

girth, nodes per plant and days to maturity, as these 

traits had direct relation with fresh stalk yield as 

indicated by their positive and significant association. 

Hence, fresh stalk yield can be increased by following 

indirect selection using above associated traits in 

sweet sorghum. 

Association of sugar yield with its 

component characters Association between sugar 

yield was positive and highly significant with juice 

yield per plant, fresh stalk yield per plant, total 

biomass per plant, grain yield per plant, total soluble 

sugars, brix per cent, bioethanol yield per plant and 

juice extraction per cent. The results of the present 

investigation were in corroborative with Mallikarjun 

et al. (1998), Hapase and Repale (1999), Verma et 

al. (1999), Singh and Khan (2004), Kadian and Mehta 

(2006) and Unche et al. (2008b). 

Association among sugar yield attributing 

characters The association of total biomass with 

fresh stalk yield per plant, juice yield per plant, grain 

yield per plant, brix per cent, total soluble sugars 

and bioethanol yield per plant; fresh stalk yield per 

plant with juice yield per plant, grain yield per plant, 

brix per cent, total soluble sugars and bioethanol yield 

per plant; grain yield per plant with juice yield per 

plant; brix per cent with total soluble sugars, 

bioethanol yield per plant, juice extraction per cent 

and juice yield per plant; juice yield per plant with 

juice extraction per cent, total soluble sugars and 

bioethanol yield per plant; juice extraction per cent 

with total soluble sugars and bioethanol yield per 

plant; total soluble sugar with bioethanol yield per 

plant were positive and significant. The reports of 

Ganesh et al. (1995), Singh and Khan (2004), Kadian 

and Mehta (2006), Kachapur and Salimath (2009), 

Unche et al. (2008b) and Sandeep et al. (2010) were 

in agreement with the above results. 

The results on association of sugar yield with 

its attributing traits indicated importance of juice yield, 

fresh stalk yield, total biomass, grain yield, total 

soluble sugars, brix per cent, bioethanol yield and 

juice extraction per cent in improving sugar yield as 

these traits had direct relation with sugar yield. 

Hence, improvement in these traits automatically 

improve sugar yield. Thus, the above correlated traits 

can be effectively utilized in formulating indirect 

selection schemes. 

Path analysis 

The correlation estimates are the sum total 

of direct effect and indirect effects of an independent 

character on a dependent character and it is quite 

obvious that the correlation (positive or negative) may 

be of small magnitude and non-significant in spite of 

its direct effect and/or some of the indirect effects 

are operating in the opposite direction. Therefore, path 

analysis is required to partition the correlation value 

of independent characters on dependent character 

into direct and indirect effects so as to get a correct 

picture of the association of characters. Hence, path 

co-efficient analysis was carried out to know the 

direct and indirect effects of the component 

characters on sugar yield and the results are 

presented in Table 4. 

The results of path analysis of component 

characters of sugar yield indicated maximum positive 

direct effect of total soluble sugars and juice yield 

on sugar yield whereas bioethanol yield, fresh stalk 

yield and total biomass has very high, moderate and 

low negative direct effect, respectively on sugar yield. 

However, all the traits exhibited moderate to high 

positive indirect effect via juice yield and total soluble 

sugars. The indirect effect via total biomass and fresh 

stalk yield is negative and low to moderate while juice 

extraction per cent is negligible and negative. These 

results were in accordance with the earlier reposts of 

Mallikarjun et al. (1998), Hapase and Repale (1999) 

and Kachapur and Salimath (2009). In general, the 

results revealed that the indirect contribution of the 

characters viz., total biomass, fresh stalk yield and 

juice extraction per cent via juice yield resulted in 

their positive correlation with sugar yield. 

39


40

VEMANNA et al 

41


REFERENCES 

Ganesh, S., Khan, A. K. F., Suresh, M and Senthil, 

N., 1995. Character association for alcohol 

yield in sweet sorghum. The Madras 

Agricultural Journal. 82: 361-363. 

Hapase, R. S and Repale, J. M., 1999. Variability, 

correlation and path analysis in sugarcane. In: 

Proceedings of the 61 st Annual Convention of 

the Sugar Technologists Association of India, 

New Delhi, India, 7-9 September: pp. 130-141. 

Johnson, H. W, Robinson, H. F and Comstock, R. 

E., 1955. Estimates of genetic and 

environmental variability in soybean. 

Agronomy Journal. 47: 314- 318. 

Kachapur, R. M and Salimath, P. M., 2009. Genetic 

studies on correlation and character 

association in sweet sorghum [Sorghum 

bicolor (L.) Moench]. Green Farming. 2: 343- 

346. 

Kadian, S. P and Mehta, A. S., 2006. Correlation 

and path analysis in sugarcane. Indian Journal 

of Agricultural Research. 40: 47-51. 

Kimbeng, C. A and Bingham, E. T., 1998. Population 

improvement in Lucerne (Medicago sativa L.) 

components of inbreeding depression are 

different in original and improved populations. 

Australian Journal of Experimental Agriculture. 

38: 831-836. 

Krishnakumar, Singh, P. K and Singh, J. R. P., 2004. 

Genetic variability and character association 

in subtropical clones of Sugarcane 

(Saccharum complex hybrid). Indian Sugar. 

54: 189-198. 

Mallikarjun, H., Khanure, S. K and Kachapur, M. D., 

1998. Correlation and path analysis for juice 

quality parameters in sweet sorghum 

genotypes. The Madras Agricultural Journal. 

85: 207-208. 

Manickam, S and Das, L. D. V., 1994. Character 

association and path analysis in forage 

sorghum. Mysore Journal of Agricultural 

Sciences. 28: 116-119. 

Nahar, S. M. N., Khaleque, M. A and Miah, M. A., 

2002. Correlation, path co-efficient and 

construction of selection index in sugarcane. 

Pakistan Sugar Journal. 17: 2-10. 

Patel, K. C., Patel, A. I., Mali, S. C., Patel, D. U and 

Vashi, R. D., 2006. Variability, correlation and 

path analysis in sugarcane (Saccharum spp.). 

Crop Research. 32: 213-218. 

Patil, F. B., Gadekar, D. A and Bhoite, A. G., 1996. 

Variability studies in forage sorghum. Journal 

of Maharashtra Agricultural Universities. 

Z21: 330-332. 

Rajappa, P. V., 2009. Morphological and AFLP marker 

based genetic diversity in sweet sorghum 

working germplasm. M. Sc. (Agri.) Thesis 

submitted to University of Agricultural 

Sciences, Bangalore. 

Roy, D., 2000. Analysis of skewness and kurtosis. 

In: Plant breeding – The Analysis and 

Exploitation of Variation. Narosa Publishing 

House. New Delhi. India. pp 300-304. 

Sandeep, R. G., Gururaja Rao, M. R., Chikkalingaiah 

and Shivanna, H., 2009a. Assessment of 

variability for grain yield, ethanol yield and their 

attributing characters in germplasm 

accessions of sweet sorghum [Sorghum 

bicolor (L.) Moench]. Mysore Journal of 

Agricultural Sciences. 43: 472-476. 

Sandeep, R. G., Gururaja Rao, M. R., Chikkalingaiah 

and Shivanna, H., 2010. Association and path 

analysis for ethanol yield in sweet sorghum 

[Sorghum bicolor (L.) Moench]. Mysore Journal 

of Agricultural Sciences. 44: 28-30. 

Sankarapandian, R., 2002. Variability studies in two 

groups of hybrid populations in forage sorghum. 

Forage Research. 28: 46-48. 

Sankarapandian, R., Rajarathinam, S and Muppidathi, 

N., 1996. Genetic variability, correlation and 

path co-efficient analysis of jaggery yield and 

related attributes in sweet sorghum. 

The Madras Agricultural Journal. 83: 628-631. 

42

VEMANNA et al 

Singh, S. P and Khan, A. Q., 2004. Inter-relationship 

and path analysis in sugarcane (Saccharum 

spp. Complex). Environment and Ecology. 22: 

903-911. 

Umakanth, A. V., Madhududhana, R and 

Madhvilatha, K., 2004. Variability, character 

association and path analysis in rabi sorghum. 

The Andhra Agricultural Journal. 51: 333-336. 

Unche, P. B., Misal, M. B., Borgaonkar, S. B., 

Chavan, B. D and Sawant, D. R., 2008b. 

Correlation studies in sweet sorghum [Sorghum 

bicolor (L.) Moench]. International Journal of 

Plant Sciences. 3: 69-72. 

Unche, P. B., Misal, M. B., Borgaonkar, S. B., 

Godhawale, G. V., Chavan, B. D and Sawant, 

D. R., 2008a. Genetic variability studies in 

sweet sorghum [Sorghum bicolor (L.) Moench]. 

International Journal of Plant Sciences. 3: 16- 

18. 

Verma, P. S., Shri Pal and Karma, N. K., 1999. 

Genetic variability and correlation studies in 

sugarcane. Indian Sugar. 49: 125-128. 

43


ESTRUS SYNCHRONIZATION RESPONSE AND FERTILITY RATE FOLLOWING 

TREATMENT WITH PGF 2 

α AND GnRH IN ACYCLIC LACTATING ONGOLE COWS 

K.VENKATA RAMANA, K.SADASIVA RAO, K.SUPRIYA and N.RAJANNA 

Department of Veterinary Gynaecology and Obstetrics, College of Veterinary Science, 

Sri Venkateswara Veterinary University, Rajendranagar – 500 030 


ABSTRACT 

Estrus synchronization response and fertility following Ovsynch and double prostaglandin injection protocols 

in post partum Ongole cows was studied. A total of 50 Ongole parous cows above 60 days postpartum were divided 

in to two treatment groups consisting of 22 cows in each and 6 cows in control group. The follicular dynamics were 

monitored every day by ultrasonography till the ovulation. The emergence of follicular wave was observed on 1.33, 

3-4 days in Ovsynch and double PG groups, respectively. The size of dominant follicle found to be 12.48 ± 0.57 mm 

in Ovsynch and control group whereas 10.00 ± 0.78 mm in double PG group. In Ovsynch group estrus response was 

noticed in 100 per cent cows and estrus was recorded after 50 to 80 hours of PGF 2 

á injection with the duration of 

16.28 ± 2.36 hrs While in double PG the duration of estrus and mean estrous cycle length recorded as 14.20 ± 2.56 

hrs and 21.50 ± 0.21 days, respectively. The ovulations were noticed after 1.50 ± 0.22 days of 2 nd GnRH injection 

with conception rate of 54.54 per cent in Ovsynch. The mean service period found to be 81.18 ± 1.62 days in 

lactating multiparous Ongole cows. It may be concluded that double injection of prostaglandin has better conception 

rate than Ovsynch protocol and both the treatments reduced the service period around 80 days when compare with 

control group, there by reduced the calving interval in lactating Ongole cows. 

Ongole breed of cattle is dual purpose (milk 

and draught) cattle, due to their adaptability traits, 

superior production capacity and high disease 

resistance under harsh tropical conditions. However, 

certain reproductive impediments like long service 

period which results in to long calving intervals, 

nocturnal incidence of estrus with shorter duration 

are limiting the economic use of this cattle breed. 

The postpartum ovarian inactivity could be due to 

suckling induced inhibition of the LH surge (Gumen 

et al, 2003 and Naidu et al, 2007).Hence, an attempt 

was made to study the follicular dynamics during the 

postpartum and to enhance the fertility with PGF 2 α 

and GnRH hormonal protocols in lactating Ongole 

cows. 


A total of fifty postpartum lactating Ongole 

cows in their 2 nd to 5 th lactation maintained under 

standard feeding and management stationed at Cattle 

Project, Live Stock Research Station, Lam Farm, 

Guntur were included in this study. The cows were 

randomly divided in to two groups consisting of 22 

cows in each treatment group and six cows in control 

group. Estrus synchronization was performed by 

Ovsynch protocol (Treatment-I) i.e., day 0 Receptal 

10 g i.m, day 7 Lutalyse 25 mg i.m and again on 

day 9 Receptal 10 g i.m. Where as in double injection 

of prostaglandin group (Treatment-II) the first 

injection (Lutalyse 25 mg i.m) was given on day ‘0’ 

and 2 nd injection was given on day 12 th . The 

inseminations were carried out on observed estrus 

in both the groups. The non returned cows were 

examined for pregnancy per rectally between day 60 

to 70 post insemination. 

Ovarian structures in six cows in each 

treatment groups and control group were monitored 

daily by using a real time B-mode ultrasound scanner 

with a trans rectal linear-array transducer from day 

‘0’ of GnRH injection to till the end of induced estrus 

with ovulation to assess the fate of first wave 

dominant follicle and the emergence of subsequent 

wave. The scanning was also done in control group 

and ovarian changes and estrus response was 

recorded and compared with treatment groups during 

the treatment period. The data was analyzed by 

Minitab ®(16) (2012) software. 

email: kvr_vetgyn@yahoo.in 

44

RAMANA et al 


In Ovsynch protocol the first injection of 

GnRH is designed to induce ovulation and formation 

of a new or accessory corpus luteum and a new 

follicular wave. In the present investigation 

ultrasound scanning of ovaries was done every day 

after injection of GnRH induced ovulation and till the 

formation of corpus luteum. However, follicular wave 

emerge was noticed in all the six cows on day 

1.33+0.21. The dominant follicle resulted from this 

wave emergence grew up to 12.48+0.57 mm by day 

7.6 with a growth rate of 1.66+0.26 mm per day. This 

is in agreement with the reports of Mishra et al.(2002) 

and Souza et al. (2006) in Sahiwal cows with GnRH. 

However, Krishna Mohan et al. (2010) reported much 

lesser size (9.17 + 0.27 mm) dominant follicle in 

Sahiwal cows. 

All the cows with a corpus luteum which were 

administered with luteolytic dose (25 mg of Dinoprost 

Tromethamine) on day 7 were in estrus within 

2.33+0.21 days. The dominant follicle of all the six 

cows was ovulated with the second dose of GnRH 

on day 9 of the luteal phase. The ovulation recorded 

was 100 per cent with GnRH treatment which is in 

agreement with Gumen et al. (2003). This could be 

due to larger size of the dominant follicle measuring 

more than 9 mm will potentially ovulate in the GnRH 

treatment animals (Adams 1992). Ultrasound 

monitoring of the ovulated cows had shown a corpus 

luteum of 16.50+0.30 mm on day 10 following the 

induced estrus. Out of 22 postpartum lactating cows, 

8 cows showed estrus after 1 st GnRH injection and 

the cows exhibited normal estrus except two which 

had weak estrus following PGF 2 α administration on 

day 7 of the treatment. Second dose of GnRH was 

administered on day 9 and all the cows inseminated 

at the observed estrus. The estrus response recorded 

in this study was in agreement with Mialot et al. 

(1998) and Vasconcelos et al. (1999). In the present 

study the conception rate found to be 54.54+0.36 

per cent. 

The ultrasound scanning of PGF 2 α treated 

cows revealed a dominant follicle of 10.00 + 0.78 

mm within 3-4 days after the PGF 2 α administration, 

which is in agreement with Alan et al. (2003) and 

Naidu et al. (2010) in Nelore cows. Out of 22 cows 

treated with double injections of prostaglandins 18 

exhibited estrus within 3.66+0.21 days. The time of 

onset of estrus following PGF 2 α injection recorded in 

this study is corroborating to the findings of Alves et 

al. (2002) in Gir cows. 

In the present study the conception rate 

found to be 67.00 +0.26 per cent. Naidu et al. (2006) 

has reported higher conception rate (90.0%) than the 

present findings in Ongole cows, which might be due 

to better synchrony of ovulation and fertilization as 

the existing follicles were influenced the next wave 

of follicles during induction. All the treated postpartum 

lactating ongole cows in Ovsynch and double PG 

groups exhibited 100 and 82.5 per cent of estrus, 

respectively. The reason for varied estrus response 

rate between different treatment groups might be due 

to the difference in the treatment protocols and due 

to, presence of too small dominant follicles (< 9 mm) 

at the time of second PGF 2 

injection (Rivera et al. 

1998). 

In the control group the mean time required 

for conception after calving was recorded as 

163.60+10.72 (95-397) days, which is less than the 

previous studies (Venkateswarulu, 1971; Rao et al, 

1985; Acharya & Bhat 1990; Ravi Kiran et al. 1995; 

Rao et al. 2001and Naidu et.al,.,.2010). The service 

period of cows in the treatment groups resulted a 

reduction of approximately 85 days compared to 

control group cows. 

Hence, it is concluded that the estrus 

synchronization with GnRH and PGF2 gives better 

results and would reduce the calving to service period 

drastically and beneficial to the farmers in dairy 

industry. 

ACKNOWLEDGEMENT 

The authors express their sincere gratitude to the 

SVVU, Tirupati for providing facilities to carry out 

the research work at Cattle Project, Live Stock 

Research Station, Lam Farm, Guntur.A.P. 

45

ESTRUS SYNCHRONIZATION RESPONSE AND FERTILITY RATE 

REFERENCES 

Acharya and Bhat 1990. Productive and reproductive 

traits in Ongole cows. ICAR Bulletin. 

Adams, G. P. Matteri R. Kastetic, J. P. Ko, J. C .H 

and Ginther, O J 1992. Association between 

surges of follicle stimulating hormone and the 

emergence of follicle wave in heifers. Journal 

of Reproduction and Fertility 94: 177-178. 

Alan Bennett Maia Alexandre Alves Ciro Torres 

Reinaldo Jose Mendes Streets Vicente Ribeiro 

Rocha Jr Giovanni Ribeiro e Carvalho 

Jefferson Ferreira da Fonseca Alberto Neto 

Marcatti Anderson George of Assisi-2003. 

Characteristics of follicular dynamics and luteal 

regression in cows of Gir and Nelore cows after 

treatment with cloprostenol. Journal of Animal 

Science. 32(1) 1806-9290. 

Alves N G costa E P da Guimaraes J D Silva M R 

Zamperlini B Costa F M J Santos A D F 

Miranda Neto T 2002. Ovarian activity in 

Holstein and crossbreed Holstein x Zebu cows 

during two normal estrous cycles. 

(Portuguese). Revista brasieira de Zootecnia. 

31(2), 627-634. 35 ref. 

Gumen A Guenther J N Wiltbank M C 2003. Follicular 

size and response to Ovsynch versus 

detection of estrous in anovular and ovular 

lactating dairy cows. Journal of dairy Science 

86 (10) 3184-3194. 

Krishna Mohan U K Mishra O P Mishra Singh C 

and Prakash B S 2010. Follicular development 

pattern in post partum anestrous sahiwal cows 

during Ovsynch protocol. IndianVet. Journal., 

87: 448-450. 

Mialot J P Laumonnier G Ponsart C Fauxpoint 

H Barassin F Ponter A A and Deletang F 

1999. Postpartum subestrus in dairy cows; 

comparison of treatment with prostaglandin F2 

or GnRH + prostaglandin F2 + GnRH. 

Theriogenology 52 : 901-911. 

Mishra O P Khan J R and Awasthi M K 2002 

Study of follicular dynamics in Sahiwal cows. 

Indian Journal Animal Reproduction 23: 193. 

Naidu G V Babu Rao K 2006 Estrus pattern and 

conception rate in postpartum lactating Ongole 

cows. Indian Journal of Animal Reproduction 

27 (1) 14 – 17. 

Naidu G V Rao A S Rao K B 2007 Progesterone 

profile in postpartum lactating Ongole (Zebu) 

cows. Indian Journal of Animal Reproduction. 

28 (1) : 12-14, 

Naidu G V Seshagiri A Babu Rao K 2010. 

Progesterone profile in postpartum lactating 

Ongole (Zebu) cows. Indian Journal of Animal 

Reproduction. 31 (1) :79-80. 

Rao K B and Venkata Naidu G 2001 Annual Progress 

report of the technical programme on Genetic 

improvement of Ongole breed through 

Associate Herd Testing Scheme, ANGRAU 

Rao A V and Venkataramaiah P 1985 Studies on the 

effectiveness of a smaller dose of 

prostaglandin F2 in increasing the reproductive 

efficiency of Ongole cattle. Indian Veterinary 

Journal 67: 528-530 

Ravikiran G Rao G N and Jayarama Krishna V 

Satyanarayana A 1995. Performance of ongole 

and crossbred cows under village conditions. 

Indian Journal of Animal Science 65: 782. 

Rivera G M Goni C G Chaves M A Ferrero S B and 

Bo G A 1998. Ovarian follicular wave 

synchronization and induction of ovulation in 

postpartum beef cows. Theriogenology 49 : 

1365 -1375. 

Souza A F Pinheiro V G Ereno R L and Barros M 

2006. Synchronization of ovulation in 

anestrous Nelore cows treated with hormonal 

protocol without progesterone or progestagens. 

Reproduction fertility and development. 18(2) 

115-116. 

Vasconcelos J L M Silcox R W Rosa G J M Pursley 

J R and Wiltbank M C 1999. Synchronization 

rate, size of the ovulatory follicle and 

pregnancy rate after synchronization of 

ovulation beginning on different days of the 

estrous cycle in lactating dairy cows. 

Theriogenology 52 : 1067 – 1078. 

Venkateswarlu M 1971. Studies on genetic 

correlation and inheritance of economic 

characteristics of Ongole cattle, M.Sc Thesis 

submitted to Agra University. 

46


A STUDY ON MIGRATION PATTERN OF SHEEP FLOCKS IN TELANGANA 

REGION OF ANDHRA PRADESH 

N. RAJANNA, M. MAHENDAR and K. VENKATA RAMANA 

Department of Livestock Production and Management, 

Sri Venkateswara Veterinary University, College of Veterinary Science, 

Rajendranagar, Hyderabad-30. 


ABSTRACT 

A survey was carried out to collect information about migration pattern of sheep flocks in Telangana region 

during 2010-2011. A total of 576 farmers were selected by multistage stratified random sampling technique and the 

information was collected from them through personal interview. It was revealed the existence of twenty traditional 

migratory routes in the study area. The mean duration and distance of migration of flocks were 124.3 ± 10.5 days 

and 112.2 ± 19.5 km, respectively. The migration mostly started in the mid-January and extended up to July. The 

perception of farmers about basis for migration was lack of grazing resources (90.80%), periodical drought (80.90%), 

traditional occupation (77.78%), fields filled with crops (74.65%), disease problem (64.06%), lack of feeding resources 

(61.81%), lack of water resources (30.73%) and heavy rains (23.44%) and ranked them from I to VIII. The problems 

faced during migration included attack of diseases (87.85%), lack of shelter for animals (81.60%), theft (74.13%), 

restriction of entry into other villages (71.18%), lack of veterinary facilities (67.88%) predators (23.26%) and abortions 

due to stress (13.72%). Thus, knowledge about the migration pattern will help policy makers and planners in making 

suitable corrective and remedial measures 

Sheep is one of the important livestock 

species contributing to the livelihood of resource poor 

farmers in rural areas, particularly that are prone to 

drought. It contributes to the farm households not 

only by acting as source of livelihood and nutritional 

security, but also as a moving asset, which can be 

liquidated at a times of crises within short period. 

Andhra Pradesh state is known for its diversified 

livestock resources in nine well defined agro climatic 

zones. Andhra Pradesh state is divided into three 

geopolitical regions viz., Coastal Andhra, Telangana 

and Rayalaseema. According to 2008 census sheep 

population in Andhra Pradesh are 255.39 lakhs and 

ranks first in the country. In Telangana region of 

Andhra Pradesh, sheep rearing largely depended on 

grazing under extensive system of production. 

Whenever the grazing sources degraded, farmers 

were compelled to resort migration. During migration 

shepherds night shelter their flocks in farmer’s field 

and get some payment either in cash or kind in 

exchange for leftover of sheep manure. However, 

information on migration pattern of sheep flocks under 

field condition is scanty. Therefore, knowledge about 

the migration pattern will help policy makers and 

planners in making suitable corrective and remedial 

measures. Hence it was felt very essential to study 

the migration pattern of sheep flocks in Telangana 

region of Andhra Pradesh . 


The study was undertaken in Telangana 

region of Andhra Pradesh during 2010-2011. 

Telangana region was divided into three zones viz., 

Northern Telangana Zone (NTZ), Central Telangana 

Zone (CTZ) and Southern Telangana Zone (CTZ) on 

the basis of the agro-climatic conditions. Multistage 

stratified random sampling technique was applied to 

select the villages and sheep farmers. In the first 

stage two districts from each zone were selected 

and in the second stage four mandals from each 

district and in the third stage four villages from each 

selected mandal were selected based on sheep 

population. From each village 6 respondents 

possessing sheep were selected randomly for the 

present study. Hence, 576 sheep farmers constituted 

the study sample. Data on migration practices, 

reasons and problems of migration were studied from 

the respondents by face-to-face interview. Based on 

farmers responses frequency and percentages were 

calculated and accordingly rankings were given. 

email: neeradiraj@gmail.com 

47


Table 1. Months, duration and distance of migration of sheep flocks in Telangana region 

S.No. Zone Tract No. Months of migration Duration (days) Distance (Km) 

1 NTZ I 15 th Feb- 15 th May 60 60 

2 NTZ II 5 th Feb-5 th June 121 25 

3 NTZ III 20 th Feb- 20 th June 121 120 

4 NTZ IV 15 th Feb- 15 th June 121 55 

5 NTZ V 10 th Feb-10 th June 121 80 

Mean± SE 108.8± 12.2 68.0 ±15.7 

6 STZ VI 5 th April- 5 th July 91 70 

7 STZ VII 15 th April- 15 th July 94 200 

8 STZ VIII 25 th Dec- 25 th July 213 70 

9 STZ IX 5 th April- 5 th July 91 30 

10 STZ X 

5 th Jan-5 th April & 

10 th Aug-10 th Sep 

122 20 

11 STZ XI 15 th Jan- 15 th Aug 212 232 

12 STZ XII 10 th April- 10 th July 92 232 

13 STZ XIII 15 th Feb- 15 th April 60 150 

14 STZ XIV 5 th Jan-5 th Aug 212 200 

15 STZ XV 20 th Feb-20 th June 121 25 

16 STZ XVI 10 th Jan-10 th June 151 250 

17 STZ XVII 15 th Feb- 15 th June 121 260 

Mean± SE 131.6 ±15.4 144.9± 27.51 

18 CTZ XVIII 5 th Jan- 5 th April 90 25 

19 CTZ XIX 20 th Jan- 20 th June 151 50 

20 CTZ XX 20 th Feb- 20 th June 121 90 

Mean± SE 120.66± 17.66 55.0± 18.92 

Overall Mean± SE 124.3 ± 10.05 112.2 ± 19.5 


Sheep rearing largely depended on grazing 

under extensive system of production. Whenever, 

the grazing sources degraded farmers were 

compelled to resort migration. The migration in local 

language (Telugu) known as ‘Valasa’ or ‘Mannem’ is 

being performed by farmers who are having large 

flock size. The migration started between 5 th Feb 

and 20th Feb in I to V tracks and between 5 th Jan – 

20 th Feb in XVIII to XX tracks, whereas, year round 

migration was observed in ST zone due to prevailed 

cropping pattern (Table 1). In majority of tracks sheep 

farmers returned from migration to their native track 

between April and June. Thus initiation linked to the 

onset of dry season and withering of surface 

vegetation while the termination was based on the 

onset of monsoon. The migrating sheep flock 

covered a minimum distance of 25 km and maximum 

of 260 km with a mean of 112.2 ± 19.5 km. The 

duration of migration ranged from 60 to 213 days 

with a mean of 124.3 ± 10.5 days. Kumaravelu (2007) 

identified 8 major, 10 minor and eleven migratory 

tracks, respectively in Andhra Pradesh and Tamil 

Nadu. Regarding the onset and return of migration 

48

RAJANNA et. al. 

Table 2. Reasons for migration of sheep flock’s as perceived by sheep farmers in Telangana region 

49


Table 3. Problems faced during sheep flock’s migration as perceived by sheep farmers in Telangana region 

50

RAJANNA et al 

the present findings corroborated with Pattanayak et 

al. (2003), Sushilkumar et al. (2003), Arora et al. 

(2007) and Gopaldass (2007). 

As far as duration and distance covered 

Rajapandi, (2005) reported Coimbatore sheep 

migrated a distance of 100 to 200 km and Kumaravelu 

(2007) had described the duration (days) ranged 

from 91 to 315 days in southern zone of Tamil Nadu 

state. 

Reason for migration 

Majority (90.80%) of sheep farmers 

perceived lack of grazing resources followed by 

periodical drought (80.90%), traditional occupation 

(77.78), fields filled with crops (74.65%), disease 

problem (64.06%), lack of feeding resources 

(61.81%), lack of water resources (30.73%) and 

heavy rains (23.44%) as a basis of migration and 

ranked them from I to VIII, respectively (Table 2) . 

Farmers should be encouraged to take up Silvi 

Pasture system, controlled grazing and culling of 

unproductive animal as a remedial measure for the 

above problems. These results are in conformity with 

findings of Dorji et. al. (2003) and Saravanakumar et 

al. (2003) who reported shortage of water and grazing 

land and feeding resources, tradition, successive 

drought, and disease outbreaks were the reasons of 

migration. 

Problems faced during migration 

Problems faced by sheep farmers were 

ranked in the order of attack of diseases (87.85%), 

lack of shelter for animals (81.60%), theft (74.13%), 

restriction of entry into other villages (71.18%), lack 

of veterinary facilities (67.88%) predators (23.26%) 

and abortions due to stress (13.72%) from I to VII, 

respectively. During migration, the shepherds along 

with sheep flocks spent most of the time in forests, 

river belts and remote villages where the veterinary 

facilities were not available in time and up to the 

mark, leading to disease outbreaks. The sheep 

farmers allowed animals for penning during night 

times. Hence the sheep could not receive any 

protection from adverse weather leading to disease 

susceptibility. Lack of care during lambing and for 

new born lambs during migration has lead to lamb 

mortality because the lambs also move continuously 

without any protection from heat resulting in heat 

stress. These findings were corroborated with the 

Kuldeepporwal et al. (2006) and Suresh et al. (2008). 

REFERENCES 

Arora, A. L., Prince, L. L. L and Mishra, A. K. 2007. 

Performance evaluation of Jaisalmeri sheep 

in farmer’s flocks. Indian Journal of Animal 

Sciences: 77 (8)759-762 

Dorji, T., Tshering, G., Wangchuk, T., Rege, J. E. O 

and Hannote, O. 2003. Indigenous sheep 

genetic resources and management in Bhutan. 

Animal Genetics Resource information Bulletin 

33: 81-91. 

Gopaldass.T 2007. Production performance and 

management practices of Pugal sheep in the 

home tract. Indian Journal Animal 

Sciences.77(8)763-766. 

Kuldeepporwal, Karim, S. A., Sisodia, S. L and Singh, 

V. K. 2006. Socio-economic survey of sheep 

farmers in western Rajasthan. Indian Journal 

of Small Ruminants 12 (1): 74-81. 

Kumaravelu, N. 2007. Analysis of sheep production 

system in Southern and Northern Zones of 

Tamilnadu. Ph.D Thesis submitted to Tamil 

Nadu Veterinary and Animal Sciences 

University, Chennai. 

Pattanayak, G. R., Patro, B. N., Das, S. K and Nayak, 

S. 2003. Survey and performance evaluation 

of Ganjam Sheep. Indian Journal of Small 

Ruminants 9(1): 47-49. 

Rajapandi, S. 2005. Distribution and management 

practices of Coimbatore sheep. Thesis 

submitted to Veterinary College and Research 

Institute, Namakkal, Tamil Nadu. 

Suresh, A., Gupta, D. C and Mann, J. S. 2008 

Constraints in adoption of improved 

management practices of sheep farming in 

semi-arid region of Rajasthan. Indian Journal 

of Small Ruminants 14 (1): 93-98. 

Sushilkumar , Sharma R C, Mishra, A. K and Arora 

A L 2003. Production performance of sheep 

and certain management practices in farmer’s 

flocks of south East Rajasthan. Indian journal 

of small ruminants, 9(2): 103-105. 

51


UTILIZATION OF POULTRY WASTE AN UN-CONVENTIONAL PROTEIN SOURCE 

IN SMALL RUMINANT RATIONS 

J. NARASIMHA, V.CHINNI PREETHAM AND S.T.VIROJI RAO 

All India Co-ordinated Research Project on poultry breeding, College of Veterinary Science, 

Sri Venkateswara Veterinary University, Hyderabad-500030 

Date of Receipt : 16.08.2012 Date of Acceptance :13.12.2012 

ABSTRACT 

A complete feed containing poultry litter (35%) and other feed ingredients were formulated and processed 

in to mash. The feed was tested on six each of Nellore rams and indigenous bucks in a digestion- cum-metabolism 

trial using a completely randomized design to asses the voluntary feed intake and nutrient utilization. The voluntary 

feed intake of DM and the intake per kg DMI was significantly (P

NARASIMHA et al 

Table 1. Proximate composition of experimental ration and poultry litter (%DM) 

Proximate principle Experimental ration (%) Poultry litter (%) 

Dry matter 91.25 93.45 

Organic matter 80.00 63.21 

Crude protein 12.18 15.70 

Ether extract 1.87 0.87 

Crude fibre 30.17 15.08 

Total ash 20.00 36.78 

Acid insoluble ash 6.19 12.39 

Nitrogen free extract 35.78 31.57 

Calcium 0.89 4.57 

Phosphorous 0.76 3.7 

on various factors like dry matter, season, climatic 

condition and type of feed (Taneja, 1969; Mehrothra 

and Mullick, 1960). 

There was no significant difference in 

digestibility co-efficient of Dry matter, Organic matter, 

(Table 2). Similar findings were reported by 

(Mallikarjuna, 1989), in sheep and goats fed rations 

containing cotton straw, maize cobs for dry matter. 

A non-significant difference in digestibilities for Crude 

Protein was observed in sheep and goats. Similar 

results were reported by (Murthy et al., 1996) when 

fed poultry litter and poultry droppings in the pelleted 

ration. The lower digestibility of Crude Protein in the 

present experiment may be due to incorporation of 

cotton seed hulls at 40 percent level. The cotton seed 

hulls contained about 31 percent lint, mostly made 

of cellulose and about 14.3 percent lignin. It is quite 

likely that proteins in the cotton seed hulls are located 

in the structural component of cell. Structural protein 

(Maynard et al., 1981) which may not be available 

for the microbes to attack due to high lignin content. 

Further the fineness of cotton seed hulls during 

processing might have also contributed to lower 

digestibility due to faster rate of passage through the 

digestive tract (Keys and Smith., 1984). There was 

no significant difference in ether extract and crude 

fibre digestibility in the two species of sheep and 

goats (Table 2). The findings are in agreement with 

those of (Sreedhar et al., 1993). 

The non-significant difference in Nitrogen free 

extract digestibility between sheep and goats 

observed in the present study concur with the results 

of (Murthy et al., 1996) who also reported nonsignificant 

difference in Nitrogen free extract 

digestibility between sheep and goats fed poultry 

litter/poultry droppings based pelleted ration. All 

experimental animals were in positive N, Ca, and P 

balances indicating that the experimental feed 

supplied these nutrients in required quantities to both 

species. Sheep retained significantly (P>0.01) higher 

N, Ca and P than goats (Table 2). This could be 

attributed to higher Dry matter intake in sheep. The 

ration met Digestible crude protein (DCP) and Total 

digestible nutrients (TDN) requirements as 

recommended by ICAR (1985). The results of this 

study indicate that complete feed containing poultry 

litter up to 35 percent level could be utilized for feeding 

of small ruminants. The complete ration formulated 

in this study met the nutritive requirement of sheep 

and goats. Further it was observed that poultry litter 

could be used up to 35 percent level in complete 

feeds of small ruminant rations as an un- conventional 

protein source without any adverse effect. 

53

UTILIZATION OF POULTRY WASTE AN UN-CONVENTIONAL PROTEIN SOURCE 

Table 2. Digestibility of nutrients in sheep and goats 

Nutrient Sheep Goat Level of significance 

DMI % BW 5.62±0.23 2.76±0.16 (**) 

Water intake L/100kg 13.71±0.55 4.61±0.16 (**) 

Per kg DMI 2.56±0.24 1.66±0.13 (**) 

Digestibility co-efficients (%) 

DM 51.57±0.64 51.53±1.16 NS 

OM 56.29±0.15 56.85±0.64 NS 

CP 51.39±0.91 51.59±0.89 NS 

EE 67.49±1.79 65.41±1.31 NS 

CF 51.15±0.35 51.96±0.58 NS 

NFE 61.99±0.29 62.54±0.72 NS 

N (g/kg) 4.98±0.34 2.56±0.13 (**) 

Ca (g/kg) 2.76±0.23 1.59±0.08 (**) 

P (g/kg) 2.08±0.14 0.97±0.04 (**) 

DCP intake 

Per day (g) 67.64±4.64 32.18±2.63 (**) 

Per 100kg body weight (kg) 0.35±0.01 0.17±0.13 (**) 

TDN intake 

Per day (g) 499.26±37.17 240.74±19.20 (**) 

Per 100kg body weight (kg) 2.63±0.11 1.03±0.09 (**) 

NS- Non significant ; ** Significant (P>0.01) 

REFERENCES 

AOAC. 2005. Official methods of analysis. 

Association of official analytical chemist. 18 th 

Ed. Washington DC. USA. 

ICAR. 1985. Nutrient requirement of livestock and 

poultry publications and information division 

Indian Council of Agricultural Research, New 

Delhi 

Keys,J.E and Smith,L.W. 1984. Effect of Ensiling 

Corn Stover with Alfalfa on Growth, Intake, 

and Digestion by Yearling Dairy Heifers as 

Compared with Whole Corn Plant 

Silage.Journal of dairy science 67(9) :1971- 

1975 

Livestock census, 2003. Department of animal 

husbandry, dairying and fisheries. Ministry of 

Agriculture, Government of India. http: //dahd/ 

nic.in/census.htm. 

Mallikarjuna, G.1989. Studies on the pattern of 

volatile fatty acids concentration in rumen of 

Ssheep and goats and their relative levels with 

respect to time after feeding. MVSc Thesis 

submitted to Acharya N.G.Ranga Agricultural 

University, Hyderabad. 

54

NARASIMHA et al 

Maynard, L., Lossli,J.K., Horold, F.H and Warner, 

R.L.1981.Animal nutrition, 7 th edition, Tata 

McGrawHill Publishing company, New Delhi, 

India 

Mehrothra and Mullick, D.N.1960. Indian Journal of 

Veterinary Science and Animal Husbandry 

30:30 

Murthy, K.S., M.R. Reddy and G.V.N. Reddy. 1996. 

Nutritive value of supplements containing 

poultry droppings/litter for sheep and goats. 

Small Ruminant Research. 21(2):71-75. 

Nageswera Rao,G. 1983. Statistics for Agricultural 

sciences. Oxford and IBH Publishing 

company, New Delhi 

mixture. Indian Journal of Animal Nutrition 10 

(2): 77-81 

Talapatra, S.K.,Ray,S.C and Sen, K.C. 1940. The 

analysis of mineral constituents in biological 

materials. Indian Journal of Veterinary Science 

and A.H. 10:243 

Taneja, G.L. 1969. Variation in body temperature, 

respiration rate, water intake and body weight 

on Marwari sheep during the year. Indian 

Veterinary Journal 46:49 

Venugopal Rao D., Naidu M.M and Raghavan G.V. 

1997. Utilisation of complete feed containing 

poultry droppings in sheep and goats. Indian 

Veterinary Journal 74:858-861 

Sreedhar,C., Reddy, T.J and Raghavan G.V. 1993. 

Nutrient availability in goats fed cotton seed 

hulls and poultry waste based concentrate 

55


POSTPARTUM OVARIAN FOLLICULAR DYNAMICS AND ESTRUS ACTIVITY IN 

LACTATING ONGOLE COWS 

K. VENKATA RAMANA, K. SADASIVA RAO, K. SUPRIYA and N. RAJANNA 

Department of Animal Reproduction Gynaecology & Obstetrics, College of Veterinary Science, 

Sri Venkateswara Veterinary University, Rajendranagar – 500 030 

Date of Receipt : 06.12.2012 Date of Acceptance :28.01.2013 

ABSTRACT 

The objective of this study was to characterize early postpartum follicular dynamics in lactating Ongole 

cows in relation to their ovarian activity and subsequent reproductive performance using 70 multiparous lactating 

Ongole cows. The follicles measuring above 6 mm diameter and corpus luteum measuring 8-10 mm were detected 

by day 20-25 postpartum period by ultrasonography. The first and second wave of the dominant follicle emerged on 

1.80 + 0.8 and 12.46 + 0.20 days respectively. The mean growth rate and size was significant (P

RAMANA et al 

with small follicles measuring > 6 mm diameter. In 

the ultrasound monitoring follicles measuring above 

6 mm diameter and corpus luteum measuring 8-10 

mm were detected by day 20-25 postpartum period. 

The resumption of ovarian activity observed in this 

investigation is close to the findings of Roche et al. 

(1992) Henao et al. (2000). The follicular size > 6 

mm reported in this study is in concurrence with the 

observations of Krishna mohan et al (2010) and 

Satheesh kumar et al (2008). However, 

Rajamahendran et al. (1990) reported first postpartum 

ovulation as early as 10-15 days postpartum in Bos 

indicus cows. 

The follicular growth pattern monitored using 

an ultrasound scanner during the standing estrus in 

ten estrus cycles revealed the occurrence of seven 

two wave and the other three shown three wave 

cycles with wave emergence on day 1.80 + 0.80 and 

12.46+0.50 for two wave cycles, day 1.52 +0.03, 9.60 

+0.40 and 15.20 + 0.37 for three wave cycles, 

respectively. The two wave pattern (7/10) of follicular 

growth observed in the present investigation is in 

close agreement with the findings of Figueiredo et 

al. (1997), Mayra et al. 1999), Alan et al. (2003), 

Borges et al. (2004), Gaur and Purohit (2007) and 

Akter et al. (2010) who have reported predominantly 

two wave pattern in the estrus cycle in Nelore or Zebu 

cows. On the contrary much shorter intervals were 

reported by Borges et al.(2001) in zebu crosses, 

Rhodes et al.(1995) in cross breed heifers and Malhi 

et al. (2005) in Hereford cows. 

The mean diameter of the first and second 

dominant follicles (10.23 +0.40 and 12.30+ 0.36 mm) 

of the two wave recorded in this study were in close 

agreement with the findings of Figueiredo et al. (1997) 

Mayra et al. (1997) Akter et al. (2010) in Nelore cows. 

Contrary to these findings Gaur and Purohit (2007) 

observed the lesser average diameter of dominant 

follicle size of 8.02 + 0.38 and 9.10 + 0.24 mm in 

Nelore cows for the first and second waves, 

respectively. However Krishna Mohan et al. (2010) 

also recorded higher diameter of (14.6 + 0.12 mm) 

than the present study in normal cyclic Sahiwal cows. 

It was observed that the first wave dominant follicle 

of three wave cycles attained a maximum size of 

10.70+0.20 mm with a mean growth rate of 0.87+0.03 

mm per day and in the second wave of the dominant 

follicle maximum size was 9.80+0.37 mm with growth 

rate of 0.77+0.06 per day. The third wave maximum 

diameter was 12.80+0.37 mm with a mean growth 

rate of 1.46+0.90 mm per day, which is significantly 

bigger and faster in growth rate than the first and 

second waves in the same estrous cycle. However, 

the growth rate of second and third waves were not 

significant. This could be due to larger duration of 

dominant higher progesterone and low pulsatile 

frequency of LH secretion (Wolfenson et al. 2004) 

The growth rate of the dominant follicle recorded in 

the present study were in agreement with the findings 

of Figueiredo et al. (1997). The variation in the 

diameter and growth rate of the dominant follicle 

reported could be due to inherent characters of the 

breeds. 

Body score condition (Rhodes et al.1995), 

negative energy balance, Insulin like Growth factor, 

inhibin and gonadotrophin hormones systemic levels 

Rhodes et al. 1997) altered LH pulse frequency and 

follicular growth. 

In normal two wave cycles, the first wave dominant 

follicle did not differ significantly in their size with 

ovulatory dominant follicle but it was small in size. 

The smaller diameter of first wave dominant follicle 

might be due to the fact that the first wave emerged 

during the period of higher progesterone production 

by the corpus luteum. These findings are in close 

agreement with the observations of Figueiredo et al. 

(1997), Mayra et al. (1999) and Viana et al. (2000) in 

Nelore cows. 

In the present study the progesterone 

concentration observed during the development of 

first follicular wave was between 1.48 to 2.98 ng/ml 

which could be a contributing factor for the smaller 

size of the dominant follicle of this first wave (Vinoles 

et al. 1999). 

Perusal of data revealed that, the mean 

maximum diameter of the ovulatory follicle was larger 

than the diameter of the dominant follicles of previous 

waves, which was in agreement with the findings of 

Figueiredo et al. (1997) and Mihm et al. (2006). The 

growth rate of ovulatory follicle in two wave cycles 

was 0.91+0.88 mm per day, was less than first wave 

follicle (0.94+0.80 mm per day), which could be due 

to lower plasma concentrations of progesterone and 

57

POSTPARTUM OVARIAN FOLLICULAR DYNAMICS AND ESTRUS ACTIVITY 

presence of high FSH receptors (Knopf et al. 1989). 

Kulick et al. (2001) opined that the slower average 

growth rate of the dominant follicle of the second in 

two wave cycle was compensated by taking a longer 

period for reaching maximum diameter and ovulation. 

The maximum diameter of dominant follicles 

of first and second waves in two wave cycles reached 

on 5.13 + 0.63 and 18.50 + 0.50 days and in three 

wave cycles, 6.45+ 0.88, 12.89+3.06 and 20.44+1.42 

days and regression started on 10.80+ 1.10 in first 

wave in two wave cycle and 7.12+ 0.74 and 15.15+ 

2.26 days in first and second waves of three wave 

cycle, which were in agreement with the Figueiredo 

et al. 1997) and Gaur et al. (2007) in Nellore cows. 

Statistical analysis of the data of diameter 

of dominant follicle in two wave cycles revealed that 

the diameter of the first wave dominant follicle was 

significantly (P< 0.01) smaller than the second wave 

dominant follicle (ovulatory follicle). The growth rate 

of second wave dominant follicle was faster than its 

counterpart in the first follicular wave. 

The regression of dominant follicles of first 

wave in two wave cycle and first and second waves 

in three wave cycle occurs between 7-15 days 

observed in the present study were similar to the 

findings of Figueiredo et al. (1997) and Gaur et al. 

(2007) in Nellore cows. The mean regression rate of 

first wave in two wave cycle was 1.41+0.20 mm per 

day and in three wave cycle 1.20 + 0.33 and 1.48 + 

0.33 in first and second waves respectively. 

The mean duration of phase of regression 

of dominant follicles in first wave of two wave cycles 

was recorded as 6.50+ 0.56 days and in three wave 

cycles 7.13 + 1.86 and 4.72 + 1.42 days respectively 

in first and second waves. The mean period of static 

phase was 1.20±0.26 days in first wave of two wave 

cycle and 1.80±0.34 and 1.67±0.67 days for first and 

second waves of three wave cycles, respectively. 

The mean ovulation in natural estrus in postpartum 

lactating Ongole cows was recorded as 20.90 ±0.46 

and 22.20±0.37 respectively in two wave and three 

wave estrous cycles. The mean duration of first and 

second wave in two wave estrous cycles in 

postpartum lactating Ongole cows were 14.20±0.40 

and 9.10±0.45, respectively. Where as in three wave 

estrous cycles the duration of first, second and third 

waves were 11.20±0.37, 10.60±0.40 and 6.0±0.31 

days, respectively. In the present study, in natural 

cycle, the corpus luteum grew to a maximum 

diameter of 15.93 + 0.37 and 17.8 + 0.37 mm in two 

and three wave cycles on the day 13.1+1.50, 

14.60+0.56 and remained static up to 14.60+ 1.50 

and 15.90+0.45 days of the estrous cycles, 

respectively. 

The above results were almost comparable 

to that observed by Figueiredo et al. (1997) in Nelore 

cows 15.56 + 0.44 and 17.69+0.80 mm in two and 

three wave cycles, respectively. But Mayra et al. 

(1999) and Rhodes et al.(1997) reported higher size 

in zebu cows. 

The mean period of first exhibition of 

postpartum estrus was recorded as 109.50 + 4.56 

days. The incidence of estrus was recorded as 32.50 

% and 62.50 % during day and night time respectively. 

These findings were in corroboration with the report 

of Venkat Naidu et al (2010) 

It may be concluded that the knowledge 

about the follicular dynamics in postpartum lactating 

Ongole cows helps in planning and designing of the 

synchronization protocols and reducing the service 

period, inter calving period etc, for improving 

reproductive performance. 

ACKNOWLEDGEMENT 

The authors express their sincere gratitude 

to the SVVU, Tirupati for providing facilities to carry 

out the research work at Cattle Project, Live Stock 

Research Station, Lam Farm, Guntur. 

REFERENCES 

Akter. Z, Talukder. A.K., Akter. T., Kabir. M.S., 

Kamal. M.M., Bari. F.Y and Shamsuddin. M. 

2010. Ultrasonographic study of ovarian 

cyclicity in Zebu cows of Bangladesh. 5 (2), 

65. 

Alan Bennett Maia Alexandre Alves Ciro 

TorresReinaldo Jose Mendes Streets, Vicente 

Ribeiro Rocha Jr., Giovanni, Ribeiro e Carvalho, 

Jefferson Ferreira da Fonseca, Alberto Neto 

Marcatti Anderson George of Assisi-2003. 

58

RAMANA et al 

Characteristics of follicular dynamics and luteal 

regression in cows of Gir and Nelore cows after 

treatment with cloprostenol. Journal of Animal 

Science. 32(1) :1806-9290. 

Borges, A.M., Torres, C. A.A, Rocha Junior, V.R., 

Ruas, J.R.M., Gioso, M.M., Fonseca, J.E., 

Carvalho, G.R., Maffili, V.V,–2004. Follicular 

dynamics and ovulation time of non-lactating 

Gir and Nelore cows during two seasons of 

the year. Arquivo Brasillerio de Medicina 

Veterinaria e Zootecnia. 56:(3), 346-354. 

30 ref. 

Borges, A.M., Torres, C. A.A, Ruas, J.R.M., Rocha 

Junior, V.R., Carvalho, G.R –2001. Ovarian 

follicular dynamics in crosbred Holstein-zebu 

heifers. Arquivo Brasillerio de Medicina 

Veterinaria e Zootecnia. 53;5, 595-604. 18 ref. 

Evandro S. Sartorelli, Luciano M. Carvalho, Bergfelt, 

D.R, Ginther, O.J., Ciro M. Barros. 2005. 

Morphological characterization of follicle 

deviation in Nelore (Bos indicus) heifers and 

cows. Theriogenology 63 2382-2394. 

Figueiredo, R. A., Barros, C. M., Pinheiro, O. L 

and Soler J M P 1997 Ovarian follicular 

dynamics in Nellore Breed (Bos indicus) cattle. 

Theriogenology 47 : 489-1505. 

Gaur, M and G. N. Purohit, 2007. Follicular dynamics 

in Rathi (Bos indicus) cattle Veterinarskiarhi 

77 (2); 177-186. 

Ginther, O.J., M.A.Beg., F.X. Donadeu and D.R. 

Bergfelt, 2003. Mechanism of follicle deviation 

in monovular farm species. Anim. Reprod. 

Sci., 78: 239 – 257. 

Henao G Olivera – Angel M and Maldonado – Estrada 

J G 2000 Follicular dynamics during 

postpartum anestrus and the first estrous 

cycle in suckled and non-suckled Brahman 

(Bos indicus) cows. Animal Reproduction 

Science 63 : 127 – 136 

Knopf, L., J.P. Kastelic, E. Schallenberger and O.J. 

Ginther, 1989. Ovarian follicular dynamics in 

heifers: test of two-wave hypothesis by 

ultrasonically monitoring individual follicles. 

Dom. Anim. Endocrin., 6: 111-119. 

Krishna Mohan, U.K. Mishra, O.P Mishra, Singh, C 

and Prakash B.S. 2010. Follicular 

development pattern in post partum anestrous 

sahwal cows during Ovsynch protocol. 

IndianVet. Journal., 87: 448-450. 

Kulick, L.J., D.R. Bergfelt, K. Kot, and O.J. Ginther, 

2001. Follicle selection in cattle: Follicle 

deviation and codominance within sequential 

waves. Biol. Reprod., 65: 839 –846. 

Malhi, P.S., G.P. Adams and J. Singh, 2005. Bovine 

model for the study of reproductive aging in 

women: Follicular, luteal and endocrine 

characteristics. Biol. Reprod., 73: 45 – 53. 

Mayra Elena Ortiz, D. avila Assumpcao, Ed Hoffmann 

Madureira. Rubens Paes de arruda, Eneiva 

Carla carvalho Celeghini, Pedro Paulo 

Gimenez Gumoes, Pedro Henrique Candini, 

Jose Antonio Visintin. Sao Paulo 1999. Braz. 

J. Vet. Res. Anim. Sci. 36 (6) 

Mihm, M., P.J. Baker, J.L.H. Ireland, G.W. Smith, 

P.M. Coussens, A.C.O. Evans and J.J. 

Ireland, 2006. Molecular evidence that growth 

of dominant follicles involves a reduction in 

follicle stimulating hormone dependence and 

an increase in luteinizing hormone dependence 

in cattle. Biol. Reprod., 74: 1051 – 1059. 

Peters A R and Lamming G E 1986 Regulation 

of ovarian function in the postpartum cow : an 

endocrine model. Veterinary Record 118 : 236- 

239. 

Rajamahendran R and Taylor C 1990 

Characterisation of ovarian activity in 

postpartum dairy cows using ultrasound 

imaging and progesterone profiles. Animal 

Reproduction Science 22 : 171-180. 

Rhodes, F.M., A.J. Peterson, P.D. Jolly, W.H. 

McMillan, M.Donnison, A. Ledgard, G. Parton 

and D.R. Hall, 1997. Bovine ovarian follicle 

and oocyte characteristics after emergence of 

the first follicular wave. Theriogenology, 47: 

149 (Abst.). 

Rhodes, F.M., De’ath, G., Entwistle, K.W. 

1995Animal and temporal effects on ovarian 

59

POSTPARTUM OVARIAN FOLLICULAR DYNAMICS AND ESTRUS ACTIVITY 

follicular dynamics in Brahman heifers. Animal 

Reproduction Science, 38(4). 265-277. 

Roche, J. F., Crowe M. A and Bolland, M. P 1992 

Postpartum anestrus in dairy and beef cows. 

Animal Reproduction Science 28 : 371-378. 

Satheshkumar, S., Palanisamy. A., Subramanian. 

A., Kathiresan. D., and Ramadass. P. 2008. 

Follicular Wave Synchronization using GnRH 

Agonist in Jersey Crossbred cows. Indian J. 

Anim. Reproduction, 29 (2) 154 – 158. 

Venkata Naidu. G, Seshagiri Rao. A and Babu Rao. 

K, 2010. Progesterone profile in postpartum 

lactating Ongole (Zebu) cows. Indian Journal 

of Animal Reproduction 31 (1). 

Viana, J.H.M.; Ferreira, A., de M.; camargo, L.S, de 

A. 2000. Follicular dynamics in zebu cattle. 

Pasquisa Agropecuaria Brasileira. 35 (12) 

2501-2509. 40 ref. 

Vinoles, C., A. Meikle, M. Forsberg and E. Rubianes, 

1999. The effect of subluteal levels of 

exogenous progesterone on follicular 

dynamics and endocrine patterns during early 

luteal phase of the ewe. Theriogenology, 51: 

1351-1361. 

Wolfenson, D., G. Inbar, Z. Roth, M. Kaim, A. Bloch 

and R.Braw-Tal, 2004. Follicular dynamics and 

concentrations of steroids and gonadotropins 

in lactating cows and nulliparous heifers. 

Theriogenology, 62: 1042-1055. 

Zeitoun, M.M., H.F. Rodriguez and R.D. Randel, 1996. 

Effect of season on ovarian follicular dynamics 

in Brahman cows. Theriogenology, 45: 1577- 

1581. 

60

Research Notes 


DEVELOPMENT AND EVALUATION OF FIBER ENRICHED KHAKRA 

M. KIRTHY REDDY, P. UMADEVI, P.S.S.SAILAJA and APARNA KUNA 

Post Graduate Research Center, College of Home Science, 

Acharya N.G Ranga Agricultural University, Rajendra Nagar, Hyderabad-500030 


Dietary fiber components have unique 

chemical structures and characteristic physical 

properties (e.g., bulk/volume, viscosity, water-holding 

capacity, adsorption/binding or fermentability) that 

determine their subsequent physiologic behavior 

(Schneeman and Tietyen, 1994). Individuals with high 

intakes of dietary fiber appear to be at significantly 

lower risk for developing coronary heart disease, 

stroke, hypertension, diabetes, obesity, and certain 

gastrointestinal diseases (James et al., 2009). 

Khakra is a ready to eat, light crispy, crunchy 

flat bread snack of Gujarat in western India. It is a 

very versatile snack and can be eaten as fat free 

chips.Though khakra is gaining importance, the 

traditional khakra is made up of oil and also it is made 

up of refined flour which has very low fibre in it which 

in turn increases the calorie load. Low fibre and high 

fat content in the diets are making people landing in 

to various chronic life style disorders like 

diabetes,cancer etc. Hence, the present research was 

taken up to prepare the khakras with fiber rich 

ingredients and without addition of any visible fat 

thereby making the product therapeutic. 

The benefits of consuming foods rich in fiber 

are numerous, ranging from improved large bowel 

function to slowed digestion and absorption of 

carbohydrate and fat and reduced risk for certain 

diseases (Ali et al. 1982). 

Moreover, isoflavones contained in soybeans 

are effective cancer-preventive agents for lowering 

risks of various cancers (El Gharras, 2009). Evidence 

also points to the beneficial effects of soy isoflavones 

in the prevention of cardiovascular disease (El 

Gharras, 2009). Their potential health benefits of soyisoflavones 

include prevention of osteoporosis via 

phytoestrogen effects of isoflavones, and prevention 

of neovascularization in ocular conditions (Zhu et al., 

2005). 

Table 1. Khakras of different formulations 

Ingredients Control (T 1) (gms) T 2 (Experimental with 

methi leaf powder) 

(gms) 

T 3 (Experimental 

without methi leaf 

powder(gms) 

Wheat flour 84 - - 

Whole wheat flour - 46 48 

Defatted soy flour - 15 15 

Oats flakes flour - 20 20 

Methi leaf powder - 2 - 

Green chillies 10 10 10 

Ajwain seeds 3 3 3 

salt 4 4 4 

email: kirthy88@gmail.com 

61


There is therefore the need to develop a different 

approach to offer the weary consumers the 

opportunity to feed on improved formulations with 

substantive health benefits from wheat-soy 

combinations (Gomez et al., 2003). 

Hence, an attempt was made to increase 

fibre content of khakra with no additional visiblefat. 

Product development 

Three products T 1 , 

T 2, 

T 3 

were developed in 

various combinations of whole wheat flour/oats flake 

powder/defatted soy flour/methi leaf powder in 

different proportions which were given. 

Procedure 

Three products were developed using various 

combinations of whole wheat flour/ oats/ defatted soy 

flour/ methi leaf powder in different proportions. Roast 

and grind whole wheat, defatted soy bean and oat 

flakes in to fine powders. Methi leaves are blanched 

at 65 0 c for 2-3 minutes, dried and powered which was 

only added in T 2 

sample. Mix all the above ingredients 

including green chillies, salt and ajwain seeds with 

luke warm water. T 1 

sample is made up of only whole 

wheat flour, green chillies, salt and ajwani seeds. All 

these are kneaded in to individual doughs containing 

various ingredients. Keep it for 15 minutes a side. 

Make the dough into small balls of weight 7gms each 

and hot press them for 45-60 secs. 

Sensory evaluation Sensory evaluation was done 

to select the most acceptable recipes with 5 point 

Hedonic rating scale. 

Hedonic scale ratings Like extremely- 5, Like 

moderately – 4, Neither like nor dislike – 3, Dislike 

moderately – 2, Dislike extremely – 1. 

The nutrient compositions of the recipes were 

calculated for protein, fat, fiber, and energy by using 

the Nutritive value of Indian foods. (Gopalan et al, 

2004). The completed score cards after the 

evaluations were subjected to statistical analysis. 

(Snedecor,G.W and Cochran, W.G, 1983) 

Table 2 Sensory evaluation of khakras 

S.No. Colour Taste Flavour Texture Over all 

acceptability 

Control (T 1 ) 3.55 3.91 3.73 3.45 3.36 

T 2 4.18 3.82 4.45 4.55 4.36 

T 3 3.91 4.64 3.63 4.09 3.73 

Se D 0.261 0.343 0.213 0.384 0.210 

CD NS 0.705* 0.436* 0.789* 0.431* 

CV 15.804 20.442 12.953 22.876 12.895 

* significant NS- Non significant 

Khakra of three formulations were subjected to the 

sensory evaluation and the scores are recorded for 

the following attributes colour, taste, flavour, texture 

and overall acceptability were presented in Table 2. 

Colour 

No significant changes were observed 

among the scores for colour in which T 2 

(4.18%) 

scored highest followed by T 3 

(3.91%) and lowest 

score was recorded in T 1 

(3.55%). As per the 

observations made by Trongpanich et al. 2001, it 

was found that there was no significant difference in 

the preferential scores in colour, odor and taste 

between the snack samples that contained 5 – 15 % 

DFC and the control sample at p < 0.05. However, 

adding DFC (Dietary Fiber Concentrate) in the snacks 

made up of corn grits could improve the snack’s 

texture as the texture preferential scores of all the 

snack samples which contained 10 %DFC were 

higher than of the control one (Trongpanich et al., 

2001). The darker colour of the crumbs of whole 

wheat bread and fortified breads and biscuits have 

been reported by several authors (Singh et al., 2000; 

62

KIRTHY et al 

Akhtar et al., 2008; Serrem et al., 2011). The brownish 

bread appearance could be directly related to the 

increase in fiber content (Hu et al., 2007)T 2 

= modified 

recipe with 15gms defatted soy flour, 20gms oat 

flakes and 2gms methi leaf powder, T 3 

= modified 

recipe with 15gms defatted soy flour, 20gms oat 

flakes. T 1 

= control recipe made up of whole wheat 

flour. 

Control (T 1 

) T 2 

T 3 

Taste 

Scores for taste of khakras recorded 

significant changes (p


Table 3. Nutritional evaluation of Khakra 

S.No. Protein (gms) Fiber (gms) Fat (gms) Energy (Kcal) 

Control (T 1 ) 8.3 6.2 0.8 286 

T 2 14.7 13.56 1.43 316 

T 3 15 13.78 1.47 322 

SeD 0.490 2.588 3.657 1.393 

CD 1.222 6.456 NS 3.474 

CV 4.737 32.859 184.240 0.849 

Nutritional quality of khakras are tabulated 

in Table 3 and are presented in Fig 3. Significant 

differences (p

KIRTHY et al 

El Gharras H. 2009. Polyphenols: food sources, 

properties and applications – a review. 

International Journal Food Science 

Technology. 44: 2512-2518. 

Gomez, M., Ronda, F., Blanco, Caballero, P and 

Apesteguía A. 2003. Effect of dietary fibre on 

dough rheology and bread quality. European 

Food Research Technology. 216: 51-56. 

Hu, GH., Yang, F., Ma, Z and Zhou, Q. 2007. 

Development of Research and application of 

rice bran dietary fibre. China Food Addit., 84(5): 

80-85. 

James., W, Anderson, Pat baird, Richard H Davis J 

r, Stefanie ferreri, Mary knudtson, Ashraf 

koravm, Valerie waters and Christine l william. 

2009. Health benefits of dietary fiber. Nutrition 

Reviews. 67(4):188–205. 

Joel Ndife, L. O. Abdulraheem and U. M. Zakari. 2011. 

Evaluation of the nutrtional and sensory quality 

of functional breads produced from whole 

wheat and soya bean flour blends. African 

Journal of Food Science Vol. 5(8)466 – 472. 

Schneeman B.O and Tietyen. 1994. Dietary fiber. 

modern nutrition in health and disease. shills 

m. e. olson j. a. shike m. lea and fibiger 

philadelphia, pa. 8:89-100.Serrem C, Kock H, 

Taylor J. 2011. Nutritional quality, sensory 

quality and consumer acceptability of sorghum 

and bread wheat biscuits fortified with defatted 

soy flour. Int. J. Food Science Technology. 

46: 74-83. 

Singh R, Singh G and Chauhan GS (2000). Nutritional 

evaluation of soy fortified biscuits. J. Food 

Science Technology. 37: 162-164. 

Snedecor, G.W and Cochran, W.G.1983.Statistical 

Methods Oxford and IBH publishing 

company New Delhi. 

Trongpanich K, Pracha Boonyasirikool, Sumalai 

srikumlaitong, Chowladda taengpook and 

Udom kanjanapakornchai. 2001. Feasibility 

study on snack production by using dietary 

fiber concentrate from soymilk residue. Natural 

Science. 35: 188 – 194. 

Zhu D, Hettiarachchy N, Horax R, Chen P (2005). 

Isoflavone contents in germinated soybean 

seeds. Plant Foods Human Nutrition. 60: 147- 

151. 

65



INFLUENCE OF NITROGEN AND WEED MANAGEMENT ON GROWTH AND YIELD 

OF AEROBIC RICE (Oryza sativa L.) 

K. SANDYARANI, M. MALLA REDDY, R. UMA REDDY and P.V. RAO 

Department of Agronomy, Agricultural College, 

Acharya N.G. Ranga Agricultural University, Aswaraopet - 507 301 


The soil N dynamics and path way of nitrogen 

losses in dry sown rice system are different from 

lowlands and result in different fertilizer nitrogen 

recoveries. The alternate moist and dry soil conditions 

may stimulate nitrification-denitrification processes 

in dry sown rice, leading to loss of nitrogen through 

N 2 

and N 2 

O (Prasad, 2011). Hence, traditional lowland 

rice fertilizer doses may not be optimum for aerobic 

rice. Further, aerobic soil conditions and dry tillage 

practices, besides alternate wetting and drying are 

conducive for germination and growth of highly 

competitive weeds, which cause grain yield losses 

ranging from 50-91%, compared to conventional 

production systems (Singh et al., 2006), in which 

weeds are suppressed by standing water and 

transplanted rice seedlings have a “head start” over 

germinating weed seedlings. As the concept of 

aerobic rice in Andhra Pradesh is new, relatively few 

insights into weed management and nitrogen 

fertilization exist. Hence, the present investigation 

was planned out to find out the optimum dose of 

nitrogen and effective weed management practice in 

aerobic rice. 

Field experiment was conducted during 

kharif, 2011 at Regional Agricultural Research Station, 

Warangal, Andhra Pradesh. The soil of the 

experimental site was sandy loam in texture, medium 

in available nitrogen (288 kg ha -1 ), low in available 

phosphorus (7.6 kg ha -1 ) and medium in available 

potassium (73 kg ha -1 ) with a pH of 8.1. The 

experiment was laid out in randomized block design 

(factorial concept) with three nitrogen doses viz., 120, 

180 and 240 kg ha -1 and four weed management 

treatments, viz., pre-emergence application of 

pendimethalin @ 1.2 kg a.i. ha -1 + post-emergence 

application of pyrazosulfuron ethyl @ 30 g a.i. ha -1 at 

25 DAS, mechanical weeding at 20 and 45 DAS, 

weed free check and weedy check replicated thrice. 

Rice variety ‘WGL-32100’ was sown by dibbling at 

30 cm row spacing with solid rows with a seed rate 

of 40 kg ha -1 . Phosphorus and potash @ 60 and 50 

kg ha -1 were applied uniformly as basal in the form of 

single super phosphate and muriate of potash, 

respectively. Nitrogen was applied in the form of urea 

as per the treatments in three equal splits, each at 

basal, active tillering and panicle initiation stage. A 

range of mean minimum temperature of 19.7 to 26.1 

0 

C and mean maximum temperature of 27.1 to 33.0 

0 

C was recorded during the crop growth period. A 

total rainfall of 349.4 mm was received during the 

crop season in 26 rainy days. Supplemental irrigation 

was given as and when required to maintain the soil 

in moist condition. The weed density and dry weight 

were recorded in each plot using a quadrant of 1 m × 

1 m size. The data on weed density and dry weight 

were subjected to square root transformation before 

statistical analysis. 

Weed spectrum of the experimental field 

consisted of three groups of weeds like grasses, 

sedges and broad leaved weeds. The observed 

sedges were Cyperus rotundus, Fimbristylis 

argentea; grasses were Cynodon dactylon, 

Echinochloa colona, Dinebra retroflexa, Panicum 

javanicum and broad leaved weeds were Corchorus 

olitorius, Eclipta alba, Digera arvensis, Cyanotis 

axillaris, Psoralea corylifolia, Ammannia baccifera, 

Euphorbea geniculata, Phyllanthus niruri, Portulaca 

oleracea, Abutilon indicum, Celosia argentia, 

Commelina benghalensis, Merremia emarginata, 

Gynandropsis pentaphylla and Parthenium 

hysterophorus. Among these, broad leaved weeds 

were dominant followed by grasses and sedges in 

aerobic rice. 

email: ksragrico@gmail.com 

66

SANDYARANI et al 

Weed parameters like weed density, dry 

weight, weed control efficiency and weed index were 

not significantly influenced by the application of 

different doses of nitrogen except weed density at 

60 DAS and weed dry weight at 15 DAS and harvest 

(Table 1 ). At 60 DAS, the weed density recorded 

with 240 kg N ha -1 was significantly higher than 120 

kg N ha -1 but was at par with 180 kg N ha -1 . Preemergence 

application of pendimethalin @ 1.2 kg 

a.i. ha -1 followed by pyrazosulfuron ethyl @ 30 g a.i. 

ha -1 at 25 DAS registered significantly lower weed 

density at all the stages of observation compared to 

weedy check and mechanical weeding except at 60 

DAS where they were at par with each other (Table 

1). Similar trend was observed with respect to the 

dry weight of weeds at 60 DAS. Higher weed control 

efficiency was recorded with herbicides than 

mechanical weeding at all the stages which led to 

lower weed index in the former treatment. The 

interaction between the nitrogen levels and weed 

management treatments was significant with respect 

to the dry weight of weeds at 15 DAS and harvest 

only. The weed dry weight was significantly higher 

with mechanical weeding compared to herbicides 

application at all the doses of nitrogen both at 15 

DAS and harvest. Similarly, the dry weight of weeds 

significantly increased at 240 kg N ha -1 compared to 

120 kg N ha -1 at 15 DAS and 180 kg N ha -1 as well at 

harvest except in the weed free treatment. This could 

be attributed to vigorous growth and development of 

weeds owing to higher uptake of nutrients at higher 

rate of nitrogen application. Similar results were 

reported by Sharma et al. (2007). 

Nitrogen removal by the weeds at harvest 

was significantly higher at 240 kg N ha -1 over 120 kg 

N ha -1 but at par with 180 kg N ha -1 (Table 2). It was 

also significantly more with mechanical weeding 

compared to herbicidal application which was at par 

with weedy check due to higher density and dry weight 

of weeds in the latter treatment. Singh and Tripathi 

(2007) also reported similar results. 

Application of 240 kg N ha -1 recorded 

significantly higher yield attributes and grain yield over 

120 kg N ha -1 but at par with 180 kg N ha -1 except the 

test weight (Table 2). The straw yield was not 

significantly different among the different nitrogen 

doses. Increased yield under higher nitrogen levels 

might be due to adequate nutrient supply which would 

have resulted in increased growth and yield 

components. Similar findings were reported by 

Shekara et al. (2010). Among the weed management 

practices, pre-emergence application of pendimethalin 

@ 1.2 kg a.i. ha -1 followed by post-emergence 

application of pyrazosulfuron ethyl @ 30 g a.i. ha -1 at 

25 DAS recorded significantly higher yield attributing 

parameters, grain yield and straw yield over 

mechanical weeding and it was comparable with weed 

free treatment. The increased grain yield was mainly 

due to effective control of weeds in herbicide applied 

plots (Jayadeva et al., 2011). The significantly lowest 

yield attributing parameters and yield among the 

treatments were observed with unweeded check 

owing to severe crop-weed competition throughout 

crop growth period. 

Nitrogen uptake by grain and straw of rice 

increased significantly with increasing doses of 

nitrogen upto 240 kg N ha -1 (Table 2). Among all the 

weed management practices, significantly higher 

nitrogen uptake by grain as well as straw was 

observed with herbicides compared to weedy check 

but at par with mechanical weeding (Table 2). 

The highest net returns and returns per rupee 

invested were obtained with the application of 240 

kg N ha -1 over other two doses. Among the weed 

management practices, weed free check recorded 

highest values followed by pre-emergence application 

of pendimethalin @ 1.2 kg a.i. ha -1 followed by postemergence 

application of pyrazosulfuron ethyl @ 30 

g a.i. ha -1 at 25 DAS. These results corroborate the 

findings of Jayadeva et al. (2011). 

It can be stated that application of 180 kg N 

ha -1 was found to be optimum for aerobic rice in sandy 

loam soils of Telangana region and pre-emergence 

application of pendimethalin @ 1.2 kg a.i. ha -1 followed 

by post-emergence application of pyrazosulfuron 

ethyl @ 30 g a.i. ha -1 at 25 DAS was found to be 

effective and economical weed management practice 

in aerobic rice during kharif season. 

67

INFLUENCE OF NITROGEN AND WEED MANAGEMENT ON GROWTH 

Table 1. Influence of nitrogen doses and weed management on weed density, weed dry weight, weed control efficiency and weed index in aerobic 

rice 

Data subjected to square-root (“x+1) transformation; Figures in parentheses are original values. 

Pendi.-pendimethalin; py.ethyl-pyrazosulfuron ethyl; M.W-mechanical weeding; DAS-days after sowing 

68

SANDYARANI et al 

Table 2. Influence of nitrogen doses and weed management on yield attributes, yield, nitrogen uptake by crop and weeds and economics in 

aerobic rice 

Data subjected to square-root (“x+1) transformation; Figures in parentheses are original values. 

Pendi.-pendimethalin; py.ethyl-pyrazosulfuron ethyl; M.W-mechanical weeding; DAS-days after sowing 

69

INFLUENCE OF NITROGEN AND WEED MANAGEMENT ON GROWTH 

REFERENCES 

Jayadeva, H.M., Bhairappanavar, S.T., Hugar, A.Y., 

Rangaswamy, B.R., Mallikarjuna, G.B., 

Malleeshappa and Naik, C.C.D. 2011. 

Integrated weed management in aerobic rice. 

Agricultural Science Digest. 31 (1): 58-61. 

Prasad, R. 2011. Aerobic rice Systems. Advance in 

Agronomy. 111: 207-246. 

Sharma, R.P., Pathak, S.K and Singh, R.C. 2007. 

Effect of nitrogen and weed management in 

direct-seeded rice under upland conditions. 

Indian Journal of Agronomy. 52 (2): 114- 119. 

Shekara, B.G., Nagaraju and Shreedhara, D. 2010. 

Growth and yield of aerobic rice as influenced 

by different levels of N, P and K in Kaveri 

command area. Journal of Maharashtra 

Agricultural Universities. 35 (2): 195-198. 

Singh, B., Malik, R.K., Yadav, A and Nandal, D.P. 

2006. Weed management in direct seeded rice 

under different crop establishment methods. 

Extended summaries in the National 

Symposium on Conservation Agriculture and 

Environment. Varanasi, Uttar Pradesh, 26-28 

October 2006. pp.332-333 

Singh, K and Tripathi, H.P. 2007. Effect of nitrogen 

and weed control practices on performance of 

irrigated direct seeded rice (Oryza sativa). 

Indian Journal of Agronomy. 52 (3): 231-234. 

70



EFFECT OF SEED PRIMING ON BIOCHEMICAL CHANGES DURING SEED 

STORAGE OF MAIZE (ZEA MAYS L.) HYBRIDS 

M. RAM KUMAR, P. S. RAO, V. PADMA and K. V. RADHA KRISHNA 

Department of Crop Physiology, College of Agriculture 

Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad-500 030 


Maize is one of the most important cereal 

crops in the world. It is widely grown twice a year in 

certain agro climatic zones of India and the world as 

a staple food. Only 20-25 percent quantity of the seed 

is invariably stored and used by farmers in 

subsequent seasons. The remaining 75-80 percent 

of the seed quantity is transported to market during 

the first season itself to meet the demand of the 

farmers. The challenging task to overcome problems 

in process of the seed storage is the seed 

deterioration (viz., physiological or biochemical 

changes) which ultimately leads to loss of its vigour 

and viability. Priming is also thought to increase 

enzyme activity and counteract the effects of lipid 

peroxidation (Saha et al., 1990). During priming de 

novo synthesis of á-amylase is also documented 

(Lee and Kim, 2000). Metabolic activities in seeds 

increase with á-amylase activity, indicating higher 

seed vigour. Rapid and uniform field emergence, are 

two essential prerequisites to increase yield, quality 

and ultimately profits in crop production. Uniformity 

and percentage of seedling emergence of directseeded 

crops have a major impact on final yield and 

quality. 

The medium vigour (Six month old) seed lots 

of five maize hybrids viz., AH 122, SMH-9, DHM 

111, DHM 115 and DHM 117 having germination up 

to minimum seed certification standard (MSCS) were 

dried to 9% moisture are used for the study during 

2010-11. The seeds were subjected to priming at 25 o C 

with distilled water (T 1 

), PEG - 1.2 MPa (T 2 

), KNO 3 

@ 0.5% (T 3 

) along with untreated control (To). The 

invigoration treatments were given to the seeds 

by soaking in same quantity of water/aqueous 

solution of chemical (1: 1 seed and water/solution) 

for 18 hours at ambient temperature followed by drying 

back to original moisture content under shaded 

condition. Immediately after drying the treated seeds 

were stored in moisture impervious containers at 

ambient condition. The seed samples (primed and 

unprimed) were drawn at 0, 2, 4 and 6 months after 

treatment for studying the enzymatic changes during 

storage. The fresh seed sample of 0.5 g was 

homogenized with 5ml of chilled citrate buffer (pH 

5.0) and centrifuged at 10,000 rpm for 15 minutes. 

The supernatant was used for assessing the 

activity of á-amylase as per the procedure described 

by Choi et al. (1996). Enzyme extract for peroxidase 

was prepared by first freezing the weighed amount 

of seed sample (1g) in liquid nitrogen to prevent 

proteolytic activity followed by grinding with 10 ml 

extraction buffer (0.1M phosphate buffer, pH 

7.5,containing 0.5 mM EDTA). Brie was passed 

through four layers of cheese cloth and filtrate was 

centrifuged for 20 min. at 15000 G and the supernatant 

was used as enzyme extract. The enzyme extract 

was used for assesing the acivity of peroxidase 

described by Castillo et al. (1984). 

The α - amylase activity (mmol g -1 fr wt) 

was reported to be significantly different among 

treatments and hybrids. There was a significant 

interaction between hybrids and treatments at all 

duration of time after storage (Table 1). Among the 

five maize hybrids DHM 117 primed with water 

(Hydropriming) recorded maximum value (2.17 mmol 

g -1 ) of á- amylase activity while unprimed seeds of 

AH 122 recorded least value (1.81 mmol g -1 ). 

Significant interaction between hybrids and treatments 

at all time intervals of germination at all the months 

of storage was noticed. The findings are in conformity 

with the studies of Sung and Chang (1993); where in 

the hydropriming was superior to PEG 6000 in sh-2 

corn hybrid and was more effective in improving the 

emergence which resulted due to higher á- amylase 

and â-amylase activities. Similarly a laboratory 

study was conducted by Sathish and 

email: sampalrao@gmail.com 

71

EFFECT OF SEED PRIMING ON BIOCHEMICAL CHANGES DURING STORAGE 

Table 1. Effect of seed priming on á-amylase activity (mmol g -1 fr wt) of maize hybrids during storage 

S.No. 

Hybrid ‘0’ Month 2 Months after storage 

Treat 

ment 

Control 

HYDRO 

PE 

G 

KNO 3 Mean 

Contr 

ol 

HYDRO PEG KNO 3 Mean 

1 AH 122 5.07 5.15 5.10 5.13 5.11 4.95 5.03 4.98 5.00 4.99 

2 SMH 9 5.23 5.30 5.27 5.31 5.28 5.14 5.24 5.17 5.21 5.19 

3 DHM 

117 5.30 5.40 5.34 5.37 5.35 5.22 5.31 5.25 5.27 5.26 

4 DHM 

111 5.13 5.20 5.14 5.18 5.15 5.01 5.10 5.05 5.07 5.06 

5 DHM 

115 5.17 5.26 5.20 5.23 5.22 5.07 5.17 5.10 5.14 5.12 

Mean 13.93 5.17 5.25 5.21 5.22 5.21 5.08 5.17 5.11 5.14 

Hybrid (H) 

Treatment 

(T) 

HxT 

Hybrid 

(H) 

Treatment (T) 

S.Em± 0.004 0.004 0.009 0.002 0.002 0.004 

CD at 5% 0.013 0.012 0.027 0.006 0.005 0.012 

HxT 

S.No 

. Treat 

ment 

Hybrid 4 Months after storage 6 Months after storage 

Control 

HYDRO 

PE 

G 

KNO 3 

Mean 

Contr 

ol 

HYDRO 

1 AH 122 3.73 3.82 3.77 3.80 3.78 1.81 1.90 1.84 1.87 1.85 

2 SMH 9 3.88 4.12 3.97 4.03 4.01 2.02 2.14 2.05 2.07 2.07 

PEG 

KNO 

3 

Mean 

3 DHM 

117 4.01 4.37 4.04 4.07 4.12 2.08 2.17 2.14 2.15 2.14 

4 DHM 

111 3.81 3.89 3.83 3.85 3.85 1.88 1.97 1.91 1.94 1.92 

5 DHM 

115 3.86 3.95 3.90 3.93 3.91 1.94 2.11 1.98 2.01 2.03 

Mean 11.26 3.87 4.03 3.90 3.93 3.93 1.95 2.10 1.98 2.01 

Hybrid 

(H) 

Treatment 

(T) 

HxT 

Hybrid 

H) 

Treatment (T) 

S.Em± 0.003 0.0032 0.007 0.006 0.005 0.012 

CD at 5% 0.010 0.0091 0.020 0.018 0.016 0.036 

HxT 

Sundareshwaran (2010) who evaluated the influence 

of seed priming on biochemical parameters of fresh 

and aged seeds of maize hybrid (COH(M) 5) and its 

parental lines UMI 285 (female) and UMI 61 (male). 

Seeds were soaked in water @ 1% KH 2 

PO 4 

, 3% KNO 3 

and 2 % CaCl 2 

solution for 6 hrs. The results revealed 

that all the seed priming treatments affected the 

biochemical activity of seeds. However, seed priming 

with 1% KH 2 

PO 4 

for 6 h significantly increased the 

protein content, á-amylase and dehydrogenase 

activities in both fresh and aged seed lots of all the 

three genotypes. The results are also in conformity 

with Sathish and Sundareshwaran (2010) and 

Wattanakulpakin (2012). 

The peroxidase activity was observed at 

different months of storage (Table 2). The hybrid DHM 

117 showed maximum peroxidase activity with 

hydropriming indicating the treatment is the most 

reliable technique for increasing peroxidase activity 

there by increasing the vigour during storage. The 

significant interaction between hybrids and treatments 

was observed at all periods of storage. Priming 

72

KUMAR et al 

Table 2. Effect of seed priming on peroxidase activity (EU/Litre) of maize hybrids during storage 

S. 

No. 

Hy 

brid 

Treatm 

ent 

1 AH 

2 SMH 

‘0’ Month 2 Months after storage 

Control HYDRO PEG KNO 3 Mean 

Con 

trol 


122 86654.6 87252.0 86854.0 87054.0 86953.6 66346.0 66942.0 66545.0 66746.00 66644.75 

9 88376.0 88971.0 88574.0 88771.0 88673.0 67671.0 68272.0 68203.3 68071.00 68054.33 

3 DHM 

117 88966.0 89566.0 89161.0 89369.0 89265.5 68232.0 68834.0 68435.0 68632.00 68533.25 

4 DHM 

111 87215.0 87816.0 87417.0 87616.0 87516.0 66545.0 67142.0 66745.3 66943.00 66843.83 

5 DHM 

115 87983.0 88380.0 87988.0 88183.0 88133.5 67107.0 67706.0 67305.0 67508.00 67406.50 

Mean 13.93 87838.8 88397.0 87998.8 88198.6 88108.3 67180.2 67779.2 67446.73 67580.00 

Hybrid(H) Treatment(T) HxT 

Hybrid(H 

) 

Treatment(T) 

S.Em± 0.77 0.69 1.54 0.52 0.46 1.04 

CD (0.05) 2.21 1.98 4.43 1.50 1.34 3.01 

HxT 

S.No. 

Hybri 

d 

Treat 

ment 

1 AH 

122 

2 SMH 

9 

3 DHM 

117 

4 DHM 

111 

5 DHM 

115 

4 Months after storage 6 Months after storage 

Control HYDRO PEG KNO 3 Mean 

Con 

trol 


43105 43702 43306 43508.0 43405.3 17003 17601.3 17202 17407 17303.3 

44793 45394 44991 45191.7 45092.3 18694 19293 18894 19097 18994.5 

45352 45958 45557 45756.0 45655.8 19256 19857 19456 19652 19555.3 

43663 44266 43867 44065.3 43965.3 17564 18165 12433 17961 16530.8 

44235 44830 44438 44632.0 44533.8 18128 18729 18328 18524 18427.3 

Mean 44229 44830 44431.8 44630.4 

Hybrid 

(H) 

Treatment (T) 

HxT 

4453 

0.5 

18129 18729 

Hybrid 

(H) 

17262. 

6 

Treatment (T) 

18528.2 

S.Em± 0.85 0.76 1.71 0.65 0.58 1.30 

CD at 5% 2.45 2.19 4.91 1.86 1.67 3.74 

HxT 

treatments showed superior values in comparision 

to control. Syed et al., (2010) revealed that the 

activity of catalase and peroxidase during accelerated 

ageing and repair priming treatment of maize (Zea 

mays L.) seeds. Seed priming with KNO 3 

was 

performed at different concentrations of (0.5, 1, 2.5 

and 4%) and seeds were soaked for 8, 12 and 24 h in 

each individual concentration and the results showed 

that there was significant difference for duration of 

ageing treatment on germination characteristics of 

maize seeds. Increasing ageing duration resulted 

higher reduction in germination characteristics. KNO 3 

had positive effects on seed germination of aged 

seed. This was higher in application of 0.5% KNO 3 

73

EFFECT OF SEED PRIMING ON BIOCHEMICAL CHANGES DURING SEED STORAGE 

for 8 h and 2.5% for 24 h. Antioxidant activity of 

aged seeds increased after seed priming treatments. 

Seed priming with hormones was more effective than 

seed priming with KNO 3 

in activation of antioxidant 

enzymes. It was suggested that using seed 

enhancement treatments like seed priming could 

improve aged and non-aged seed performance. 

REFERENCES 

Castillo F I, Penel I and Greppin H, 1984. Peroxidase 

release induced by ozone in Sedum album 

leaves, Plant Physiology, 74: 846-851. 

Choi Y H, Kobayashi M and Sakurai A, 1996. 

Endogenous gibberellins A1 level and á- 

amylase activity in germinating rice seeds, 

Journal of Plant Growth Regulation, 15: 147- 

151. 

Lee S S and Kim J H, 2000. Total sugars, á-amylase 

activity, and emergence after priming of normal 

and aged rice seeds, Korean Journal Crop 

Sciences, 45:108–111 

Saha R, Mandal A K, and Basu R N, 1990. Physiology 

of invigoration treatments in soybean (Glycine 

max L.) Seed Science and Technology, 18: 

269–276. 

Sathish S and Sundareswaran S, 2010. Biochemical 

evaluation of seed priming in fresh and aged 

seeds of maize hybrid (COH (M) 5) and its 

parental lines, ISSN vol. 4: 2. 

Sung F J M and Chang Y H, 1993. Biochemical 

activities associated with priming of sweet corn 

seeds to improve vigor, Seed Science and 

Technology 21, 97–105. 

Syed, Ata Siadat, Amir Moosavi and Mehran Sharafi 

Zadeh, 2012. Effects of seed priming on 

antioxidant activity and germination 

characteristics of maize seeds under different 

ageing treatment, Research Journal of Seed 

Science, 5: 51-62. 

Wattanakulpakin, Songsin Photchanachai, Khanok 

Ratanakhanokchai, Khin Lay Kyu, Panumart 

Ritthichai and Shuichi Miyagawa, 2012. 

Hydropriming effects on carbohydrate 

metabolism, antioxidant enzyme activity and 

seed vigor of maize (Zea mays L.), African 

Journal of Biotechnology, 11(15): 3537-3547. 

74



AN ECONOMIC ANALYSIS OF BLACKGRAM IN 

GULBARGA DISTRICT OF KARNATAKA 

DEEPAK HEGDE, D. V. SUBBA RAO, N. VASUDEV and K. SUPRIYA 

College of Agriculture, ANGR Agricultural University, Rajendranagar, Hyderabad-500030 


The area of traditional cultivation of black 

gram is confined to the South Asia and adjacent 

regions (India, Pakistan, Afghanistan, Bangladesh 

and Myanmar). About 70 per cent of world’s black 

gram production comes from India and it is the largest 

producer as well as consumer of black gram. It 

produces about 1.5 million tonnes of blackgram 

annually from about 2.5 million hectares of area with 

an average productivity of 400 kg per hectare. Black 

gram output accounts for about 10 per cent of India’s 

total pulse production. The major producing states 

are Andhra Pradesh, Maharashtra, Orissa, Madhya 

Pradesh, Tamil Nadu and Uttar Pradesh. The study 

was under taken in Karnataka with specific objective 

to estimate the costs and margins at different stages 

in marketing channel of blackgram. 

Combination of purposive and random 

sampling techniques was used for selection of district, 

markets, market functionaries and farmers required 

for the study. Two taluks in this district were selected 

based on the probability proportional to the area under 

the study. Two villages from each taluk were selected 

based on area cultivated under pulses and obtained 

yield. The required primary data were obtained from 

25 sample farmers from each village by interview 

method making a sample of 100 from the district as 

a whole. Farmers are categorized into small and large 

based on the land holdings. 

It was also intended to study the market 

functionaries involved at different stages of the value 

chain of pulses, their marketing costs and margins. 

Commission agents (15), traders (15), processors 

(15), wholesaler (10) and retailers (10) were selected 

at random. Secondary data pertaining to the agro 

economic features of the study area were collected 

from tahaseldar office and Agriculture Department of 

Gulbarga district. Multiple linear regression model was 

fitted to analyze the factors influencing the profit 

margin of blackgram. 

The cost of cultivation of blackgram was 

estimated at Rs.27, 671. It increased with the size 

of holding from Rs. 27,044 for small farmers to Rs. 

28,307 for large farmers (Table.1). It was observed 

that the operational costs accounted for a major share 

in the total costs on all the categories of farms. The 

total operational costs were Rs. 22,972, Rs. 24,057 

and Rs. 23,493 for small farmers, large farmers and 

the sample as a whole respectively. Higher 

operational cost of large farmers was due to hiring 

more human labour and tractor services and incurring 

more cost on manures and fertilizers and plant 

protection chemicals. 

The price spread was studied in two 

channels. Commission agents were involved in 

channel-I while traders were involved in channel-II. 

On an average, the producer incurred a cost of Rs. 

159 per quintal of blackgram towards soot, gunny 

bag, labour charges, transportation, weighing (Rs.) 

and miscellaneous in channel I. Commission agent 

incurred a cost of Rs. 90 in channel I. In channel II, 

blackgram producer incurred a marketing cost of Rs. 

199. Total marketing cost incurred by the trader was 

Rs. 135. Processor’s marketing cost and wholesalers 

marketing costs were the same in both the channels. 

Total marketing cost incurred by retailer was Rs. 76. 

The results were in conformity with the findings of 

Banerjee and Palke (2010). 

Because of more marketing cost incurred by 

farmers and more margins obtained by the 

middlemen, producers share in consumer’s rupee was 

less in channel II (73 per cent) than in channel-I (78 

per cent). Similar views were shared by Govind Pal 

(2002). Even though the producers share in 

consumer’s rupee was less in channel-II when 

compared to channel-I, most of the farmers in Jewargi 

taluk of Gulbarga district were selling their produce 

in this channel. 

email: deepakhegde236@gmail.com 

75

AN ECONOMIC ANALYSIS OF BLACKGRAM IN GULBARGA 

The total costs (Rs. 798) and margins (Rs. 

633) were more in channel-II than channel-I, because 

of which the price spread was more and producers 

share in consumer’s price was less in channel II. 

Price spread was Rs. 1093 and Rs. 881 in channel I 

and II respectively. 

Multiple regression model was employed to 

study determinants of profit margin per quintal of 

pulses. Out of five variables included in the model 

three variables significantly explained the variation 

in profit margin per quintal of pulses (R 2 = 0.92). 

Operating cost of production, marketing cost and 

gross price received by the producer were found 

significantly influencing profit margin (Table 3). 

The coefficient of determination (R 2 = 0.92) 

showed that about 92 percent of the variation in profit 

was explained by the variables included in the model. 

The result showed that, one rupee increase in 

operating cost decreases the profit margin per quintal 

by Rs.0.72. Reduction in the marketing cost increases 

the profit margin per quintal of blackgram. If the 

marketing cost is increased by one rupee, farmer 

experiences less profit margin (Rs.5.66). If the market 

price received by the producer is increased by one 

rupee, the profit margin of blackgram will be 

increased by Rs.0.74. Education level and fixed cost 

of production were found to be non-significant. 

Table 1. Cost of cultivation of Blackgram (per hectare) 

Sl.No 

Particulars 

Farmers 

Small farmer Large farmer Pooled 

1.Operational cost (Rs.) 

a Human Labour 

i. Owned labours 

ii. Hired labours 

b. Bullock labour 

i. Owned labours 

7995 8162 8104 

5914 2471 5077 

2080 5692 3027 

5167 5016 5059 

3468 3229 3304 

ii. 

Hired labours 

1699 1787 1754 

c 

Tractor Power 

608 1220 819 

d. Seed 

e. FYM 

f. Fertilizers 

g. 

Plant protection 

chemicals 

h. Interest on working 

capital 

Total operational 

cost (Rs.) 

a. Land Revenue 

752 783 773 

1750 1560 1643 

2998 3082 3052 

2200 2660 2507 

1503 1574 1537 

22972 24057 23493 

100 100 100 

76

DEEPAK et al 

Table 2 Price spread and marketing margin for blackgram (Rs/qtl) 

S.No 

Particulars 

Channel I (Rs/qtl) 

Blackgram 

Channel II (Rs/qtl) 

1 Producer 

a) Gross price received 3371 3198 

b) Marketing cost 159 199 

Net price received 3211 2999 

2 Commission Agent 

a) Marketing cost 90 -- 

b) Margin 69 

3 Trader 

a) Purchase price 3198 

b) Marketing cost -- 135 

c) Selling price 3450 

d) Margin 117 

4 Processor 

a) Purchase price 3529 3450 

b) Marketing cost 126 126 

c) Processing cost 199 199 

d) Selling price per quintal of dal Dall 5790 5790 

e) 

Selling price of per quintal of dal 

multiplied with conversion factor 

(CF) 

3821 3821 

f) Margin 166 245 

5 5 Wholesaler Wholesaler 

a) 

a) 

Purchase 

Purchase 

price 

price 

3821 

3821 

3821 

3821 

b) 

b) 

Marketing 

Marketing 

cost 

cost 

62 

62 

62 

62 

c) 

c) 

Selling price per quintal of dall 


5950 

5950 

5950 

5950 

d) 

d) 



multiplied with CF 

multiplied with CF 

3927 

3927 

3927 

3927 

e) 

e) 

Margin 

Margin 

106 

106 

106 

106 

6 

6 

Retailer 

Retailer 

a) 

a) 

Purchase price 

Purchase price 

3927 

3927 

3927 

3927 

b) 

b) 

Marketing cost 

Marketing cost 

76 

76 

77 

77 

c) 

c) 



6200 

6200 

6200 

6200 

77

AN ECONOMIC ANALYSIS OF BLACKGRAM IN GULBARGA 

Table 3 Regression estimates of determinants of profit margin for blackgram 

Y= Profit margin per quintal of blackgram 

Variables Coefficients Standard Error t Stat 

Intercept 

Operating cost of production 

Fixed cost of production 

455.30* 176.86 2.57 

-0.72** 0.10 -6.85 

0.02 0.27 0.06 

Marketing cost -5.66 ++ 2.62 -2.16 

Market price of the produce 0.74** 0.09 8.01 

Education level 455.30 176.86 2.57 

F value 27.61 

R 2 0.92 

Adj. R 2 0.89 

N 18 

++ 

Significant at 5 % level, * Significant at 5 % level, ** Significant at 1 % level 

Note: Operating cost and fixed costs of production includes total of all components 

REFERENCES 

Banerjee, Gangadhar and Palke, L. M. 2010. 

Economics of Pulses Production and 

Processing of India. National Bank for 

Agriculture and Rural Development. 

Occasional Paper - 51 

Govind Pal. 2002. Marketing of gram in Block 

Shahabganj; district Chandauli, Uttar Pradesh 

(an economic analysis). Indian Journal of 

Agricultural Economics. 57(3): 388 

78



GENE ACTION AND COMBINING ABILITY STUDIES IN CHICKPEA 

(Cicer arietinum L.) 

B. REDDY YAMINI, V. JAYALAKSHMI, B. NARENDRA and P. UMAMAHESHWARI 

Department of Genetics and Plant Breeding, Agricultural College, 

Acharya N.G.Ranga Agricultural University, Mahanandi -518 503 


Chickpea (Cicer arietinum L.) 2n=2x=16, is 

the third most important food legume globally, 

occupying an area of 11.55 m ha with a production of 

10.46 m t (FAO STAT 2010). India is the largest 

producer of chickpea in the world sharing about 72% 

of area and production globally and accounts for about 

30% and 38% of national pulse acreage and 

production respectively. Though India is the largest 

producer of chickpea, the productivity is low (943 

kg/ha) compared to other chickpea producing 

countries viz., Mexico (1809 kg/ha), Australia (1268 

kg/ha) and Ethiopia (1265 kg/ha) and the production 

is not adequate to meet the domestic demand. 

Consequently India is importing chickpeas every 

year. Hence, there is every need to to improve the 

productivity potential of chickpea through appropriate 

breeding strategies. Choice of an appropriate breeding 

procedure for improving a trait depends mainly on 

the nature of gene action involved in the inheritance 

of the character, thus, emphasizing the importance 

of genetic analysis for yield and its components. In 

the present investigation, an attempt has been made 

to assess the nature of gene effects for yield and its 

component characters following the diallel analyses, 

so as to design breeding strategies for improvement 

of chickpea yield potential. 

The experimental material consisted of seven 

parents and also twenty-one F 1 

s, derived from seven 

parental genotypes viz., NBeG-3, JG-11, ICCV 05106, 

MNK-1, ICCV 95333, KAK-2 and Vihar, crossed in 

diallel fashion excluding reciprocals. The 

experimental material was sown in a Randomized 

Block Design with three replications during Rabi 2011- 

12. Data were recorded on five competitive randomly 

selected plants per replication from each treatment 

for seven characters viz., days to 50 per cent 

flowering, days to maturity, plant height, number of 

branches per plant, number of pods per plant, seed 

yield per plant and 100-seed weight. Data is subjected 

to combining ability analysis according to Model I 

and Method II of Griffing (1956). 

The analysis of variance revealed significant 

differences among the treatments for all the seven 

traits indicating considerable amount of variability 

thus justifying the use of material under study. 

Analysis of variance for combining ability (Table 1) 

revealed significant general combining ability (gca) 

and specific combining ability (sca) for all the 

characters studied, indicating the importance of both 

additive as well as non additive genetic components 

of variation in the expression of these attributes. 

Importance of both types of gene effects has been 

observed earlier in chickpea for seed yield and related 

attributes by Preethi Verma and Waldia (2010), 

Bharadwaj et al (2009) and Patil et al (2006). 

However, variance components indicated that the 

magnitude of the non additive (sca) variance was 

considerably higher than additive (gca) variance for 

all the characters except plant height and 100 seed 

weight, indicating the preponderance of non additive 

genetic effects (dominance and epistasis) in 

controlling the expression of these characters. The 

predominance of non additive gene action was 

reported by Sarode et al. (2001) for days to 50 per 

cent flowering and days to maturity; Bhardwaj and 

Sandhu (2009) for number of branches per plant, 

number of pods per plant and seed yield per plant. 

Gupta et al. (2007) reported the importance of additive 

gene action in inheritance of plant height and 100 

seed weight. 

The estimates of gca effects (Table 2) 

indicated that parents NBeG-3, JG-11, ICCV 05106 

and Vihar were good general combiners for number 

of pods per plant, where as NBeG-3 and JG-11 

showed significantly higher gca effects for number 

of branches per plant. With regard to phenological 

email: reddyyamini56@gmail.com 

79


S. 

No. 

Character 

gca 

(df=6) 

sca 

(df=21) 

error 

(df=54) 

² gca 

² sca 

² gca 

/ ² 

sca 

1 Days to 50% flowering 40.42 ** 12.15 ** 2.43 4.22 9.72 0.43 0.41 

2 Days to maturity 9.49 ** 2.00 ** 0.62 0.99 1.38 0.71 0.50 

3 Plant height (cm) 70.00 ** 6.30 ** 1.13 7.65 5.17 1.48 0.71 

h 2 

4 

5 

Number of branches 

per plant 

Number of pods per 

plant 

37.03 ** 18.75 ** 0.61 4.05 18.14 0.22 0.18 

533.32 ** 360.87 ** 1.28 59.12 359.60 0.16 0.25 

6 Seed yield per plant (g) 7.16 ** 30.70 ** 0.16 0.78 30.54 0.03 0.05 

7 100 seed weight (g) 276.73 ** 20.19 ** 1.35 30.60 18.83 1.62 0.75 

* Significant at Pd”0.05, ** Significant at P d”0.01, gca – general combining ability; sca – specific combining 

ability; s² gca – variance due to gca ; s² sca – variance due to sca. h 2 - heritability in narrow sense 

Table 2. Estimates of general combining (gca) effects for seven yield attributes in Chickpea 

S. 

No. 

Genotype 

Character 

NBeG-3 JG-11 

ICCV0 

5106 

M N 

K-1 

ICCV9 

5333 

KAK-2 

Vihar 

S.Em 

of Gi 

S.Em 

of 

Gi-Gj 

1 

Days to 50 

percent Flowering -0.476 -3.03** -2.59 ** 1.97 ** 1.60 ** 0.49 2.04 ** 0.48 0.73 

2 Days to maturity -1.00 ** -1.15 ** -0.30 0.85 ** 0.00 -0.185 1.78 ** 0.24 0.37 

3 Plant height -2.02 ** -2.75 ** 0.53 4.92 ** 1.91 ** -2.63 ** 0.04 0.33 0.50 

4 

Number of 

branches per 

plant 

2.22 ** 2.85 ** -0.01 -3.18 ** -1.08 ** -0.55 * -0.25 

0.24 0.37 

5 

6 

7 

Number of pods 

per plant 

Seed yield per 

plant 

100 seed 

weight 

2.77 ** 12.19 ** 3.16 ** -12.95 ** -3.95 ** -2.22 ** 1.02 ** 0.35 0.53 

0.76 ** 0.46 ** -0.71 ** -1.41 ** - 

0.56 ** 0.51** 0.96 ** 0.12 0.19 

-3.71 ** -6.61 ** -3.34 ** 10.31 ** 3.00 ** -0.38 0.73 * 0.36 0.55 

*Significant at Pd” 0.05 , **Significant at Pd”0.01 

traits, JG-11 and ICCV 05106 recorded significant 

desirable negative gca effects for days to 50 per cent 

flowering, while, NBeG-3 and JG-11 for days to 

maturity, suggesting that these parents could be good 

general combiners for breeding for earliness. The high 

general combining ability for plant height and 100 

seed weight was recorded in MNK-1 and ICCV 95333. 

For seed yield per plant the genotypes viz., NBeG-3, 

80

YAMINI et al 

Table 3. Estimates of specific combining (Sca) effects for seven yield attributes in Chickpea 

S. 

No Cross D 50 F DM PH NB/P NP/P SY/P 

100 

SW 

1 NBeG -3 x JG-11 2.56 -1.77* 2.43* 1.81* -11.74** 3.42** 1.64 

2 

3 

NBeG-3 x ICCV05106 2.44 0.71 -0.52 -4.76** 7.15** 

NBeG-3 x MNK-1 -2.44 -1.77* -0.48 1.68* -4.44** 

- 

4.76** 

- 

11.79** 

- 

3.44** -4.88** 

4 NBeG-3 x ICCV 95333 1.26 0.75 -0.84 7.77** 31.99** 5.53** 0.6 

5 NBeG-3 x KAK-2 1.37 0.27 -1.19 2.05** 4.32** 0.82* 5.52** 

6 NBeG-3 x Vihar -3.85** -1.03 2.31* -0.43 3.64** 7.51** 1.27 

7 JG-11 x ICCV 05106 2.67 -0.47 1.14 5.53** 23.63** 5.67** 1.35 

8 JG-11 x MNK-1 6.11** 0.05 4.57** 1.04 -0.48 4.66** -2.15* 

9 JG-11 x ICCV95333 -3.52* 0.23 -4.83** -2.23** -7.2** -4.38** -4.89** 

10 JG-11 x KAK-2 -3.41* -1.25 1.55 2.02** 33.29** 6.1** -1.72 

11 JG-11 x Vihar -5.3** -1.55* -0.21 -0.06 30.05** 0.96** -0.77 

12 ICCV05106 x MNK-1 -2.33 1.86* 0.93 2.1** -0.36 0.66 1.33 

13 

ICCV05106 X ICCV 95333 -5.96** 0.05 2.87** 1.13 4.66** 0.06 5.85** 

14 ICCV05106 x KAK-2 -2.85* 0.9 -1.57 -3.62** -15.4** -0.21 1.83 

15 ICCV05106 x Vihar -2.41 -2.4** -0.3 7.63** 20.86** 8.78** -0.57 

16 MNK-1 x ICCV 95333 -0.52 -0.44 0.86 -3.08** 0.66 2.33** 4.77** 

17 MNK-1 x KAK-2 -3.41* -0.58 -4.61** 5.78** 11.51** 4.47** -6.82** 

18 MNK-1 x Vihar 1.7 -0.55 0.79 -5.53** -8.45** -3.95** 2.37* 

19 ICCV95333 x KAK-2 3.3* -1.07 1.6 3.69** 4.04** 4.61** 1.4 

20 ICCV 95333 x Vihar 1.74 -0.36 -3.35** 0.59 0.69 -0.64 -2.26* 

21 KAK-2 x Vihar 2.85* 0.16 2.92** -4.61** -6.99** 1.42 4.38** 

S.E of Sii-Sjj 1.64 0.83 1.12 0.82 1.19 0.42 1.23 

S.E of Sij-Sik 2.08 1.05 1.42 1.04 1.51 0.53 1.55 

S.E of Sij-Skl 1.94 0.98 1.33 0.98 1.41 0.49 1.45 

* Significant at Pd” 0.05, ** Significant at Pd” 0.01 

D 50 F= Days to 50% flowering, DM= Days to maturity, PH= Plant height, NB/P= Number of branches per 

plant, NP/P= Number of pods per plant, SY/P= Seed yield per plant, 100 SW=100 seed weight. 

JG-11 and Vihar exhibits highly significant positive 

gca effects indicating that they were good general 

combiners for seed yield. So, these parents can be 

exploited for the development of improved lines of 

chickpea, because high gca effects are mostly due 

to additive gene effect or additive x additive 

interaction effects which are fixable (Griffing, 1956). 

The sca effect is an important criterion for 

the evaluation of hybrids. Among the various gene 

interactions contributing towards sca, the additive x 

additive type of gene interaction is fixable in 

segregating generations in self pollinated crops like 

chickpea. More over ultimate aim of a plant breeder 

is to develop potential homozygous lines through 

hybridization. The cross combinations with significant 

desirable sca effects along with mean performance 

and gca effects of the parents are listed in Table 3. 

JG-11 x Vihar had significant desirable sca effects 

for seed yield per plant and number of pods per plant 

81


and also gave highly significant negative sca effects 

for days to 50 per cent flowering and days to maturity. 

A few crosses viz., JG-11 x ICCV 95333, JG-11 x 

KAK-2, ICCV 05106 x ICCV 95333 and ICCV 05106 

x KAK-2 also recorded highly significant sca effects 

as well as low mean values for days to 50 per cent 

flowering, indicating early maturity and these crosses 

involved only one good combiner suggesting additive 

x dominance gene effects in these crosses. In these 

crosses, additive component present in good 

combiners and the complimentary epistatic effects 

in F 1 

hybrid might work in the same direction to 

maximize the desirable effects of this trait in 

segregants. Promising crosses viz., NBeG-3 x ICCV 

95333, JG-11 x ICCV 05106, JG-11 x KAK-2 and 

ICCV 05106 x Vihar exhibited significant sca effects 

Table 4. Specific combining ability effects, mean performance and general combining ability effects 

of parents and promising crosses for yield and yield attributes 

Character 

Days to 50 per 

cent flowering 

Crosses with high per se 

performance and significant 

sca effects 

JG-11 x ICCV 95333 

JG-11 x KAK-2 

JG-11 x Vihar 

ICCV 05106 x ICCV 95333 

ICCV 05106 x KAK-2 

sca effects 

-3.52* 

-3.41* 

-5.3** 

-5.96** 

-2.85* 

Per se 

performa 

nce 

35.3 

34.3 

34.0 

33.3 

35.3 

gca effects of 

parents 

G x P 

G x P 

G x P 

G x P 

G x P 

Days to maturity NBeG-3 x JG-11 -1.77* 88.3 G x G 

Plant height JG-11 x MNK-1 

4.57** 47.7 P x G 

ICCV 05106 x ICCV 95333 2.87** 46.3 P x G 


branches per 

plant 

Number of pods 

per plant 

Seed yield per 

plant 

NBeG-3 x JG-11 

NBeG-3 x ICCV 95333 

NBeG-3 x KAK-2 

JG-11 x ICCV 05106 

JG-11 x KAK-2 

ICCV 05106 x Vihar 



JG-11 x ICCV 05106 

JG-11 x KAK-2 

JG-11 x Vihar 


NBeG-3 x JG-11 


NBeG-3 x Vihar 

JG-11 x ICCV 05106 

JG-11 x MNK-1 

JG-11 x KAK-2 


MNK-1 x KAK-2 

ICCV 95333 x KAK-2 

100 seed weight ICCV 05106 x ICCV 95333 

MNK-1 x ICCV 95333 

MNK-1 x Vihar 

KAK-2 x Vihar 

1.81* 

7.77** 

2.05** 

5.53** 

2.02** 

7.63** 

7.15** 

31.99** 

23.63** 

33.29** 

30.05** 

20.86** 

3.42** 

5.53** 

7.51** 

5.67** 

4.66** 

6.1** 

8.78** 

4.47** 

4.61** 

5.85** 

4.77** 

2.37* 

4.38** 

27.5 

29.5 

24.3 

29.0 

24.9 

28.0 

58.5 

76.3 

84.4 

88.7 

88.7 

70.5 

20.7 

21.8 

25.3 

21.5 

19.8 

23.1 

25.1 

19.6 

20.6 

38.5 

51.1 

46.4 

37.7 

G x G 

G x P 

G x P 

G x P 

G x P 

P x P 

G x G 

G x P 

G x G 

G x P 

G x G 

G x G 

G x G 

G x P 

G x G 

G x P 

G x P 

G x G 

P x G 

P x G 

P x G 

P x G 

G x G 

G x G 

P x G 

82

YAMINI et al 

coupled with high per se performance for seed yield 

and yield attributes like number of branches and 

number of pods per plant. For plant height and 100 

seed weight ICCV 05106 x ICCV 95333 (poor x good) 

registered significant sca effect with high mean 

values. Hence this cross could be exploited for 

identifying tall and bold seeded genotypes in the 

segregating generations. 

The results of the present investigation 

revealed the preponderance of non additive gene 

action for yield and yield components and therefore 

heterosis breeding may be rewarding for improving 

chickpea. But the practical production of hybrid gram 

is not biologically feasible due to small size and 

cleistogamous nature of the flowers and strong 

hybridization barriers (Preethi Verma and Waldia, 

2010). In view of such problems, Jensen’s (1970) 

selective diallel mating system and its modifications 

(Frey, 1975) would be utilized for the creation and 

isolation of recombinants to breed superior chickpea 

varieties. The crosses NBeG-3 x JG-11 for seed yield 

and number of branches, NBeG-3 x ICCV 05106, JG- 

11 x ICCV 05106 and ICCV 05106 x Vihar for number 

of pods per plant and NBeG-3 x Vihar and JG-11 x 

KAK-2 for seed yield per plant exhibited significant 

sca effects coupled with high per se performance 

with good x good combiners. Due to additive x additive 

effects and their possibility of fixation, single plant 

selection could be practiced in segregating 

generations to isolate purelines from these crosses. 

REFERENCES 

Bhardwaj, R and Sandhu, J. S. 2009. Components 

of variance analysis in chickpea. Jounal of 

Food Legumes. 22(4): 254-255. 

Bharadwaj, R., Sandhu, J. S., and Gupta, S. K. 2009. 

Gene action and combining ability estimates 

for yield and other quantitative traits in 

chickpea. Indian Journal of Agricultural 

Sciences. 79: 895-900. 

Frey, K. J. 1975. Breeding concepts and techniques 

for self pollinated crops. Proceedings of 

International workshop on grain legumes, 

ICRSAT, Patancheru, India. 257-278. 

Griffing, B. 1956. A generalized treatment of the use 

of diallel cross in quantitative inheritance. 

Heredity. 10:31-34. 

Jensen, N. F. 1970. A diallel selective mating system 

for cereal breeding. Crop Science. 10:629-635. 

Patil. J. V. Kulkarni, S. S and Gawande, V. L. 2006. 

Genetics of quantitative characters in chickpea 

(Cicer arietinum L.). New Botanist- International 

Journal of Plant Science Research. 33:1-4. 

Preethi Verma and Waldia, R. S. 2010. Diallel 

analysis for nodulation and yield contributing 

traits in chickpea. Journal of Food Legumes. 

23 (2): 117-120. 

Sarode, N. D. Deshmukh, R. B. Kute, N. S. 

Kanawade, D. G and Dhonde, S. R. 2001. 

Genetic analysis in chickpea (Cicer arietinum 

L.). Legume Research. 24:3, 159-163. 

Gupta, S. K. Kaur Ajinder and Sandu, J. S. 2007. 

Combining ability in desi chickpea. Indian 

Journal of Pulses Research. 20(1):22-24. 

83



GENETIC DIVERGENCE IN BRINJAL (Solanum melongena L.) 

BALAJI LOKESH, P.SURYANARAYANA REDDY, R.V.S.K.REDDY and N.SIVARAJ 

Vegetable Research Station, A.R.I, Rajendranagar, Hyderabad-500030 


The study was conducted at Vegetable 

Research Station, Agricultural Research Institute, 

Rajendranagar, Hyderabad,during rabi season of 

2008-09. Sixty genotypes of Brinjal collected from 

various agro-climatic regions of India by N.B.P.G.R 

Regional station, Hyderabad were evaluated in a 

Randomized Block Design with two replications for 

fourteen quantitative characters. The mean data were 

analyzed following standard statistical techniques 

with the objective of studying the nature and 

magnitude of genetic diversity available in the 

germplasm. Genetic diversity is an important factor 

for any heritable improvement. Knowledge of genetic 

diversity is useful for selecting desirable genotypes 

from a germplasm for the successful breeding 

programme. The genetic divergence between 

genotypes was estimated using Mahalanobis D 2 

statistic (1936). 

In the present investigation, The D 2 value 

was used for the final grouping of the genotypes into 

eight distinct clusters as presented in Table 1. Cluster 

V was the largest cluster consisting of 15 genotypes 

while cluster VIII consisted of single genotype i.e, 

MR/04-26. The mean inter and intra cluster D and D 2 

values (Table 2) suggest that the genotypes within a 

cluster are less divergent than those of different 

clusters. The intra cluster and inter cluster D 2 values 

ranged from 714.92 to 2452.22 and 2339.92 to 

35995.80 respectively. Lowest inter cluster D 2 value 

was recorded between cluster I and II (2339.92) 

indicating close relationship and similarity for most 

of the characters of the genotypes. Highest inter 

cluster D 2 value was recorded between clusters III 

and VIII (35995.80) indicating wider genetic diversity 

among genotypes in these groups. 

The percentage contribution of each 

character towards divergence in Brinjal is presented 

in Table 3.Highest contribution towards divergence 

was put forth by average fruit weight (44.12%) 

followed by plant spread(43.62%), average fruit length 

(4.52%), number of branches per plant (2.71%), 

number of flower clusters per plant (2.03%) and 

average fruit diameter (1.41%) respectively. This 

suggest that in order to select genotypes for 

hybridization, the material should be screened for 

important traits like average fruit weight, plant 

spread, average fruit length, number of branches per 

plant, number of flower clusters per plant and average 

fruit diameter. Similar results were reported by Satesh 

Kumar et al. (2007). 

The mean performance of genotypes of 

clusters is presented in the Table 4. In calculation of 

cluster means, the superiority of a particular genotype 

with respect to a given character gets diluted by other 

related genotypes that are grouped in the same 

cluster which are inferior or intermediary for that 

character in question. Hence, apart from selecting 

genotypes from the clusters which have high intercluster 

distance for hybridization, it is also desirable 

to have selection of parents based on extent of 

genetic divergence with respect to a particular 

character of interest. On the basis of the mean 

performance of the characters in each cluster, the 

following genotypes were identified as superior for 

further genetic studies. The genotypes IC-111431 and 

IC-203593 were regarded as superior for number of 

flower clusters per plant. MR/04-26 was superior for 

days to 50% flowering, average fruit weight, shoot 

and fruit borer incidence on fruit and fruit yield per 

plant.IC-111352 and IC-111428 were regarded as 

superior for number of fruits per cluster.IC-13601 and 

PSR-11883 were regarded as superior for number of 

fruits per plant. Similar genetic divergence studies 

on Brinjal in India have been carried out by many 

researchers (Bansal and Mehta 2007, Sherly and 

Shanthi 2007, Nandan Mehta and Mayuri Sahu 2009). 

email: balajilokesh4@gmail.com 

84

LOKESH et al 

Table 1. Clustering pattern of 60 germplasm accessions of Brinjal on the basis of Mahalanobis D 2 

statistics 

Cluster 

No of 

genotypes 

Genotypes 

I 5 IC-089876-B,IC-111384,IC-111431,IC-111468,IC-203593 

II 11 IC-104086,IC-345309,IC-89910,PSR-11836,IC-13637, 

IC-111461-B,IC-111308,AR04-131,IC-111317, 

IC-345255,IC-135056 

III 5 IC-245335,DBT/OR-37,MR/04-02,PSR 11773,MR/04-81 

IV 11 IC-13601,IC-135920,IC-90930,IC-256208,IC-137751, 

PSR-11883,IC-111086,IC-136280,IC-127024,AR/04-132,IC-111071 

V 15 IC-111352,IC-111356,IC-383119,PSR-11891,IC-99649, 

IC-256150,IC-90767,IC-111444,IC-111074,IC-112851, 

IC-111428,IC-089905,IC-112755,MR/04-94,IC-136278 

VI 8 IC-136006,IC-136245,IC-135934,IC-136088, 

IC-104086,AR/04-145,MR/04-88,IC-90087 

VII 4 IC-135955,IC-74204,AR/04-477,IC-11404 

VIII 1 MR/04-26 

Table 2. Average intra and inter cluster D 2 and D values for eight clusters in 60 germplasm accessions 

of Brinjal 

Cluster I II III IV V VI VII VIII 

I 714.92 

2339.92 

6693.23 

6998.93 

3349.35 

8799.52 

4568.94 

32737.66 

(26.73) 

(48.37) 

(81.81) 

(83.65) 

(57.87) 

(93.80) 

(67.59) 

(180.93) 

II 1414.06 

3047.26 

5279.60 

3970.72 

10954.37 

8873.22 

31216.35 

(37.60) 

(55.20) 

(72.66) 

(63.01) 

(104.66) 

(94.19) 

(176.68) 

III 2452.22 

7563.46 

8260.76 

17611.32 

16941.25 

35995.80 

(49.51) 

(86.96) 

(90.88) 

(132.70) 

(130.15) 

(189.72) 

IV 1937.25 

3064.44 

5211.95 

8650.18 

14041.89 

(44.01) 

(55.35) 

(72.19) 

(93.00) 

(118.49) 

V 1701.21 

3914.04 

3986.40 

18843.24 

(41.24) 

(62.56) 

(63.13) 

(137.27) 

VI 1451.12 

(38.09) 

3899.03 

(62.44) 

10777.12 

(103.81) 

VII 1299.78 

(36.05) 

23498.27 

(153.29) 

VIII 0.00 

(0.00) 

The figures in the parenthesis are D values 

85

GENETIC DIVERGENCE IN BRINJAL 

Table 3. Percent contribution of characters towards diversity in Brinjal germplasm 

S.No Character Percent 

contribution 

1 Plant height (cm) 0.23 

2 Plant spread(cm 2 ) 43.62 

3 Number of branches per plant 2.71 

4 Days to 50% flowering 0.00 

5 Number of flower clusters per plant 2.03 

6 Number of flowers per cluster 0.00 

7 Number of fruits per cluster 0.00 

8 Fruit length (cm) 4.52 

9 Fruit diameter (cm) 1.41 

10 Fruit weight (g) 44.12 

11 Number of fruits per plant 0.23 

12 Shoot and fruit borer incidence on shoot (%) 0.00 

13 Shoot and fruit borer incidence on fruit (%) 0.28 

14 Yield/ plant (kg) 0.85 

REFERENCES 

Bansal, S and Mehta, A. K. 2007. Genetic divergence 

in brinjal (Solanum melongena L.) Haryana 

Journal of Horticultural Sciences 36(3/4): 319- 

320. 

Mahalanobis, P. C. 1936. On the generalized distance 

in statistics. Proceedings of National Institute 

of Sciences, India 12: 49- 55. 

Nandan Mehta and Mayuri Sahu. 2009. Genetic 

divergence in brinjal (Solanum melongena L.) 

International Journal of Plant Sciences, 

Muzaffarnagar 4(1): 123-124. 

Satesh Kumar, Singh, A. K, Sharma, J. P and Neerja 

Sharma. 2007. Genotype clustering in brinjal 

(Solanum melongena L.) using D 2 statistic. 

Haryana Journal of Horticultural Sciences 

36(1/2): 95-96. 

Sherly, J and Shanthi, A. 2007. Diversity studies in 

brinjal. Haryana Journal of Horticultural 

Sciences 36(1/2): 162-163. 

86

LOKESH et al 

Table 4. Mean values of clusters for fourteen characters in 60 brinjal germplasm accessions 

87



RELATIONSHIP BETWEEN PROFILE OF BENEFICIARY FARMERS AND THE 

SOCIO-ECONOMIC IMPACT OF IRRIGATED AGRICULTURE MODERNIZATION 

AND WATER BODIES RESTORATION AND MANAGEMENT (IAMWARM) 

PROJECT IN PUDUKKOTTAI DISTRICT 

G. ABIRAMI, B.VIJAYABHINANDANA and T. GOPI KRISHNA 

Department of Agricultural Extension, Agricultural College, 

Acharya N.G Ranga Agricultural University, Bapatla- 522 101 


The project Irrigated Agriculture 

Modernization and Water Bodies Restoration and 

Management (IAMWARM) was introduced in 2007 

and funded by World Bank. Its objective was to 

improve irrigation service delivery including 

adaptation of modern water-saving irrigation 

technologies and ultimately to ensure food security 

and improved farm incomes. Keeping this in view, 

present study was proposed to study the socioeconomic 

impact of IAMWARM project on beneficiary 

farmers in Pudukkottai district of Tamil Nadu in the 

year 2012. The implications of the study would be 

useful to the project officials, implementing 

authorities, funding agencies concerned, for 

extending project benefits to the farming community. 

A study was undertaken purposively in 

Pudukkottai district of Tamil Nadu as this project was 

first implemented in Pudukkottai district under first 

phase sub-basin of the project during the year 2007. 

Thus, it gave sufficient time interval to study the 

impact. Four taluks were selected randomly and three 

villages from each taluk were selected randomly. Ten 

beneficiaries from each village were selected randomly 

using simple random sampling procedure, thus 

making a total sample of 120 beneficiary farmers. 

Ex-post facto research design was followed. Data 

was collected through interview schedule from the 

beneficiary farmers of the project covering all aspects 

of the socio-economic impact. To convert the data 

into meaningful findings some statistical tools were 

used. viz. a) Frequency and Percentage analysis b) 

Correlation analysis c) Multiple regression analysis 

and d) class interval. 

a) Socio-economic impact of the project 

Socio-economic impact of the project in SRI 

technique was studied with eleven variables namely, 

knowledge, adoption, income, asset acquisition, yield, 

water use efficiency, participation in the project 

activities, labour use, social participation, cost of 

cultivation, and empowerment. By adding and 

averaging the scores of all the items, the individual 

score for socio-economic impact was worked out. It 

was used to categorize the respondents into three 

groups based on the class interval (exclusive) method 

as low, medium and high level of socio-economic 

impact. 

Table 1. Distribution of respondents according to socio-economic impact 

S.No 

Category 

Beneficiary Farmers 

N=120 

Frequency 

Percentage 

1. Low (49-62) 30 25.00 

2. Medium (63-76) 56 46.67 

3. High (77-90) 34 28.33 

** - significant at 0.01 level of probability 

email: abarangi@gmail.com 

88

ABIRAMI et al 

Socio-economic Impact: A cursory look at 

the Table 1 indicates that 46.67 per cent of beneficiary 

farmers had medium level of socio-economic impact, 

followed by high (28.33%) and low level of socioeconomic 

impact (25.00%). The result was the 

cumulative effect of all the factors contributed to the 

socio-economic impact. The reason for high level of 

socio-economic impact might be particularly due to 

majority of the farmers obtained fine knowledge about 

SRI and adopted SRI technique fairly in their field. 

As a result they received more income and asset 

acquisition. Medium level of socio-economic impact 

might be due to partial adoption of technology and 

inefficient management of labour. That results in more 

cost of cultivation. Low level of socio-economic 

impact might be due to poor adoption & SRI 

technology. 

b) Relationship between profile of beneficiary 

farmers and the socio-economic impact 

An attempt has been made to find out the 

association between independent variables and 

dependent variables through correlation coefficient 

(r) values. The results are presented in Table 2. 

Table 2. Correlation coefficient between profile of beneficiary farmers and the socio-economic impact 

N= 120 

S. No Independent Variables ‘r’ values 

1. Age 

2. Education 

3. Land Holding 

4. Farming Experience 

5. Information sources utilization 

6. Training Received 

7. Economic Motivation 

8. Scientific Orientation 

9. Innovativeness 

10. Risk Orientation 

-0.2119 NS 

0.4014** 

0.3870** 

0.3537** 

0.3793** 

0.4815** 

0.5241** 

0.6113** 

0.5927** 

0.6084** 

** Significant at 0.01 level of probability NS = Non Significant 

The results presented in the Table 2 clearly 

indicate that almost all computed ‘r’ values of 

education, land holding, farming experience, 

information sources utilization, training received, 

economic motivation, scientific orientation, 

innovativeness and risk orientation with socioeconomic 

impact were found positively significant 

relationship at 0.01 level of probability. Whereas, age 

with socio-economic impact had non-significant and 

negative relationship. 

From this study it could be concluded that 

higher the education, higher the land holding, higher 

the experience in farming, higher the information 

sources utilization, higher the training received, 

higher the economic motivation, higher the scientific 

orientation, higher the innovativeness and higher the 

risk orientation, the higher would be the socioeconomic 

impact. 

The probable reason for age, not influencing 

the socio-economic impact can be explained that 

89

RELATIONSHIP BETWEEN PROFILE OF BENEFICIARY FARMERS & IMPACT 

adoption of innovation (in this context adoption of 

SRI technique) in Indian agriculture does not differ 

from non-adoption with respect to age, it depends on 

how worthy the innovation is to a farmer for efficient 

crop production. This trend was also noticed by 

Mohammad et al (2009). 

The reason for positive and significant 

correlation of education with socio-economic impact 

might be due to the fact that, the education widens 

horizons of the individual to get information from 

various sources. This seems to be inter-related with 

farmers to bring changes in their personal, 

psychological orientation, to adopt new ideas, 

practices and technologies and motivate the farmers 

towards achieving high socio-economic impact. This 

result was in agreement with the results of Manoj 

(2008) and Suresh and Rameshbabu (2008). 

There was positive and significant 

relationship between land holding and socio-economic 

impact. This might be due to the fact that land holding 

provides the economic base for the farmers to 

practice new agricultural technologies. Land holding 

also provides regulated impetus to make optimum 

utilization of resources on farm for achieving 

maximum profits. Similar results were reported by 

Rameshbabu (2002) and Reddy et al. (2007). 

It was found that farming experience had 

positive and significant relationship with socioeconomic 

impact. This might be due to the fact that 

experience is the best teacher, farmer having more 

experience in farming, irrespective of age would know 

the difficulties and problems in farming better than 

less experienced and who seek for new alternative 

farm practices and adopt new production technologies. 

This result was in conformity with the results of 

Thyagarajan (2004) and Reddy et al. (2007). 

Positive and significant relationship was 

noticed between information sources utilization and 

socio-economic impact. This might be due to the fact 

that different information sources utilization updated 

the farmers with new production technologies and 

motivate them to adopt it to improve their profits. 

This finding was in tune with the results of Reddy et 

al. (2007) and Mohammad et al. (2009). 

From the Table 2. it was clear that there was 

positive and significant relationship between training 

received and socio-economic impact. This might be 

due to the fact that training is one of the means by 

which desired changes in knowledge and skills could 

be attained. An individual who receives training 

become more knowledgeable, skilful and develop 

rationale and adopt improved farming practices led 

to have more socio-economic impact. This might be 

the reason for above result. The result was in 

agreement with the results of Basawarajaiah (2001). 

Economic motivation was found to be positively 

and significantly associated with the socio-economic 

impact. The reason could be that the farmers with 

more economic motivation would be oriented towards 

more information sources utilization; risk bearing that 

might help them to adopt new production technologies. 

This finding was in line with the findings of Manoj 

(2008) and Suresh and Rameshbabu (2008). 

The results furnished in the Table 2 indicated 

that there was positive and significant relationship 

between scientific orientation and socio-economic 

impact. It might be due to the reason that the farmers 

having more scientific orientation would gather more 

information from authentic sources like Krishi Vigyan 

Kandra, TNAU scientists, etc., and think rationally 

before applying into the field conditions, get the higher 

production and profits. Similar results were reported 

by Manoj (2008) and Mohammad et al. (2009). 

There was positive and significant relationship 

between innovativeness and socio-economic impact 

(Table 2). This might be due to the fact that farmers 

who are relatively earlier in adopting new agricultural 

innovations would orient towards more risk taking, 

more scientific orientation, maintain higher social 

status. Their earliness to adopt innovations would 

have resulted in higher socio-economic impact in 

terms of increasing higher yields and income. This 

result was in conformity with the results of Damodaran 

(2007) and Manoj (2008). 

The correlation between risk orientation and 

socio-economic impact was positive and significant 

(Table 2). It could be inferred from the finding that 

higher the risk orientation, the higher would be the 

90

ABIRAMI et al 

socio-economic impact. This might be due to the fact 

that higher risk oriented farmers adopt the innovations 

and get more yield and higher income. Hence, such 

type of relation existed in the study. This finding was 

in line with the findings of Chandrasekhar et al. (2005) 

and Manoj(2008). 

c) Multiple Linear Regression of selected 

independent variables with socio-economic 

impact. 

An attempt was made to find out the amount of 

contribution made by the independent variables in 

explaining the variation in the dependent variable 

through multiple linear regression. The results are 

presented in Table 3. 

Table 3. Multiple regression analysis of Profile of beneficiary farmers and the socio-economic impact 

S. No Variables 

Regression 

coefficient (B) 

Standard error 

‘t’ value 

1. Age 

-6.3303 0.7039 -8.9927** 

2. Education 

0.7092 0.3255 2.1784NS 

3. Land Holding 

0.4241 0.4370 0.9704NS 

4. Farming Experience 

4.6575 0.6232 7.4733** 

5. Information sources utilization -0.4021 0.0695 -5.7790** 

6. Training Received 

3.3325 0.5538 6.0164** 

7. Economic Motivation 

1.4766 0.2322 6.3584** 

8. Scientific Orientation 

0.3394 0.1763 1.9248NS 

9. Innovativeness 

0.7704 0.1235 6.2369** 

10. Risk Orientation 

1.7744 0.2070 8.5691** 

R 2 = 0.861; NS = Non Significant; 

** Significant at 0.01 level of probability 

The Ten independent variables with the 

socio-economic impact of the project taken on 

Multiple Linear Regression Analysis gave the R 2 (Coefficient 

of multiple determination) value of 0.861. It 

indicates that all the selected independent variables 

put together contributed 86.10 per cent of the total 

variation in the socio-economic impact of the project 

by the beneficiary farmers, leaving the rest to 

extraneous factors. The independent variables viz., 

farming experience, training received, economic 

motivation, innovativeness and risk orientation 

contributed significantly to the socio-economic impact 

of the project. The variable scientific orientation was 

not having significant value, but the value is near to 

significant t –value (1.980272). So, it also could be 

considered as significant 

REFERENCES 

Baswarajaiah, V.2001. Impact of Edira Watershed 

Development Programme on farm families in 

Mahaboobnagar District of Andhra Pradesh. 

M. Sc. (Ag.) Thesis submitted to Acharya N 

G Ranga Agricultural University, Hyderabad, 

India. 

91

RELATIONSHIP BETWEEN PROFILE OF BENEFICIARY FARMERS & IMPACT 

Chandrasekhar, V., Gangadharappa, N.R and 

Suresha, S.V. 2005. Knowledge level farmers 

about selected technological interventions in 

TAR-IVLP. Mysore Journal of Agricultural 

Sciences. 39 (3): 410-414. 

Damodaran, C. 2007. Irrigation management and 

socio-economic changes among Cauvery old 

delta farmers. M.Sc. (Ag.) Thesis submitted 

to Acharya N G Ranga Agricultural University, 

Hyderabad, India. 

Manoj, A. 2008. Impact of Krishi Vigyan Kendra on 

farmers Srikakulam district of Andhra 

Pradesh. M. Sc. (Ag.) Thesis submitted to 

Acharya N G Ranga Agricultural University, 

Hyderabad, India. 

Ca Mohammad Ajaz-ul-Islam, Masoodi, N.A., 

Masoodi, T.H and Gangoo, S.A. 2009. 

Awareness and participation of beneficiaries 

in social forestry programme in Baramulla 

district of Kasmir valley. Indian Journal of 

Social Research. 50(4): 353-364. 

Rameshbabu, C. 2002. Effectiveness of Indo-Dutch 

Operational Research project on drainage and 

water management for salinity control in 

Prakasam district of A.P. M. Sc. (Ag.) Thesis 

submitted to Acharya N G Ranga Agricultural 

University, Hyderabad, India. 

Reddy, P.T.S., Prabhakar, K and Gidda Reddy, P. 

2007. Analysis of influence of selected 

independent variables on knowledge of rice 

farmers on Eco-friendly technologies. Journal 

of Research ANGRAU. 35 (2): 31-37. 

Suresh, T.V and Ramesh Babu, C.H. 2008. Extent 

of participation of farmers in Sujala 

Kalinganahalli Halla Watershed Project, 

Andhra Agricultural journal. 55(3): 405-407. 

Thyagarajan, S. 2004. Rice production technology – 

adoption and constraints. Indian Journal of 

Extension Education. 40 (3&4): 44-47. 

92



CONSTRUCTION OF SELECTION INDICES FOR F 2 

POPULATION 

DERIVED FROM CROSSES BETWEEN 

GRAIN SORGHUM × SWEET SORGHUM [Sorghum bicolor (L.) Moench] 



Department of Genetics and Plant Breeding 

Acharya N.G. Ranga Agricultural University, Hyderabad – 500 030 


The selection indices by discriminant 

function analysis were constructed based on the data 

of a population of 800 F 2 

plants developed by 

crossing three grain sorghum genotypes viz., 27 B, 

ICSB 38 and 296 B as a female parent and four sweet 

sorghum genotypes viz., SSV 84, SSV 74, URJA 

and NSSV 13 as a male parent. Majority of selection 

indices were found to be more efficient than straight 

selection based on sugar yield alone. The selection 

index consisting of six character combination viz., 

sugar yield, total biomass, fresh stalk yield, brix per 

cent, juice yield and total soluble sugars was more 

effective with higher relative efficiency. While, 

selection based on five characters combinations viz., 

sugar yield, total biomass, fresh stalk yield, brix per 

cent and juice yield as well as four character 

combination viz., total biomass, fresh stalk yield, brix 

per cent and juice yield were also equally effective 

in selection of plants for maximum sugar yield. 

However, selection index comprising six and five 

character combinations are of little importance in 

selection process as it includes derived parameters 

such as sugar yield and total soluble sugars. In this 

regard it is suggested to go for four character 

combination which also manifested maximum relative 

efficiency coupled with higher genetic advance. 

The practical or economic value of a plant is 

affected by several traits. Since, majority of the 

economic traits are polygenically inherited and their 

expression is subjected to varying degrees of 

fluctuations due to environmental factors, eventually 

direct selection may not be useful for such characters. 

Efficiency of selection under such circumstances can 

sometimes be improved by taking into consideration 

simultaneously the phenotypic values of a number 

of plant attributes which are correlated with the 

genotypic values (high heritability) of the characters 

under consideration. 

The material for the present study comprised 

of 800 F 2 

population of sweet sorghum crosses 

derived from parents having low and high sugar 

content developed at Directorate of Sorghum 

Research, Rajendranagar, Hyderabad. These 

populations were developed by crossing the 

contrasting parents (27 B with SSV 84, ICSB 38 with 

SSV 74, 296 B with URJA and 27 B with NSSV 13) 

through hand emasculation and pollination during 

kharif 2010 and the F 1 

plants of the two crosses were 

grown during rabi 2010 - 11 and selfed to produce the 

F 2 

seeds, which were evaluated during summer 2012. 

The technique of discriminant function 

developed by Fisher (1936) was adopted to know the 

true genotypic worth of yield and its components and 

to have computational formulae for construction of 

selection indices which when applied to select plants 

can bring about effective improvement in yield 

compared to straight selection for yield. Smith (1936) 

has illustrated the use of discriminant function in plant 

selection. 

Formulation of selection indices through 

discriminant function analysis Selection indices 

were formulated in F 2 

populations of sweet sorghum 

considering sugar yield and its five component 

characters which had high correlation with sugar yield. 

Among six characters, sugar yield (X 1 

) was 

considered as dependent character, while other 

characters viz., total biomass (X 2 

), fresh stalk yield 

(X 3 

), brix per cent (X 4 

), juice yield (X 5 

) and total soluble 

sugars (X 6 

) were considered as independent 

variables. In order to select plants with high sugar 

yield, discriminant functions were computed with 

email: vemanraddi@gmail.com 

93


POPULATION 

different sets of characters and the efficiency of each 

index was compared with direct selection for sugar 

yield and other combination of characters (Table 1). 

A maximum of five component characters 

which exhibited high significant and positive 

correlation with sugar yield were used in F 2 

populations 

for construction of different selection indices. The 

expected genetic advance was computed for each 

of the indices at five per cent selection intensity. 

The relative efficiency of all the indices was computed 

considering the relative efficiency of sugar yield as 

100 per cent. The estimated values of genetic 

advance and relative efficiency for each combination 

of character in F 2 

population have been tabulated in 

Table 1 and briefly discussed below. 

Sixty three different selection indices were 

formulated based on various combinations of six 

characters considered for construction of selection 

indices. Among these, higher relative efficiency of 

2756.36 coupled with high genetic advance (90.42) 

was exhibited by combination involving all the six 

traits (including sugar yield) of X 1 

+ X 2 

+ X 3 

+ X 4 

+ X 5 

+ X 6 

, followed by the combination of five traits viz., 

X 1 

+ X 2 

+ X 3 

+ X 4 

+ X 5 

which recorded relative efficiency 

of 2734.65 with high genetic advance of 89.70 

compared to other combinations. 

Among single character, X 2 

was highly 

efficient with relative efficiency of 814.80 compared 

to the direct selection based on sugar yield (X 1 

) whose 

relative efficiency was taken as 100. Whereas, among 

two character combinations, maximum relative 

efficiency of 1661.36 was observed for the 

combination of X 2 

+ X 3 

traits with high genetic 

advance of 54.50, followed by X 2 

+ X 5 

traits with a 

relative efficiency of 1287.74 and genetic advance 

of 42.24. However, in case of three character 

combinations, the combination involving X 2 

+ X 3 

+ X 5 

exhibited higher relative efficiency of 2090.98 coupled 

with high genetic advance of 68.59. 

Among four character combinations, X 1 

+ X 2 

+ X 3 

+ X 5 

followed by X 2 + X 3 + X 4 + X 5 and X 2 + X 3 + X 5 

+ X 6 

exhibited high relative efficiencies of 2702.34, 

2455.56 and 2451.75 coupled with genetic advance 

of 88.64, 80.55 and 80.42, respectively. 

Since, sugar yield and total soluble sugars 

are estimated or derived characters, more emphasis 

during selection should be given on the directly 

measurable characters to get the accurate results. 

Hence, the combinations without sugar yield and total 

soluble sugars are considered for indirect selection 

for sugar yield. Among them, X 2 

+ X 3 

+ X 4 

+ X 5 

combination exhibited maximum relative efficiency 

of 2455.56 per cent with genetic advance of 80.55. 

Path coefficient analysis revealed the 

intricacies of yield components while discriminant 

function is useful in knowing the extent of 

improvement that can be effected in yield by selecting 

plants based on different combination of component 

characters. Smith (1936) opined that, selection index 

is the basis in considering the correlated characters 

for higher efficiency in selection for yield. When yield 

is associated with other characters, indirect selection 

through such traits is sometimes likely to be better 

than straight selection for yield. But, when the number 

of characters associated with yield is large, it 

becomes difficult to select simultaneously for all 

these characters. Under such circumstances, 

selection indices formulated by involving different 

combinations of characters with appropriate 

weightage to each character help in making the 

selection procedure easy. 

In the present study, selection index 

involving six character combination viz., sugar yield, 

total biomass, fresh stalk yield, brix per cent, juice 

yield and total soluble sugars was more effective with 

higher relative efficiency. While, selection based on 

five characters combinations viz., sugar yield, total 

biomass, fresh stalk yield, brix per cent and juice 

yield as well as four character combination viz., total 

biomass, fresh stalk yield, brix per cent and juice 

yield were also equally effective in selection of plants 

for maximum sugar yield. Similar results of increased 

efficiency by inclusion of yield as one of the 

component in formulating selection indices were 

reported by Mahadevappa and Ponnaiya (1967) in 

pearlmillet, Paroda and Joshi (1970) in wheat, Agrawal 

et al. (1978) in dwarf rice, Rahangdale et al. (1987) in 

upland rice, Mannur et al. (1991) in soybean, Mathur 

and Gupta (1992) in niger, Singh and Khan (1998) 

and Nahar et al. (2002) in sugarcane. 

When indirect selection scheme excluding 

sugar yield in formulating index is to be followed, the 

index involving combination of four characters viz., 

94

VEMANNA et al 

Table 1. Discriminant functions, their genetic advance and relative efficiency over straight selection 

for sugar yield in F 2 

generation of the sweet sorghum crosses 

Sl. No. Discriminant Function GA RE (%) 

1 Y = 0.23X 1 3.28 100.00 

2 Y = 0.12X 2 26.73 814.80 

3 Y = 0.14X 3 23.77 724.67 

4 Y = 0.36X 4 0.95 28.92 

5 Y = 0.17X 5 13.67 416.72 

6 Y = 0.36X 6 0.83 25.28 

7 Y = 2.31X 1 + 0.01X 2 33.97 1035.68 

8 Y = 1.42X 1 + 0.05X 3 28.04 854.85 

9 Y = 0.06X 1 + 1.62X 4 4.92 150.08 

10 Y = 6.44X 1 – 0.94X 5 22.82 695.72 

11 Y = 0.06X 1 + 1.80X 6 4.80 146.39 

12 Y = 0.65X 3 – 0.26X 2 54.50 1661.36 

13 Y = 0.07X 2 + 8.45X 4 33.29 1015.02 

14 Y = 0.57X 5 – 0.02X 2 42.24 1287.74 

15 Y = 0.07X 2 + 9.59X 6 33.18 1011.37 

16 Y = 0.10X 3 + 5.75X 4 27.49 838.08 

17 Y = 0.05X 3 + 0.36X 5 36.67 1117.85 

18 Y = 0.10X 3 + 6.50X 6 27.39 834.97 

19 Y = 6.49X 4 + 0.04X 5 19.27 587.57 

20 Y = 0.47X 4 + 0.25X 6 1.78 54.23 

21 Y = 0.04X 5 + 7.36X 6 19.15 583.66 

22 Y = 3.15X 1 – 0.32X 2 + 0.52X 3 61.51 1875.03 

23 Y = 0.79X 1 + 0.04X 2 + 8.07X 4 37.17 1133.16 

24 Y = 16.09X 1 + 0.16X 2 – 2.71X 5 56.51 1722.60 

25 Y = 0.79X 1 + 0.04X 2 + 9.15X 6 37.05 1129.41 

26 Y = 0.02X 1 + 0.10X 3 + 7.16X 4 30.97 944.15 

27 Y = 15.19X 1 + 0.29X 3 – 2.84X 5 51.37 1566.14 

28 Y = 0.02X 1 + 0.10X 3 + 8.12X 6 30.86 940.82 

29 Y = 4.41X 1 + 3.81X 4 – 0.65X 5 24.30 740.65 

30 Y = 0.06X 1 + 1.36X 4 + 0.65X 6 5.75 175.32 

31 Y = 4.40X 1 – 0.65X 5 + 4.29X 6 24.16 736.68 

95


POPULATION 

Sl. No. Discriminant Function GA RE (%) 

34 Y = 0.61X 3 – 0.31X 2 + 15.62X 6 63.10 1923.78 

35 Y = 0.05X 2 + 14.19X 4 + 0.10X 5 50.80 1548.63 

36 Y = 0.07X 2 + 7.56X 4 + 1.41X 6 33.99 1036.31 

37 Y = 0.05X 2 + 0.11X 5 + 16.13X 6 50.66 1544.42 

38 Y = 0.15X 3 + 13.04X 4 – 0.09X 5 44.76 1364.64 

39 Y = 0.10X 3 + 5.14X 4 + 1.09X 6 28.13 857.65 

40 Y = 0.15X 3 – 0.09X 5 + 14.83X 6 44.64 1360.77 

41 Y = 4.70X 4 + 0.04X 5 + 2.43X 6 20.10 612.67 

42 Y = 0.13X 1 – 0.32X 2 + 0.62X 3 + 14.89X 4 66.73 2034.16 

43 Y = 25.21X 1 – 0.22X 2 + 0.81X 3 – 4.64X 5 88.64 2702.34 

44 Y = 0.14X 1 – 0.32X 2 + 0.62X 3 + 16.95X 6 66.61 2030.74 

45 Y = 13.16X 1 + 0.15X 2 + 4.80X 4 – 2.24X 5 57.71 1759.40 

46 Y = 0.82X 1 + 0.04X 2 + 7.36X 4 + 1.11X 6 37.91 1155.67 

47 Y = 13.19X 1 + 0.15X 2 – 2.25X 5 + 5.35X 6 57.59 1755.58 

48 Y = 13.73X 1 + 0.28X 3 + 3.26X 4 – 2.55X 5 52.37 1596.68 

49 Y = 0.06X 1 + 0.10X 3 + 6.05X 4 + 1.57X 6 31.65 964.76 

50 Y = 13.76X 1 + 0.28X 3 – 2.55X 5 + 3.61X 6 52.26 1593.20 

51 Y = 4.57X 1 + 3.75X 4 – 0.68X 5 + 0.26X 6 25.16 766.93 

52 Y = 0.74X 3 – 0.35X 2 + 21.70X 4 – 0.17X 5 80.55 2455.56 

53 Y = 0.61X 3 – 0.31X 2 + 10.07X 4 + 4.58X 6 63.86 1946.72 

54 Y = 0.74X 3 – 0.35X 2 – 0.17X 5 + 24.72X 6 80.42 2451.75 

55 Y = 0.05X 2 + 11.34X 4 + 0.11X 5 + 3.61X 6 51.56 1571.89 

56 Y = 0.14X 3 + 10.01X 4 – 0.09X 5 + 3.81X 6 45.48 1386.50 

57 

58 

59 

60 

61 

Y = 21.88X 1 – 0.23X 2 + 0.81X 3 + 5.40X 4 – 

4.12X 5 

Y = 0.17X 1 – 0.32X 2 + 0.62X 3 + 10.78X 4 + 

5.02X 6 

Y = 21.93X 1 – 0.23X 2 + 0.81X 3 – 4.12X 5 + 

6.02X 6 

Y = 13.31X 1 + 0.15X 2 + 8.60X 4 – 2.27X 5 – 

4.17X 6 

Y = 13.89X 1 + 0.28X 3 + 6.57X 4 – 2.57X 5 – 

3.61X 6 

89.70 2734.65 

67.39 2054.36 

89.59 2731.24 

58.50 1783.51 

53.12 1619.52 

GA = Genetic advance; RE = Relative efficiency 

96

VEMANNA et al 

total biomass, fresh stalk yield, brix per cent and 

juice yield which exhibited maximum relative 

efficiency, same could be considered for selection 

schemes. Bhat and Shariff (1994) in finger millet, 

Patil et al. (1997) in sunflower and Khulbe and Pant 

(1999) in mustard obtained similar results of 

increased efficiency through indirect selection using 

different combination of characters excluding yield 

in selection index. Hence, it can be inferred that the 

maximum gain using indirect selection schemes 

could be achieved using highly correlated characters 

like total biomass, fresh stalk yield, brix per cent and 

juice yield, which is further confirmed by path coefficient 

as well as discriminant function analysis. 

REFERENCES 

Agrawal, R. K., Lal, I. P and Richharia, A. K., 1978. 

Note on selection indices and path coefficients 

in semi dwarf rice varieties. Indian Journal of 

Agricultural Science. 48: 58-60. 

Bhat, B. V and Shariff, R. A., 1994. Selection criteria 

in Finger millet (Eleusine coracana Gaertn.). 

Mysore Journal of Agricultural Sciences. 

28: 5-7. 

Fisher, R. A., 1936. The use of multiple 

measurements to taxonomic problems. Annals 

of Eugenics. 7: 87-104. 

Khulbe, R. K and Pant, D. P., 1999. Selection indices 

in Indian mustard. [Brassica juncea (L.) Czern 

& Coss]. Crop Improvement. 26: 109-111. 

Mahadevappa, M and Ponnaiya, B. W. X., 1967. 

Discriminant functions in the selection of pearl 

millet (Pennisetum typhoids Stapf and Hubb.) 

population for grain yield. The Madras 

Agricultural Journal. 54: 211-222. 

Mannur, D. M., Salimath, P. M., Patil, S. S and 

Parameshwarappa, R., 1991. Genetic studies 

in interspecific crosses of soybean Glycine 

max (L.) Merill × Glycine formosa. Indian 

Journal of Genetics and Plant Breeding. 51: 

471-475. 

Mathur, R. K and Gupta, S. C., 1992. Discriminant 

function analysis in Niger (Guizotia abyssinica 

Cass.). Crop Research. 5: 164-165. 

Nahar, S. M. N., Khaleque, M. A and Miah, M. A., 

2002. Correlation, path co-efficient and 

construction of selection index in sugarcane. 

Pakistan Sugar Journal. 17: 2-10. 

Paroda, R. S and Joshi, A. B., 1970. Correlations, 

path co-efficients and the implication of 

discriminate function for selection in wheat 

(Triticum aestivum). Heredity. 25: 383-392. 

Patil, B. R., Rudraaradhya, M and Basappa, H., 1997. 

Construction of selection indices for varietal 

selection in sunflower (Helianthus annuus L.). 

Journal of Oilseed Research. 14: 172-174. 

Rahangdale, S. L., Khoragade, P. W and Raut, S. 

K., 1987. Construction of selection indices for 

varietal selection in upland Rice. Journal of 

Maharashtra Agricultural Universities. 12: 223- 

224. 

Singh, S. P and Khan, A. Q., 1998. Selection indices 

for cane yield in sugarcane. Indian Journal of 

Genetics and Plant Breeding. 58: 353-357. 

Smith, H. F., 1936. A discriminant function for plant 

selection. Annals of Eugenics. 7: 240-250. 

97



EVALUATION OF PERFORMANCE OF DENDROBIUM ORCHID HYBRIDS 

B. GOPALA RAO, P.T.SRINIVAS and M.H.NAIK 

Department of Horticulture, Sri Venkateswara Agricultural College, 

Acharya N.G. Ranga Agricultural University , Tirupati- 517 502 


Dendrobium is one of the largest diverse 

genera of orchids, very popular among orchids 

throughout the world. In India, majority of commercial 

orchid farms are located in Tamil Nadu, Kerala, 

Karnataka and Agency areas of Andhra Pradesh. 

Dendrobium hybrids viz., Sonia-17, Emma White, 

New Wanee, Pampodour Blue Magic and Flame are 

bearing population in India. Increasing demand with 

insufficient supply of orchid flowers in international 

trade offer scope for making India a major exporter, 

having maximum genetic resources, varied climatic 

zones, availability of trained man power, lower cost 

of production as compared to other orchid growing 

countries. Very few studies are reported on the 

screening of orchids. However, the present 

investigation was carried out to evaluate Dendrobium 

hybrids viz., Sonia-17, Emma White, New Wanee, 

Pampodour, Blue Magic and Flame for export 

purpose. 

The study was conducted in the orchid farm 

Natural Synergies Limited, Nathanallur village, 

Kancheepuram district situated between 12 0 52’ N 

latitude and 79 0 51’ E longitude at an altitude of 102 

m MSL. Six hybrids of Sonia-17, Emma White, New 

Wanee, Pampodour, Blue Magic and Flame were 

screened for their performance grown under 75 per 

cent shade net. Growth parameters studied were plant 

height, number of shoots per plant, number of leaves 

per plant, number of spikes per plant, length of spike, 

number of florets per spike, length of floret pedicel, 

and longevity of spikes on plant and in the vase. 

Observations on vegetative growth parameters were 

recorded at 60, 120 and 180 days and floral characters 

at 130 and 195 days after planting. The experiment 

was laid out in Completely Randomized Block Design 

(CRD) with 4 replications and 6 treatments. 

Among the hybrids studied ‘Blue Magic’ 

produced maximum plant height (56.61 cm) and 

hybrid ‘Emma White’ produced minimum plant height 

(41.54 cm), while others showed intermediate heights. 

The hybrid ‘Flame’ had produced maximum number 

of leaves per plant (12.87) and hybrid ‘New Wanee’ 

recorded minimum number of leaves (6.44) per plant 

(Table 1). The hybrid ‘Flame’ showed distinguishable 

difference in the spike number, length of spike, and 

number of florets per spike from others (Table 2). 

The number of spikes recorded was maximum in the 

hybrid ‘Flame’ (3.68). The results showed that 

increased number of spikes had positive and 

significant relation with the leaves and shoots. The 

hybrid ‘Flame’ excelled other hybrids with a spike 

length of 57.96 cm, while hybrid ‘Pompadour’ recorded 

spike length of 48.39 cm followed by ‘Blue Magic’ 

(40.51 cm) and ‘New Wanee’ (37.86 cm), whereas 

‘Emma White’ and ‘Sonia 17’ recorded minimum spike 

length of 32.49 and 33.16 cm (Fig. 1A). Maximum 

number of florets per spike (15.58) was recorded in 

‘Flame’, which might be due to production of longest 

spikes. Whereas minimum number of florets per spike 

was recorded in ‘New Wanee’ (7.55) and ‘Sonia 17’ 

(7.60), maximum floret pedicel length was recorded 

in ‘Emma White’ and ‘Blue Magic’. The vase life study 

of different hybrids revealed that the cultivars ‘Sonia 

17’ (18.38 days) and ‘Flame’ (17.96 days) recorded 

longer vase life, whereas shorter vase life was 

observed in ‘Pampodour’ (6.45 days) in tap water 

(Table 2)(Fig. 1B). The variation observed among 

different hybrids in respect of different above 

parameters may be attributed to genetic differences 

in the hybrids studied. The above findings of the 

present investigation are in agreement with those of 

Betonio (1966) and Chandrappa (2003). 

Based on the above results, it appeared that 

Flame’s performance is better than others, though 

its vase life is comparatively less but almost equal 

to that of Sonia 17. Hence it is recommended to grow 

‘Flame’ for commercial and export purposes. 

email: gopal_hort@yahoo.co.in 

98

RAO et al 

Table 1. Plant height, number of leaves and shoots per plant of different Dendrobium hybrids (at 180 

days after planting) grown under shade net 

Hybrid Plant height (cm) No. of leaves/plant No. of shoots/plant 

Sonia 17 43.90 9.17 5.08 

Emma White 41.54 8.87 6.68 

New Wanee 43.52 6.44 7.55 

Pampodour 49.15 10.62 6.91 

Blue Magic 56.61 11.22 6.22 

Flame 52.85 12.87 7.92 

CD at 5% 2.01 0.23 0.35 

Table 2. Spike yield, quality and vase life (at 195 days) of different Dendrobium hybrids grown under 

shade net. 

Hybrid 

No. of spikes / 

plant 

No. of florets / 

spike 

Spike 

length (cm) 

Floret 

pedicel 

length (cm) 

Vase life in 

tap water 

(days) 

Sonia 17 2.96 7.60 33.16 3.75 18.38 

Emma White 2.46 11.76 32.49 4.07 13.84 

New Wanee 2.02 7.55 37.86 3.29 9.24 

Pampodour 2.09 13.45 48.39 3.68 6.45 

Blue Magic 3.28 10.23 40.51 3.80 14.88 

Flame 3.68 15.58 57.96 4.03 17.96 

CD at 5% 0.36 1.16 2.59 0.20 0.88 

99

EVALUATION OF PERFORMANCE OF DENDROBIUM ORCHID HYBRIDS 

Fig 1. Spike quality and vase life (in tap water) of different Dendrobium hybrids grown under shade 

net. 

REFERENCES 

Betonio, G.I. 1966. Germplasm collection and 

evaluation of different Anthurium cultivars. 

Journal of crop science. 20: 12. 

and flowering in Anthurium. Ph.D. Thesis 

submitted to University of Agricultural 

Sciences, Bangalore. 

Chandrappa. 2003. Evaluation and effect of media, 

biofertilizer and growth regulators on growth 

100



PROFILE CHARACTERISTICS OF SUGARCANE FARMERS IN 

CHITTOOR DISTRICT OF ANDHRA PRADESH 

S. RAMALAKSHMI DEVI, P. V. SATYA GOPAL, V.SAILAJA and S.V. PRASAD 

Department of Extension Education, S.V. Agricultural college, Tirupati-517502 


Sugarcane is the world’s largest crop and is 

grown in over 110 countries. In 2009, an estimated 

1,683 million metric tons were produced worldwide 

which amounts to 22.4% of the total world agricultural 

production by weight (FAO, 2009). India ranks second 

in cane area and sugar production after Brazil. The 

states of Uttar Pradesh, Maharashtra, Karnataka, 

Tamil Naidu and Andhra Pradesh together produce 

nearly 90 per cent of the cane and sugar in the 

country. Andhra Pradesh ranks fifth in sugar cone 

area of the country with a share of 4.83 per cent. 

The average production of Andhra Pradesh is about 

20.30 million tons contributing to 5.83 per cent of 

the total production of the country. In Andhra 

Pradesh, the major sugarcane growing districts in 

Telangana, coastal Andhra and Rayalaseema regions 

are Nizamabad, Visakhapatnam and Chittoor districts 

respectively. 

The significant contribution of researchers, 

extension functionaries and farming community plays 

pivotal role in achieving the above success. On one 

side, the researchers developed sustainable 

technologies to meet the production requirements of 

the farmers followed by effective dissemination of 

technologies by the extension functionaries so as to 

bring the technologies to the farmers for adoption. 

On the other side, the farming community is 

successfully adopting those technologies so as to 

increase the productivity levels of sugarcane. As the 

farmers are the key contributors of production, the 

present study was taken up to study the profile 

characteristics of sugarcane farmers. 

Ex-post-facto research design was adopted 

for the study. The investigation was carried out in 

Chittoor district of Rayalaseema region. Four 

mandals were selected in Chittoor district purposively 

that have highest area under sugarcane. From each 

mandal 3 villages were selected purposively. From 

each village 10 sugarcane farmers were selected 

randomly thus making a total of 120 respondents . 

The data were collected by personal interview method 

through structured interview schedule. 

The sugarcane farmers were distributed into 

different categories based on their selected profile 

characteristics and were presented in the Table 1 

and interpreted through frequencies, percentages, 

mean and standard deviation. 

Age 

Majority (57.50%) of the sugarcane farmers 

belonged to middle age category followed by young 

(31.66%) and old age (10.83%) categories. The 

probable reason for distribution might be that the 

agriculture in the present situation has been perceived 

as a profitable enterprise in particular as sugarcane 

is one of the remunerative crops for the farmers. 

Middle age and young age farmers were motivated 

to cultivate sugarcane by adopting latest production 

technologies and obtaining good returns.. Hence the 

above trend was observed. It is in conformity with 

Reddy (1997) and Gowda et al., (2011). 

Education 

Majority (90.00%) of the respondents were 

educated, 4.17 per cent were under can read and 

write only category and only 5.00 per cent were 

illiterates. The probable reason for the above 

distribution might be that, as education was gaining 

importance for the past three decades and brought 

out awareness among the farming community about 

the functional literacy. Majority of the sugarcane 

farmers were under middle and young age lead to 

the proper educational status among the farming 

community. It is in conformity with Latha (2002) and 

Gowda (2011). 

email: shilpamohan5050@gmail.com 

101

PROFILE CHARACTERISTICS OF SUGARCANE FARMERS 

Table 1. Profile characteristics of sugarcane farmers N=120 

S.No 

AGE 

Category Frequency Percentage MEAN S.D. 

1. Young (56 years) 13 10.83 

- - 

Total 120 100.00 

EDUCATION 

1 Illiterate 6 5.00 

2. Can read and write only 5 4.17 

3. Primary school 9 7.50 

4. Middle school 26 21.67 

5. High school 49 40.83 

- - 

6. Intermediate 15 12.50 

7. College level 10 8.33 

Total 120 100.00 

FARM SIZE 

1. Marginal farmer 4 3.33 

2. Small farmer 65 54.17 

3. Big farmer 51 42.50 

Total 120 100.00 

FARMING EXPERIENCE 

- - 

1. Low 19 15.83 

2. Medium 83 69.17 

3. High 18 15.00 

Total 120 100.00 

EXTENSION CONTACT 

1. Low 17 14.17 

2. Medium 76 63.33 

3. High 27 22.50 

Total 120 100.00 

TRAININGS UNDERGONE 

1 Low 37 30.83 

2 Medium 60 50.00 

3 High 23 19.17 

Total 120 100.00 

SOCIAL PARTICIPATION 

1 Low 14 11.67 

2 Medium 81 67.50 

3 High 25 20.83 

Total 120 100.00 

MASS MEDIA EXPOSURE 

1. Low 13 10.83 

2. Medium 83 69.17 

3. High 24 20.00 

Total 120 100.00 

ACHIEVEMENT MOTIVATION 

102 

25.35 11.12 

9.99 2.20 

1.825 1.0262 

10.75 3.3487 

8.65 2.17

DEVI et al 

S.No 

Category Frequency Percentage MEAN S.D. 

2. Medium 71 59.17 

3. High 23 19.16 

Total 120 100.00 

SCIENTIFIC ORIENTATION 

1. Low 22 18.33 

2. Medium 74 61.67 11.88 2.73 

3. High 24 20.00 

Total 120 100.00 

MANAGEMENT ORIENTATION 

1. Low 15 12.50 35.72. 6.39 

2. Medium 86 71.67 

3. High 19 15.83 

Total 120 100.00 

INNOVATIVENESS 

1. Low 20 16.67 17.64 4.52 

2. Medium 79 65.83 

3. High 21 17.50 

Total 120 100.00 

Farm size 

It is evident from the Table 1 that 54.17 per cent of 

the sugarcane farmers were small followed by big 

farmers (42.50%) and marginal farmers (3.33%). The 

probable reason might be that, sugarcane as a 

commercial crop need to be grown in large farms so 

as to take up required farm management practices 

and also to cope up with the post harvest management 

such as transporting to the sugar factories or taking 

up jaggery preparation. It might be very difficult to 

take up all such activities under small holding 

conditions with half to one acre of land which involve 

high investment leading to less profitability. It is in 

conformity with findings of Pandya (1995). 

Farming experience 

From Table 1 it is evident that 69.17 per cent 

of the sugarcane farmers had medium farming 

experience followed by low (15.83%) and high farming 

experience (15.00%).The probable reason might be 

that as majority of the farmers belong to middle age 

group and also there was awareness among the 

farming community about the education which made 

them to enter into farming after completing their 

education. It is in conformity with Roy (2005) and 

Reddy (1997). 

Extension contact 

From Table 1 it could be seen that 63.33 percent of 

the respondents were having medium extension 

contact followed by low (22.50%) and high (14.17%) 

extension contact. The probable reason f might be 

that as the sugarcane crop is mainly grown under 

the supervision of sugar factories and also the majority 

of sugarcane farmers were educated, the farmers 

always seek for timely extension support from factory 

officials, agricultural officers and the scientists for 

their day to day farm operations for better 

productivity. It is in conformity with Gattu (2001) and 

Roy (2005). 

Trainings undergone 

From Table 1 it could be seen that majority 

of the respondents have undergone no. of medium 

trainings undergone (50.00%) followed by low 

(30.83%) and high (19.17%) number of trainings. This 

might be due to the fact that trainings are the tools 

for upgrading the knowledge and skills in a particular 

area of operation. As sugarcane is the major 

103

PROFILE CHARACTERISTICS OF SUGARCANE FARMERS 

commercial crop, training on different technologies 

will help the farmers in taking up the farm operations 

in more viable and economical ways. On the other 

side lack of awareness on the importance of training 

and also non availability of time to attend the training 

programmers might have contributed for the above 

trend. It is in conformity with Reddy (1997) and Roy 

(2005). 

Social participation 

From Table 4.7 and Fig 4.7 it could be seen 

that majority of the respondents were having medium 

social participation (67.50%) followed by high 

(20.83%) and low (11.67%) levels of social 

participation. The probable reason for the above trend 

might be that, being a member of society everybody 

needs to work together co operatively to achieve 

higher returns. As sugarcane is one of the major 

commercial crops involve year round investment right 

from land preparation, selection of setts to the final 

transportation of sugarcane to the factories. The need 

of being a member or office bearer in such societies 

which directly involve in farming operations of 

sugarcane is essential for taking up appropriate and 

timely operations in farm production. It is in 

conformity with Reddy (1997). 

Mass media exposure 

Majority of the respondents were having 

medium mass media exposure (69.17%) followed by 

high (20.00%) and low(10.83%) levels of mass media 

exposure. The probable reason for this trend might 

be due to the fact that, as majority of sugarcane 

farmers are young and middle aged and ninety five 

per cent of sugarcane farmers were educated had 

inclination towards better utilization of different mass 

media such as radio, T.V, news papers so as to take 

up modern technologies in sugarcane production. The 

farmers with illiteracy and higher age might not be 

utilizing the mass media because of their personal 

and psychological limitations. It is in conformity with 

Reddy (1997) and Sangeetha (2004). 

Scientific Orientation 

More than half (61.66%) of the respondents 

had medium scientific orientation followed by high 

(20.00%) and low (18.33%) of scientific orientation. 

The probable reason might be that there were ample 

number of technologies developed by the scientists 

and disseminated among the farming community 

leading to successful adoption of those technologies. 

This might be because of higher scientific orientation 

among the sugarcane farmers to adopt those 

technologies as per the recommendations of the 

scientists for better returns. The education level, 

extension contact and mass media exposure directly 

contributes for the scientific orientation among the 

sugarcane farmers. Less scientific orientation for few 

farmers might be due to complexity of the 

technologies and illiteracy of the farming community. 

It is in conformity with Reddy (1997). 

Management Orientation 

Perusal of the Table 1 reveals that majority 

(71.67%) of sugarcane farmers had medium 

Management Orientation followed by high (15.83%) 

and low (12.50%) management Orientation. This 

might be due to the fact that sugarcane crop requires 

better management at each and every stage of its 

operations to get high net profit. Year round and timely 

decisions are essential to cope up with the 

environmental and human resource management. 

Morever people might be adopting age old practices 

(traditional way) without proper resource 

management. It is in conformity with Reddy (1997). 

Innovativeness 

Findings from Table 1 show that majority 

(65.83%) of the respondents had medium 

innovativeness followed by high (17.50%) and low 

(16.67%) levels of innovativeness. The possible 

reason might be that the farmers with higher 

education, extension contact and mass media 

exposure were able to update their knowledge and 

skills time to time and ready to accept the new 

technologies in their farming. How ever illiterates and 

resource poor farmers might be lacking awareness, 

knowledge and risk taking ability to adopt such 

technologies. It is in conformity with Hemanth (2002) 

and Gangadhar (2009) findings. 

The results of present study indicated that 

majority of sugarcane farmers are middle and young 

aged with required educational qualification and there 

is every chance of motivating them towards adopting 

sugarcane production technologies so as to enhance 

sugarcane productivity and also net income. As 

104

DEVI et al 

extension contact and mass media exposure were 

the major pillars for diffusing information to farming 

community there is every scope to improve these 

two components so as to utilize the extension 

personnel and mass media for strengthening their 

knowledge and skills. Psychological variables of 

sugarcane farmers i.e. Social participation, scientific 

orientation, management orientation and innovativeness 

were found to be medium and this indicates that these 

variables are the inherent igniters for the human beings. 

Hence, there is need to organize training programmes, 

group discussions, brain storming sessions, exposure 

visits etc. for sugarcane farmers and provide a platform 

to utilize these variables effectively in sugarcane 

cultivation. 

REFERENCES 

Gangadhar, M.M. 2009. Communication factors and 

entrepreneurial behavior of cotton growers. 

Journal of Research, ANGRAU, Hyderabad. 

31(3):62-67. 

Gattu, K.C. 2001. Production constraints of turmeric 

cultivation in Karimnagar district of Andhra 

Pradesh. M.Sc. Thesis submitted to Acharya 

N G Ranga Agricultural University, Hyderabad. 

Gowda, T.A., Babu, C.R., Naidu, G.R and Rao, V.S. 

2011. Profile characteristics of sugarcane 

growers in Mandya district of Karnataka. The 

Andhra Agricultural Journal. 58(2):236-239. 

Hemanth, K. B. 2002. A study on attitude, knowledge 

and adoption of recommended practices by 

oriental tobacco farmers in Chittoor District of 

Andhra Pradesh. M.Sc. (Ag.) Thesis, Acharya 

N G Ranga Agricultural University, Hyderabad. 

Latha, S.M. 2002. A study on knowledge and 

adoption of integrated pest management 

practices in cotton by farmers in Kurnool 

district of Andhra Pradesh. M.Sc. (Ag.) Thesis 



Pandya R.D. 1995. Entrepreneurial behavior of 

sugarcane farmers. Journal of Extension 

Education. 6(4): 1299-1301. 

Reddy, S. 1997. Information Management Behaviour 

(IMB)-An analysis of sugarcane research, 

extension and client system. Ph.D.. (Ag.) 

Thesis. Acharya N G Ranga Agricultural 


Roy, S. 2005. A study on the sustainability of 

sugarcane cultivation in Vishakhapatnam 

district of Andhra Pradesh. Ph.D.. (Ag.) Thesis 


University, Hyderabad 

Sangeetha, V. 2004. Training needs of cotton growers 

of Madurai district of Tamilnadu. M.Sc. (Ag.) 

Thesis submitted to Acharya N G Ranga 

Agricultural University, Hyderabad. 

105



A STUDY ON DIFFUSION STATUS OF SYSTEM OF RICE INTENSIFICATION (SRI) 

IN ANDHRA PRADESH 

K. NIRMALA and R. VASANTHA 

Department of Agricultural Extension 

College of Agriculture, Rajendranagar, ANGRAU, Hyderabad – 500 030 


Any efforts that successfully reduce the 

water allocation for rice even by 20 to 30 per cent 

will help in averting both the food and water crises 

as farmers can continue to grow more rice with less 

water. 

Frequent drought over the past 10 years has 

left the rice farmers of Andhra Pradesh in doldrums. 

Andhra Pradesh experienced severe drought in 1999- 

2000, characterized by water shortages, falling 

groundwater levels and increased risk of 

contamination of surface water. Drought, followed by 

low rainfall (534 mm annual rainfall) in the south-west 

and north-east monsoons during 1999 was 

exacerbated by groundwater extraction. Agricultural 

production was seriously reduced in kharif 1999. 

Thereafter, the thrust for conservative water-usage 

became the major concern for scientists and farmers. 

Depleted water resources, stagnated rice productivity, 

the growing importance of organic agriculture, 

increased production costs and the need for better 

utilization of family labour among small and marginal 

farmers, calls for a shift in cultivation practices. The 

System of Rice Intensification (SRI) offers a way to 

not only reduce the demand for water while growing 

irrigated rice, but also of simultaneously increasing 

rice production. SRI was introduced in Andhra 

Pradesh in kharif 2003 in all 22 districts of the state 

by Acharya N.G. Ranga Agricultural University 

(ANGRAU). Since 2003, ANGRAU and State 

Department of Agriculture has taken several initiatives 

to promote SRI in Andhra Pradesh (www. sriindia.net,2009). 

Today, India has one of the largest numbers 

of SRI farmers in the world. Official record indicates 

that SRI diffused first to Tamil Nadu State, followed 

by Andhra Pradesh (Prasad, 2006). Though Andhra 

Pradesh was the first to start large scale promotion 

of SRI, but no substantial area could be covered 

during the last few years. Even after 9-10 years of 

introduction of SRI technology among farmers of 

Andhra Pradesh, the pace of spread of technology is 

not rapid. 

Hence the present study was conceived to 

know the status of SRI in terms of diffusion and 

adoption across the selected villages and mandals 

of Mahaboobnagar district. 

The present study was conducted in 

Mahaboobnagar district as it has highest cultivated 

area under SRI during 2008-09. Ex-post facto research 

design was followed. A sample of 120 SRI cultivating 

farmers from 12 villages of four mandals of the 

district was selected randomly. Measurement of 

diffusion status was done under three dimensions 

i.e, Diffusion Status, spread of SRI in selected 

villages (secondary data) and adopter categories. 

Diffusion status of System of Rice 

Intensification was operationalised as the extent of 

spread of SRI technology among the farmers from 

2006-07 to 2010-11. Diffusion status was measured 

with the help of developed schedule comprising of 

various items that are pretested. The score obtained 

by a respondent on all items of diffusion status were 

added to get total score. Based on total scores 

obtained, respondents were grouped into 3 categories 

of low, medium and high according to equal class 

interval method. 

The second dimension i.e. spread of SRI in 

selected villages was studied in terms of number of 

farmers adopting and number of acres. Year - wise 

data was collected starting from 2006-07 to 2010- 

2011 (5 years) from secondary sources such as 

Department of Agriculture and NGOs. 

The third dimension i.e. adopter categories 

was studied by categorizing adopters into five 

categories based on the criteria of innovativeness or 

email: drankamarajug@yahoo.com 

106

NIRMALA and VASANTHA 

earliness in adoption i.e. the degree to which an 

individual or others unit of adoption is relatively earlier 

in adopting new ideas than other members of social 

system. 

The year of adoption was taken as criteria to 

determine the earliness of respondents in adoption 

of SRI. Data on number of respondents adopting SRI 

for the first time is collected year wise for five years, 

starting from 2006-07 to 2010-11 and accordingly the 

respondents were grouped into five adopter categories 

viz innovators, early adopters, early majority, late 

majority and laggards. The data was tabulated and 

depicted graphically. 

Distribution of respondents according to their 

diffusion status on SRI is depicted in Fig 1. The 

probable reason for medium to low diffusion status 

of SRI among farming community may be because 

of inherent problems associated with SRI cultivation 

such as nonavailability of skilled labour, organic 

manures, difficulties in land levelling and weeding 

cono weeder, gaps in research and extension, heavy 

rains in kharif etc. 

If the above problems are overcome by 

research and extension agencies by taking necessary 

steps, then there is a possibility for increase in area 

under SRI in the district. 

High 

12.50% 

Low 

35.00% 

Medium 

52.50% 

Fig 1. Diffusion status of SRI technology 

Table 2. Comparision between total Acreage under Rice and SRI 

S.no Year Total 

Acreage 

under 

Rice 

Acreage 

under 

SRI 

% Total 


Farmers 

SRI 

Farmers 

% 

1 2006-07 

2 2007-08 

3 2008-09 

4 2009-10 

5 2010-11 

Total 

1964 6 0.30 982 15 1.52 

2244 63 2.80 748 101 13.50 

2777 245 8.82 925.67 238 25.71 

3438 166 4.82 1719 190 11.05 

3129 149 4.76 1564.5 172 10.99 

13552 629 4.64 5939.17 716 12.05 

107

A STUDY ON DIFFUSION STATUS OF SYSTEM OF RICE INTENSIFICATION (SRI) 

The number of farmers cultivating SRI and 

acreage under SRI is compared with total number of 

rice farmers and rice acreage in the selected villages. 

Percentages were calculated. 

The percentage of SRI acreage over total 

Rice acreage is 0.30 per cent in 2006 -07, 2.80 per 

cent in 2007-08, 8.82 per cent in 2008-09, 4.82 per 

cent in 2009-10 and 4.76 per cent in 2010-11.Whereas 

percentage of farmers adopting SRI over total Rice 

farmers is 1.52 per cent in 2006 -07, 13.50 per cent 

in 2007-08, 25.71 per cent in 2008-09 , 11.05 per 

cent in 2009-10 and 10.99 per cent in 2010-11. 

Results are depicted graphically in figure 1 and 2. 

The secondary sources reported an 

increasing trend both in area and number of farmers 

from the year 2006 (year of inception of SRI) to 2009, 

afterwards a gradual decline is clearly evident in the 

acreage and number of farmers adopting SRI in 

selected villages. The present study showed similar 

trend with respect to cumulative frequency reported 

by Karthik and Manjunatha (2010). 

Percentage adoption of SRI 

50 

45 

40 

35 

30 

25 

20 

15 

10 

5 

0 

Early majority 

Late majority 

Laggards 

Early adopters 

Innovators 

2006-2007 2007-2008 2008-2009 2009-2010 2010-2011 

Years 

Fig.2. Categorisation of adopter on the basis of earliness in adoption (innovativeness) 

Table 3. Distribution of the respondents based on their earliness in adoption (innovativeness) of SRI 

technology 

S.No Year Adopter category N % 

1 2006-2007 Innovators 2 1.66 

2 2007-2008 Early adopters 11 9.17 

3 2008-2009 Early majority 44 36.67 

4 2009-2010 Late majority 40 33.33 

5 2010-2011 Laggards 23 19.17 

Total 120 100.00 

Table 3 indicates that during 2006-07, (year 

of SRI inception in the Mahaboobnagar district) SRI 

was adopted by only a few members i.e only 1.66 

percent, who are termed as innovators. As SRI is a 

new technology it was adopted only by a small 

percent of respondents. During the first year, the 

respondents (innovators) who are having high 

extension contacts and sources of information 

108

NIRMALA and VASANTHA 

adopted this technology. In 2007- 08 there was a 

little increase in number of respondents adopting SRI 

i.e. from1.66 to 9.17 percent, the probable reasons 

could be they might have got convinced by seeing 

SRI performance in innovators fields or there may 

be increase in availability of implements or 

organisation of good number of demonstrations and 

improved extension contacts with concerned 

scientists etc. must have motivated the respondents 

to adopt SRI. During 2008- 09, there was a rapid 

increase in number of farmers adopting SRI i.e. from 

9.17 to 36.67 percent, the probable reason could be 

in order to prevent depletion of ground water 

resources, which generally happens with conventional 

rice cultivation, Government has announced 

incentives to promote SRI in the form of providing 

machinery and inputs at subsidised prices which has 

shot up area under SRI. In 2009- 10, there was a 

little decrease in adoption of SRI i.e from 36.67 to 

33.33 percent, the probable reason may be problems 

with labour In 2010- 11 there was a drastic decrease 

in adoption of SRI due to intensified problems with 

labour, non availability of inputs, difficulties in water 

management, non availability of organic inputs, land 

levelling, weeding operations which has reduced SRI 

cultivation. Study reported a large majority of 

respondents under early and late majority (70%). 

Similar findings were reported by Prasad (1997). 

The curve (Fig.2 ) obtained on Adopter 

categories is an incomplete bell shaped curve. 

According to Rogers (2003) adoption of an innovation 

usually follows a normal bell shaped curve when 

plotted over a time. Since the time tested period is 

short in the present study, the curve could not be a 

complete bell shaped curve. If the study was carried 

out for longer period of time as done by Rogers then 

there is a possibility to obtain a complete bell shaped 

curve for SRI cultivation also. Similar results were 

reported by Ryan and Gross (1943) in hybrid seed 

corn in Iowa. 

The status of diffusion of SRI is medium to low 

in spite of multifarous efforts of government the 

aggregate area under SRI is not to the expectations. 

Though some farmers are able to continue this method 

and reap benefits, some others have adopted SRI 

for one season or two seasons and have discontinued 

it, some others appreciated the method but did not 

adopt it. Lack of perception accuracy and operational 

difficulties might have discouraged farmers to 

continue SRI. Keeping in view of benefits of SRI, 

the government has to take measures to increase 

its diffusion by popularising the benefits of SRI 

through interpersonal and mass communication 

media, announcing incentives in the form of supply 

of organic manures, subsidised markers and 

conoweeders. Funds should be earmarked to 

innovative farmers and NGO’s who were interested 

in developing modified implements, varieties or 

methods in SRI that definitely helps in increasing 

area under SRI. 

REFERENCES 

Karthik, K. B and Manjunatha, B. N. 2010. Adoption 

of hybrid paddy seed production technologies 

in Mandya District. Mysore Journal of 

Agricultural Sciences, 44 (4): 863-865. 

Prasad, S.C. 2006. System of Rice intensification in 

India: Innovation History and Institutional 

Challenges. WWF- ICRISAT Dialogue on 

Water, Food and Environment, Patancheru, 

Hyderabad. http:// wassan.org/Sri/documents/ 

Shambu-SRI. pdf (21 July 2011) 

Prasad, S.V. 1997 A critical analysis of diffusion and 

adoption of production recommendations of 

rainfed castor in Nalgonda district of Andhra 

Pradesh. Ph.D Thesis Acharya N G Ranga 

Agricultural University, Hyderabad. 

Rogers, E. M. 2003. Diffusion of Innovations. 5 th ed. 

New York, London, Toronto, Sydney. 

Singapore: Free Press. 

Ryan, Bryce and Neal C. Gross 1943. “The Diffusion 

of Hybrid Seed Corn in Two Iowa 

Communities”, Rural Sociology, 8:15-24. 

RS(E) Website: www. Sri-india.net, 2009. 

109



CORRELATION AND PATH COEFFICIENT ANALYSIS FOR YIELD AND 

PHYSIOLOGICAL ATTRIBUTES IN RICE (Oryza sativa L.) HYBRIDS UNDER 

SALINE SOIL CONDITIONS 

M.SUDHARANI, P.RAGHAVA REDDY, G.HARIPRASAD REDDY and CH.SURENDRA RAJU 

Seed Research and Technology Centre, Rajendranagar, Hyderabad-500030 


Correlation studies and path coefficient 

analysis were undertaken to know the inter 

relationship of yield components and physiological 

parameters related to salt tolerance and their 

usefulness in selection programmes under salt stress. 

In the present investigation 28 rice hybrids 

derived by crossing eight genotypes (RPBio-226, 

Swarna , CSR-27, CSR-30, CST-7-1, CSRC(S)7-1- 

4, SR26-B and CSRC(S)5-2-2-5 in half diallel manner 

were utilized based on their reaction to salinity 

tolerance and were evaluated during kharif, 2010 

under salt affected soils of Agricultural Research 

Station, Machilipatnam. Seedlings of 30 days old were 

transplanted in the main field having electrical 

conductivity of 7.9 dS/m and pH of 7.7 following 

randomized block design with three replications. The 

recommended agronomic, cultural and plant 

protection measures were followed in conducting the 

experiment. Genotypic and phenotypic correlation 

coefficients were calculated among eight parents 

using the formulae suggested by Al-Jibouri et al. 

(1958) and their significance was tested by using the 

‘r’ table values (Fisher and Yates, 1963) at n-2 

degrees of freedom, where ‘n’ denotes the number of 

treatments used in the calculation. 

To estimate the direct and indirect effects 

of the yield components on the yield, the statistical 

tool employed was path coefficient analysis as 

suggested by Wright (1921) and illustrated by Dewey 

and Lu (1959). The path coefficients were obtained 

by solving the ‘p’ normal equations following the 

matrix method given by Singh and Chowdhary (1985). 

In the present investigation, the genotypic and 

phenotypic correlations amongst the traits followed 

almost similar trend of association, the former being 

a little higher in most of the cases, indicating the 

existence of a strong inherent association between 

the characters. Further, dissecting these associations 

as direct and indirect effects through path analysis 

showed direct contribution of each component trait 

on yield and indirect effect it has through association 

on other component traits. 

The yield component viz., plant height 

(0.5847), number of tillers plant -1 (0.7789), number of 

productive tillers plant -1 (0.5753), panicle length 

(0.8353), panicle weight (0.5500), number of filled 

grains panicle -1 (0.7809), spikelet fertility per cent 

(0.7190), 1000-grain weight (0.5399), root/shoot ratio 

(0.4694) and harvest index (0.8128) were significantly 

and positively correlated with grain yield (Table 1) in 

rice hybrids tested under saline conditions. On the 

other hand Na + /K + ratio and SPAD chlorophyll meter 

readings exhibited significant negative association 

with grain yield, while the effect of days to 50 per 

cent flowering was non-significant. The findings of 

earlier researchers viz., Bala (2001) for plant height; 

Zeng and Shannon (2000), Natarajan et al. (2005) for 

number of tillers plant -1 ; Ravindra Babu (1996), 

Natarajan et al. (2005) for number of productive tillers 

plant -1 ; Bala (2001) for panicle length; Buu and Tuan 

(1991), Ravindra Babu (1996), Natarajan et al. (2005) 

for number of filled grains panicle -1 ; Natarajan et al. 

(2005) for 1000-grain weight ; Sajjad (1990) and Balan 

et al. (1999) for harvest index were in line with the 

present readings. However, Asch et al. (2000) 

reported strong negative association of Na + /K + ratio 

with grain yield which is in agreement with the present 

findings. Under saline soil conditions plant height, 

number of tillers plant -1 , productive tillers plant -1 , 

panicle length, panicle weight, number of filled grains 

panicle -1 , spikelet fertility per cent, SPAD values and 

test weight showed strong positive association with 

grain yield plant -1 under stressed environment. 

email: madugula.sudharani@yahoo.com 

110

SUDHARANI et al 

Table 1. Genotypic (r g 

) and phenotypic (r p 

) correlation coefficients among grain yield, its components and physiological traits in F 1 

hybrids of rice 

under saline soils 

* Significant at p=0.05; ** Significant at p=0.01; 

PH (cm): Plant height; DFF: Days to 50% flowering; TT: Number of tillers plant -1 ; PT: Number of productive tillers plant -1 ; PL (cm): Panicle length; PW(g): Panicle 

weight; 

NFGP -1 : Number of filled grains panicle -1 ; SF (%): Spikelet fertility per cent; TW (g): 1000-grain weight; GY (g): Grain yield (g plant -1 ); SES: SES for visual salt injury; 

RSR: Root /shoot ratio; HI (%): Harvest index per cent; Na + /K + R: Sodium Potassium ratio; SPAD: SPAD chlorophyll meter reading. 

111

CORRELATION AND PATH COEFFICIENT ANALYSIS FOR YIELD 

Table 2. Genotypic (G) and phenotypic(P) direct and indirect effects among grain yield, its components and physiological traits in F 1 

hybrids of rice 

under saline soils 

Residual effect =0.08005 

PH (cm): Plant height; DFF: Days to 50% flowering; TT: Number of tillers plant -1 ; PT: Number of productive tillers plant -1 ; PL (cm): Panicle length; PW(g): 

Panicle weight; 

NFGP -1 : Number of filled grains panicle -1 ; SF (%): Spikelet fertility per cent; TW (g): 1000-grain weight; GY (g): Grain yield (g plant -1 ); SES: SES for visual salt 

injury; 

RSR: Root /shoot ratio; HI (%): Harvest index per cent; Na + /K + R: Sodium Potassium ratio; SPAD: SPAD chlorophyll meter reading. 

112

SUDHARANI et al 

At genotypic level, number of total tillers plant -1 

(1.0876) exhibited highest positive effect on yield 

(Table 2), while substantial magnitude of positive 

direct effect was also exerted by spikelet fertility 

(0.4417). On the other hand, moderate direct effects 

were shown by SES for visual salt injury (0.2692) 

and root shoot ratio (0.2927). The direct effects of 

productive tillers plant -1 (-0.5877), panicle length 

(-0.3681) and panicle weight (-0.3495) were high, but 

negative, while moderate influence in the same 

direction was exhibited by SPAD chlorophyll meter 

readings (-0.2290). The direct positive effects on yield 

were reported for number of grains panicle -1 (Sajjad, 

1990), harvest index (Tripathi et al., 2011) and 

productive tillers plant -1 (Natarajan et al., 2005 and 

Tripathi et al., 2011). Therefore, more emphasis may 

be given to spikelet fertility per cent and number of 

tillers plant -1 while executing selections under saline 

soil conditions. 

The results of present investigation indicate 

selection under saline condition would be effective 

for number of total tillers per plant, spikelet fertility 

per cent as they showed significant positive 

association as well as direct effect on yield. Similarly, 

selecting the plants with low Na + /K + ratio would help 

for yield improvement along with salt tolerance as 

this trait showed significant negative association as 

well as negative direct effect on grain yield under 

stressed conditions Hence, these traits may be 

prioritized for developing ideotype(s) for saline 

environment. 

REFERENCES 

Al-Jibouri, H.A., Miller, P.A and Robinson, H.F. 1958. 

Genotypic and environmental variances and 

co-variances in an upland cotton cross of 

interspecific origin. Agronomy Journal. 50: 633- 

636. 

Asch, F., Dingkunn, M., Dorffling, K and Miezank. 

2000. Leaf K/N ratio predicts salinity induced 

yield loss in irrigated rice. Euphytica. 113: 109- 

118. 

Balan, A., Muthiah, A.R and Boopathi, S.N.M.R. 

1999. Genetic variability, character association 

and path coefficient analysis in rainfed rice, 

under alkaline condition. Madras Agricultural 

Journal. 86 (1/3): 122-124. 

Bala, A. 2001. Genetic variability, association of 

characters and path coefficient analysis of 

saline and alkaline rice genotypes under rainfed 

condition. Madras Agricultural Journal. 88(4- 

6): 356-357. 

Buu, C.B and Tuan, T.M. 1991. Genetic study in the 

F 2 

crosses for high grain quality. International 

Rice Research Newletter. 16: 11. 

Dewey, D.R and Lu, K.N. 1959. Correlation and path 

coefficient analysis of components of crested 

wheat grass seed production. Agronomy 

Journal. 51: 515-518. 

Fisher. R.A and Yates, F. 1963. Statistical Tables 

for Biological, Agricultural and Medical 

Research (6 th Edition), Hafner Publishing 

Company, New York, 

Natarajan, S.K., Saravanan, S., Krishnakumar, S and 

Dhanalakshmi, R. 2005b. Interpretations on 

association of certain quantitative traits on 

yield of rice (Oryza sativa L.) under saline 

environment. Research Journal of Agriculture 

and Biological Sciences. 1(1): 101-103. 

Ravindra Babu, V. 1996. Study of genetic parameters, 

correlations and path coefficient analysis of 

rice (Oryza sativa L.) under saline conditions. 

Annals of Agricultural Research. 17(4): 370- 

374. 

Sajjad, M.S. 1990. Correlations and path coefficient 

analysis of rice under controlled saline 

environment. Pakistan Journal of Agricultural 

Research. 11(3): 164-168. 

Singh, P. K and Chaudhary, B. D.1985. Biometrical 

Methods in Quantitative Genetic Analysis (1 st 

Edition), Kalyani Publishers, New Delhi, India. 

Tripathi, S., Verma, O.P., Dwived, D.K., Yadavendra 

Kumar., Singh, P.K and Verma, G.P. 2011. 

Association studies in Rice (Oryza Sativa L.) 

hybrids under saline alkaline environment. 

Environment and Ecology. 29(3) 1557-1560. 

Wright, S. 1921. Correlation and causation. Journal 

of Agricultural Research. 20: 557-585 

Zeng, L and Shannon, M.C. 2000. Salinity effects on 

seedling growth and yield components of rice. 

Crop Science. 40: 996-1003. 

113



GENETIC DIVERGENCE STUDIES FOR YIELD AND PHYSIOLOGICAL 

ATTRIBUTES IN GROUNDNUT (Arachis hypogaea L.) 

D. NIRMALA, V. JAYALAKSHMI, B. NARENDRA and P. UMAMAHESHWARI 

Deptartment of Genetic & Plant Breeding, Agricultural College, ANGRAU, Mahanandi – 518 503 


Selection of genotypes from the available 

genetic variation is crucial for any crop improvement 

programme. Estimating genetic diversity available in 

the existing germplasm provides clue to the choice 

of most desirable parents for use in hybridization 

programmes. Selections based on physiological traits 

that confer water use efficiency have been suggested 

for improving drought tolerance in Groundnut. In the 

present investigation an attempt was made to identify 

most diverse groundnut genotypes for practical plant 

breeding programmes utilizing physiological traits like 

SPAD Chlorophyll Metre Reading (SCMR), specific 

leaf area, crop growth rate (CGR), relative growth rate 

(RGR) etc. 

Thirty genotypes of Groundnut were 

evaluated during Kharif 2011 at Agricutural College 

Mahanandi, A.P. The experimental material was 

procured from the Groundnut Breeding Station, 

RARS, Tirupati comprising of diverse breeding 

material generated in All India Coordinated Groundnut 

Improvement Programme. The experiment was laid 

out in a Randomized Block Design replicated thrice. 

Each genotype in a replication was grown in two rows 

of 4.2 m length with a spacing of 30 cm between the 

rows and 10 cm within a row. All the recommended 

package of practices were followed to raise a good 

crop. Observations were recorded on five randomly 

chosen plants in each genotype in a replication for 

19 characters. The data collected was analyzed as 

per the standard procedures described by 

Mahalanobis’s (1936) and Rao (1952). 

Analysis of variance for both quantitative and 

physiological traits in all the 30 genotypes under study 

revealed significant differences for all the characters 

indicating the wealth of variability available in the 

germplasm. Further the data was subjected to D 2 

analysis and the results were presented in 

Table 1 to 3. 

Based on D 2 analysis all the 30 genotypes 

were grouped into 14 clusters with a variable number 

of entries in each cluster revealing the presence of a 

considerable amount of genetic diversity in the 

material (Table 2). Cluster I had maximum number 

of 10 genotypes followed by cluster II with 6 

genotypes and cluster X with 3 genotypes. Remaining 

all other clusters possessed one genotype each. 

Cluster I alone had one-third of the total genotypes 

studied indicating that the genotypes under study had 

narrow genetic diversity among them. Similarity in 

the base population from which they have been 

evolved might be the cause of genetic uniformity. 

However, the uni-directional selection potential for 

one particular character or a group of linked traits in 

several places may produce similar phenotypes which 

can be aggregated into one cluster irrespective of 

geographical diversity. Sudhir Kumar et al (2010), 

Awatade (2007) and Garajappa et al. (2005) reported 

that there is no correlation between genetic diversity 

and geographical diversity in the groundnut genotypes 

studied by them. 

Average inter cluster and intra cluster D 2 

values among the 30 genotypes were furnished in 

Table 2. The maximum intra cluster distance was 

recorded for cluster X (6.31) followed by cluster II 

(5.13) and cluster I (4.95) revealing substantial 

diversity within the clusters. Maximum inter-cluster 

values were observed between cluster III and cluster 

XII (12.35) followed by cluster V and cluster XIII 

(12.10) indicating maximum divergence between the 

genotypes included in these clusters. 

Cluster means for all the traits were given in 

Table 2. Cluster means for different characters 

indicated that none of the clusters contained genotype 

with all the desirable characters and so recombinant 

breeding between genotypes of different clusters is 

needed. Cluster XII showed higher cluster means for 

email: veera.jayalakshmi@gmail.com 

114

NIRMALA et al 

weight of pods per plant (17.67), kernel weight per 

plant (12.93) and plant height (67.00) whereas, cluster 

XIV showed highest mean values for number of 

mature pods per plant (19.20) and number of sound 

mature kernels per plant (31.6). Cluster X showed 

high mean values for harvest index (47.0), shelling 

out turn (82.18) and the genotypes of the clusters 

XIII possessed high mean value for 100 seed weight 

(59.33) and number of primary branches per plant 

(6.67). 

Among various traits studied, the highest 

contribution (Table 3) towards divergence was found 

for number of secondary branches per plant (29.89%) 

followed by CGR at 75 DAS to harvest (18.39%) CGR 

at 30-75 DAS (10.57%), 100 seed weight (8.51%), 

plant height (8.51%), SCMR (6.9%) and harvest index 

(5.75%). The manifestation of genetic diversity due 

to number of secondary branches per plant was 

reported by Muralidharan and Manivannan (2004), 

Garajappa et al. (2005), Dolma et al. (2010) and 

Pavan kumar (2010) for harvest index, Sonone et al. 

(2011) for plant height and 100 seed weight. These 

results corroborate with the findings of present study. 

The data on inter cluster distances and per 

se performance of genotypes were used to select 

genetically diverse and agronomically superior 

genotypes. The genotypes exceptionally good for one 

or more characters seemed to be more desirable. 

On this basis, CAUG-1, CSMG 2006-6, LGN 123, R- 

2001-2, and TCGS 150 were selected. Inter crossing 

of divergent groups would lead to greater opportunity 

for crossing over and realizing hidden potential 

variability by disrupting the undesirable linkages. The 

progenies obtained from such diverse genotypes 

provides a greater scope for isolating transgressive 

segregants in advanced generations particularly in 

segmental allotetraploid like groundnut. Hence these 

genotypes could be utilized in a multiple crossing 

programme to recover desirable transgressive 

segregants. 

Table 1. Distribution of 30 genotypes of groundnut in different clusters (Tocher’s method) 

Cluster No. No. of 

Genotype(s) 

genotypes 

I 10 TCGS 876, ICGV 00351, Tirupati 4, TPT 25, TPT 1, ICGV 91114, 

Narayani, DH 218, TCGS-913 ,TPT-2 

II 6 TCGS 901A, UG 6, K 1392, TCGS 901 A, GPBD 4, PBS 30086 

III 1 CSMG 2006-6 

IV 1 TCGS-584 

V 1 TCGS-150 

VI 1 CTMG 7 

VII 1 TG 68 

VIII 1 CSMG 2006-6 

IX 1 RTNG 2 

X 3 K 1463, Greeshma, Bheema 

XI 1 J 71 

XII 1 CAUG 1 

XIII 1 LGN 123 

XIV 1 R-2001-2 

115

GENETIC DIVERGENCE STUDIES FOR YIELD 

Table 2. Average inter cluster distances formed by 30 genotypes of groundnut 

116

NIRMALA et al 

Table 3. Cluster means for 19 characters in 30 genotypes of groundnut (Mahalanobis’s D 2 method) 

Clus 

ter 

No. 

PH = Plant height; PB = Number of primary branches per plant; SB = Number of secondary branches per plant; MP= Number of mature pods per plant; IMMP 

= Number of immature pods per plant; SMK = Number of sound mature kernel; WOP = Weight of pods per plant; KW = Kernel weight per plant; SO = Shelling 

out turn; 100SW =100-seed weight; HI = Harvest index; SLA = Specific Leaf Area; SCMR = SPAD chlorophyll meter reading; O.C = Oil content; CGR1 = Crop 

Growth Rate at 30 DAS to 75 DAS; CGR2 = Crop Growth Rate at 75 DAS to harvest; RGR1 = Relative Growth Rate at 30 DAS to 75 DAS; RGR 2 = Relative 

Growth Rate at 75 DAS to harvest. 

117

GENETIC DIVERGENCE STUDIES FOR YIELD 

REFERENCES 

Awatade, S.M. 2007. Genetic variability, characters 

association, path analysis and genetic 

diversity in groundnut (Arachis hypogaea L.) 

M.Sc. Thesis submitted to Dr. BSKKV, Dapoli. 

Dolma, T., Sekhar, M.R and Reddy, K.R. 2010. 

Genetic divergence studies in Groundnut 

(Arachis hypogaea L.). Journal of Oilseeds 

Research 27:2, 158-160. 

Garajappa, Dasaradha Rami Reddy, C., Naik, K.S.S 

and Srinivasa Rao, V. 2005. Genetic 

divergence in groundnut (Arachis hypogaea L.). 

The Andhra Agricultural Journal 52(3&4): 424- 

436. 

Mahalanobis P. C 1936. On the generalized distance 

in statistics. Proceedings of National Academy 

of Sciences in India 2: 49-55. 

Muralidharan, V and Manivannan, N. 2004. D 2 

analysis in groundnut. Legume Research 

27(4): 302-304. 

Pavan Kumar, C 2010. Genetic divergence in 

groundnut (Arachis hypogaea L.). M.Sc. 

Thesis submitted to Acharya N.G.Ranga 

Agricultural University. 

Rao, C.R.V 1952. Advanced statistical methods in 

biometrical research. John Wiley and Sons 

Inc., New York, pp.236-272. 

Sonone, N.G., Thaware, B.L., Bhave, S.G., Jadhav, 

B.B., Joshi, G.D and Dhekale J. S. 2011. 

Multivariate studies in groundnut (Arachis 

hypogaea L.). Journal of Oilseeds Research 

28 (1): 24-28. 

Sudhir Kumar, I., Venkstaravana, P. and Marappa, 

N. 2010. Genetic divergence of new germ 

plasm and advanced breeding lines of 

Groundnut (Arachis hypogaea L.) studied 

under late Kharif situation. Legume Research 

33(2):124-127. 

118



INFLUENCE OF METHODS OF IRRIGATION ON PLANT GROWTH, YIELD, 

FLOWER QUALITY AND VASE LIFE IN DENDROBIUM ORCHID HYBRID 

SONIA-17 UNDER SHADE NET 

B. GOPALA RAO, P.T. SRINIVAS and M.H.NAIK 

Department of Horticulture, Sri Venkateswara Agricultural College, 

Acharya N.G. Ranga Agril. University, Tirupati-517502 


Dendrobium is the biggest genera in the 

Orchidaceae family and commands a major share 

in foreign exchange. It is a water loving plant and 

needs irrigation every day. Crops, in the absence of 

definite recommendation are irrigated with different 

methods which have definite effects on the growth, 

development and performance. In such situation 

standardization of method of irrigation is necessary 

in realising the highest benefit of irrigation and save 

both cost and water. In view of this, the present 

investigation was under taken to study the effect of 

method of irrigation on vegetative and floral 

characteristics and longevity of Dendrobium hybrid 

Sonia-17. 

The experiment was conducted at orchid 

farm, Nathanallur village, Kancheepuram district, 

Tamil Nadu during the year 2006. There were four 

treatments replicated five times in a completely 

randomized block design. The Dendrobium hybrid 

Sonia-17 owing to its superiority for yield and quality 

was used for the study. The following are the 

treatment details: T1: Mist irrigation, T2: Drip 

irrigation, T3: Hose irrigation, T4: Hand watering 

(control). Observations on various parameters like 

plant height, number of leaves per plant, number of 

shoots per plant, and number of spikes per plant, 

length of spike, number of florets per spike, floret 

pedicel length, longevity of spike on the plant and in 

the tap water (vase life) were recorded at 180 and 

195 days after planting respectively. 

Among the four methods of irrigation 

included, plants grown under mist recorded maximum 

height (50.34 cm). Mist increases the humidity in 

the green house, thus it retains mist in both container 

and growing media which might enhanced the plant 

height (Table 1). Misting increased plant growth and 

yield by decreasing the canopy temperature and 

increasing the relative humidity (Stalmakh et al., 

1986),whereas lowest height of plants was recorded 

in hand watering (37.96 cm) which is on par with hose 

irrigation (38.68 cm),other growth parameters like 

number of leaves per plant (11.09), number of shoots 

per plant (6.63) were maximum in mist irrigated 

plants, whereas minimum in hand watering 

(8.84),(5.19). Gislerod and Nelson (1989) and Gislerod 

and Mortenson (1990) obtained similar results in 

Chrysanthemum and Begonia. 

Floral characters such as number of spikes 

per plant (2.91), length of spike (38.84 cm), number 

of florets per spike (9.99) and floret pedicel length 

(4.31 cm) were maximum under mist (Table 1), while 

hand watering recorded minimum number of spikes 

per plant (2.28),spike length (28.30 cm), number of 

florets per spike (5.43) and length of floret pedicel 

(3.58 cm), this might be due to increase in production 

source (leaves) and nutrients which might have helped 

in better synthesis of carbohydrates. Number of 

flowers and flower buds significantly increased with 

relative humidity in Saintpaulia (Mortensen., 1986). 

Longevity of flower spike on the plant was 

the highest under mist irrigation (94 days), whereas 

the lowest under hand watering (76 days). Vase life 

of flower spike in tap water was maximum from mist 

irrigated plants (21 days) and hand watered plants 

(control) recorded minimum vase life (18 days) 

(Fig 1). Nair and Sujatha (2004) stated that orchids 

require 60-80 per cent humidity to perform their best 

bloom. 

Hence, based on the above results, mist 

irrigation under shade net is ideal for successful 

production of growth and blooms in the Orchid. 

email: gopal_hort@yahoo.co.in 

119

INFLUENCE OF METHODS OF IRRIGATION ON PLANT GROWTH 

Table 1. Growth (at 180 DAP) and Flowering (at 195 DAP) characteristics of Dendrobium Orchid hybrid 

Sonia-17 grown under different methods of irrigation under shade net 

Treatments 

T1: Mist 

irrigation 

T2: Drip 

irrigation 

T3: Hose 

irrigation 

T4: Hand 

watering 

(control) 

Plant 

height 

(cm) 

Number 

of leaves 

/plant 

Number 

of 

shoots 

/plant 

Number 

of spikes 

/plant 

Number 

of florets 

/Spike 

Spike 

length 

(cm) 

Floret 

pedicel 

length (cm) 

50.3 11.0 6.6 2.9 9.9 38.8 4.3 

40.4 9.4 6.1 2.5 6.7 28.4 3.7 

38.6 9.0 5.6 2.5 5.9 29.6 3.8 

37.9 8.8 5.1 2.2 5.4 28.3 3.5 

CD at 5% 1.6 0.3 0.3 0.1 0.7 1.2 0.4 

Fig 1. Longevity of spikes on the plant and in the vase at room temperature of Dendrobium Orchid 

hybrid Sonia-17 as influenced by method of irrigation 

REFERENCES 

Gislerod, H. R and Nelson, P. V. 1989. The 

interaction of relative air humidity and carbon 

dioxide enrichment in the growth of 

Chrysanthemum x Morifolium Ramat. Scientia 

Horticulturae 38: 305-313. 

Gislerod, H. R and Mortenson, L. M. 1990. Effect of 

relative humidity and nutrient concentration 

on nutrient uptake and growth by Begonia x 

Hiemalis Fotsch. Schwabeland’. Horticultural 

Science 25(5): 524-526. 

Mortensen, L. M. 1986. Effect of relative humidity 

on growth and flowering of some green house 

plants. Scientia Horticulture. 29(4): 301-307. 

Nair, S. A and Sujatha, 2004. Growing orchids, 

prospects and advances, Floriculture Today 

9(7):27-28. 

Stalmakh, E.A., N.D. Cherenkov and M.A. Kuzin, 

1986. Mist irrigation is effective. 

Kartofeliovoshchi, 3: 17. 

120



STUDY ON PESTICIDE RESIDUES OF SELECTED VEGETABLES GROWN IN 

NORTH COASTAL ZONE OF ANDHRA PRADESH 

Y. PUNYAVATHI and V. VIJAYALAKSHMI 

College of Home Science, Saifabad, Hyderabad - 500004 


An attempt was made to estimate the 

pesticide residues in various vegetables (before and 

after processing) grown in north coastal zone of 

Andhra Pradesh. The fresh vegetable samples of 

brinjal, bitter gourd and tomato were collected 

randomly from three farmers in each of the three 

districts (Visakhapatnam, Vijayanagaram and 

Srikakulam). The pesticide residue content of the 

selected whole and processed vegetables (soaked 

in 3% salt water for 15 min) were analyzed for the 

pesticides namely chlorophyriphos, quinalphos, 

endosulfan, acephate, monocrotophos and 

carbofuran. 

Pesticide residue was determined by the 

method of Sharma (2007). Non-ionic residues were 

extracted with acetone / water, and the residues from 

were separated aqueous acetone to dichloromethane 

/ hexane phase. The traces of dichloromethane were 

removed and made up to the final extract with 

acetone/ hexane. Organophosphate residues were 

determined directly by gas chromatography with 

ECD/NPD Detector. 

The level of pesticide residue in all the 

selected whole and processed vegetables were below 

detectable level (BDL). The chromatogram of the 

samples are given in the figures 1-6. Reddy et al. 

(1998) also found that the level of pesticide residue 

in vegetables sampled from Srikakulam was below 

Maximum Residue Limits (MRL). 

In field studies conducted in India, the 

maximum initial deposits of cypermethrin, 

fenvalerate and deltamethrin applied to cabbage at 

50, 50 and 12 g a.i./ha were 0.34, 0.96 and 0.25 mg/ 

kg, respectively on heads, and 1.34, 0.08 and 0.30 

mg/ kg, respectively on leaves. These values were 

within the maximum residue limits of 2 mg/ kg for 

cypermethrin and fenvalerate on lettuce heads, and 

0.5 mg/ kg for deltamethrin on leafy vegatables. Most 

of the insecticide residues were found on the outer 

leaves and it was concluded that the residue levels 

found do not constitute any health hazard to 

consumers (Singh et al. 1992). Chahal et al. (1992) 

investigated the persistence of residue of endosulfan 

and fenvelerate on okra and found that the residues 

required a holding period of 1-3 days to become safe 

for consumption. 

Persistence of fluvalinate and the safe interval 

between the last application and the harvest of brinjal, 

okra, cauliflower and cabbage were determined at 

two dose rates in field experiments in India. Residues 

at 30 g a.i./ha persisted for 7, 10 and 15 days on 

brinjal, okra, cabbage and cauliflower respectively. 

A post application holding period before harvest of 

one day was suggested for these crops after 

treatment with fluvalinate (Agnihotri et al. 1992). 

Bordia and Gupta (1992) reported initial deposits of 

1.17, 12.80, 29.27 and 3.23 mg/kg when 0.05% 

monocrotophos, 0.1% carbaryl, 0.07% endosulfan 

and 0.05% fenitrothion, respectively, were applied in 

foliar application to cauliflowers in the field. Residues 

of monocrotophos, endosulfan and fenitrothion fell 

to about 50% in 3 days and those of carbaryl in 7 

days. Residues of monocrotophos, carbaryl and 

fenitrothion were below the level of detection in 15 

days, and those of endosulfan in 21 days indicating 

that they have to be harvested only after 15 days / 

21 days respectively after application of pesticides. 

After 4 days tomatoes contained 1.02, 0.41 and 1.46 

ppm profenofos, pirimiphos-methyl and 

methamidophos, respectively. Tomatoes were 

considered to be safe for human consumption 1 day 

after treatment with pirimiphos-methyl and 8 days 

after treatment with profenofos or methamidophos 

( Abdalla et al. 1993). 

The residues of most commonly used 

pesticides (endosulfan, cypermethrin, dimethoate, 

email: punyavathi.45@gmail.com 

121

STUDY ON PESTICIDE RESIDUES OF SELECTED VEGETABLES 

monocrotophos and mancozeb) on vegetables grown 

in India were observed by Dethe et al. (1995). 

Detectable levels of residues of endosulfan, 

cypermethrin, dimethoate, monocrotophos and 

mancozeb were observed in 33.3% samples of 

tomatoes (endosulfan, dimethoate and 

monocrotophos), 73.3% samples of brinjal 

(endosulfan, cypermethrin , fenvalerate, quinalphos, 

dimethoate and monocrotophos), 14.3% samples of 

okra (endosulfan), 88.9% samples of cabbage 

( endosulfan, fenvalerate and dimethoate) and 100% 

of cauliflower ( endosulfan, fenvalerate, dimethoate, 

cypermethrin, and monocrotophos). However, the 

levels of pesticide residues were below the prescribed 

MRLs. 

Moreover, pesticide residues in all the selected 

vegetables were below detectable level (BDL) in both 

whole and processed vegetables which reflects that 

the pesticides used were highly volatile and required 

holding period was taken to harvest the product. 

6.0 

5.5 

5.0 

4.5 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 

Fig 1. Chromatogram of multiple residues in whole Brinjal 

7.0 

6.5 

6.0 

5.5 

5.0 

4.5 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 

Fig 2. Chromatogram of multiple residues in processed Brinjal 

122

PUNYAVATHI and VIJAYALAKSHMI 

6.5 

6.0 

5.5 

5.0 

4.5 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 

Fig 3. Chromatogram of multiple residues in whole Bitter gourd 

7.0 

6.5 

6.0 

5.5 

5.0 

4.5 

4.0 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 

Fig 4. Chromatogram of multiple residues in processed Bitter gourd 

123

STUDY ON PESTICIDE RESIDUES OF SELECTED VEGETABLES 

100 

80 

60 

40 

20 

0 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 

Fig 5. Chromatogram of multiple residues in whole Tomato 

800 

600 

400 

200 

0 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 

Fig 6. Chromatogram of multiple residues in processed Tomato 

124

PUNYAVATHI and VIJAYALAKSHMI 

REFERENCES 

Abdalla, E. F., Sammour, E. A., Abdallah, S. A and 

Ei-Sayed, E. I. 1993. Persistence of some 

organophosphate residues on tomato and bean 

plants. Bulletin of Faculty of Agricultural 

University Cario, Egypt. 44 (2): 465-476. 

Agnihotri, N. P., Gajbhiye, V. T., Rai, S and 

Srivastava, K. P. 1992. Persistence and safe 

waiting period of fluvalinate on some 

vegetables. Indian Journal of Entomology. 54: 

299. 

Bordia, J. S and Gupta, H. C. L. 1992. Residues of 

monocrotophos, carbaryl, endosulfan and 

fenitrothion in cauliflower. Indian Journal of 

Entomology. 54 (2): 230-232. 

Chahal, K. K., Singh, B and Singh, P. P. 1992. 

Persistence of endosulfan and fenvalerate on 

okra fruits. Indian Journal of Ecology. 19 (2): 

196-199. 

Dethe, M. D., Kale, V. D and Rane, S. D. 1995. 

Pesticide residues in/on farm gate samples 

of vegetables. Pest management in 

Horticultural Eco system. 1: 49-53. 

Reddy, D. J., Rao, B.N., Sultan, M. A. and Reddy K. 

N. 1998. Pesticide residues in farm gate 

vegetables. Journal of Research ANGRAU. 26: 

6-10. 

Sharma, K. K. 2007. Pesticide Residue Analysis 

Manual. ICAR, Directorate of information and 

publications of Agriculture, New Delhi. 

Singh, B., Singh, P. P., Bhattu, R.S and Kalra, R. I. 

1992. Residues of some synthetic Pyrethroid 

insecticides on cabbage. Pesticide Residue 

Journal. 4 (2): 134-141. 

125



A STUDY ON THE KNOWLEDGE LEVEL OF FARMERS ON RECOMMENDED TEA 

CULTIVATION PRACTICES IN NEPAL 

KESHAV KATTEL, R. VASANTHA and M. JAGAN MOHAN REDDY 

Department of Agricultural Extension, College of Agriculture 

Rajendranagar, ANGR Agricultural University, Hyderabad-500 030 


Inspite of the suitable climate and other 

conducive factors, the tea growers in Nepal are not 

able to fully reap the benefits of this highly export 

oriented crop. This has resulted in a stagnation of 

the area of tea cultivation. The yields are particularly 

lower than the adjoining regions of India coupled with 

poor quality of the produce. Against this background, 

a research was conducted to assess the level of 

knowledge of the farmers on recommended tea 

cultivation practices and provide insights on the 

reasons for the underperformance of the Nepal’s tea 

industry. 

An exploratory research design was adopted 

for the study. As tea cultivation is confined to Jhapa 

and Ilam, these two districts were selected for the 

study. Jhapa represents the Terai or plains while Ilam 

represents the hilly area. Three Village Development 

Committees (VDCs) from each district were randomly 

picked and 15 farmers from each VDC were selected 

thus making a total of 90 respondents. A well prepared 

and pretested interview schedule consisting of all the 

recommended practices on tea cultivation was 

prepared by consulting the experts in the field. The 

knowledge schedule consisted of 32 items on tea 

cultivation made in the form of multiple choices, fill 

in the blanks and true (or) false statements. The 

collected data were analyzed using equal class 

intervals, frequencies and percentages. 

Majority of the respondents were of the 

middle age group (50%) and educated up to school 

level (81%). They had low experience in tea 

cultivation (48%) and were semi-medium farmers 

(33%). Fifty per cent of the respondents had medium 

socio-economic status. Majority of them had low 

extension contact (46%) with the extension agencies 

and did not receive any training (39%). In case of 

market intelligence, majority of them had medium 

market intelligence (60%). A considerable percentage 

of respondents reported that labour availability was 

difficult for tea cultivation (57%) and they were not 

timely available (69%). Majority of the respondents 

expressed that the inputs were readily available (41%) 

but not available timely (59%). Majority of the 

respondents (57%) had utilized loans from the lending 

agencies. Majority of the respondents had medium 

risk orientation (56%), innovativeness (60%) and 

achievement motivation (59%). 

Majority of the respondents (60%) had 

medium knowledge followed by low (18%) and high 

(16%) level of knowledge on recommended tea 

cultivation practices. To get a better insight on the 

level of knowledge of respondents on various items 

of the tea cultivation practices an item analysis on 

tea cultivation practices was done as depicted in 

Table 1 below. 

The item analysis revealed that cent per cent 

of the respondents had knowledge on the items such 

as ideal time for pruning and the recommended shade 

trees for tea cultivation. A large majority of the 

respondents (>80%) had knowledge on ideal soil, 

best climate, recommended mulches for tea 

cultivation, interval between two irrigations, optimum 

distance between the plants, reasons for the 

occurrence of collar canker disease, best time for 

planting, plucking cycles for different seasons, 

recommended types of planting, use of urea in pits 

at the time of planting and good winter and early 

spring rainfall improves yield. 

Nearly, 50 to 80 percent of the respondents 

had knowledge on optimum pH of soil for tea 

cultivation, selection of planting material with at least 

email: kattel_k@yahoo.com 

126

KATTEL et al 

Table 1. Item Analysis of respondents knowledge on recommended Tea cultivation practices 

N=90 

S.No. 

Knowledge Items 

Correct 

Response 

Percentage 

Incorrect 

Response 

Percentage 

1 Ideal soil for tea cultivation 88 12 

2 The optimum soil pH for tea cultivation 60 40 

3 The minimum number of clones that should be grown for 

tea cultivation in a given area 29 71 

4 Recommended types of mulches for tea cultivation 91 9 

5 The optimum number of plants per hectare of land 74 26 

6 Symptoms of boron deficiency 12 88 

7 What should be the height of Permanent frame? 76 24 

8 Reasons for occurrence of Collar Canker disease 92 8 

9 Optimum days between two consecutive irrigation 82 18 

10 The ideal time for pruning 100 0 

11 The depth of ground water table for tea cultivation 74 26 

12 The percentage of total area that one single clone variety 

should occupy 0 100 

13 The clone to seed ratio 19 81 

14 The optimum distance for planting 83 17 

15 The ideal depth of pits for planting 30 70 

16 The symptoms of Potassium deficiency 21 79 

17 Two types of planting generally recommended in tea 

cultivation 94 6 

18 Chemical for the control of Black rot 19 81 

19 The concentration for foliar application of Zinc Sulphate 33 67 

20 The plucking cycle for flush season and for other seasons 90 10 

21 The planting material should have at least 12 good mature 

buds 76 24 

22 Application of N and P fertilizers in 2 or more splits 77 23 

23 Symptoms of blister blight on tea 59 41 

24 Recommended shade trees for tea cultivation 100 0 

25 The best time for planting of tea is April to June 91 9 

26 Moderately hot and humid conditions are best for tea 

cultivation 90 10 

27 Spraying of insecticides or fungicides indiscriminately 

increases the incidence of mites 56 44 

28 Good rainfall during winter and early spring improves tea 

yield 93 7 

29 Correct dose of application of Hexaconazole 78 22 

30 Urea should not be applied in the pit at the time of planting 82 18 

31 Various types of bio-fertilizers for tea cultivation 37 63 

32 Various types of bio-pesticides for tea cultivation 56 44 

12 good mature buds, the optimum number of plants 

per hectare, the height of the permanent frame, 

various types of bio pesticides, the use of fertilizers 

in splits, depth of ground water table, doses of 

127

A STUDY ON THE KNOWLEDGE LEVEL OF FARMERS ON TEA CULTIVATION 

hexaconazole, incidence of mites population due to 

indiscriminate sprayings and symptoms of blister 

blight disease. 

Less than 50 per cent of the respondents 

had knowledge on minimum number of clones required 

in an area, the clone to seed ratio that should be 

maintained, symptoms of boron and potassium 

deficiency in plants, control of diseases such as black 

rot, recommended depth of pits for planting, various 

types of bio fertilizers and Zinc sulphate concentration 

for foliar application. Surprisingly, none of the 

respondents had knowledge on the percentage of total 

area that one single clone variety should occupy in a 

given area of field. 

The items which demand high technical 

knowledge or advices from experts such as 

knowledge on nutrient deficiency symptoms, clone 

to seed ratio, chemical for black rot control were not 

answered by more than 80 per cent of the respondents 

and 100 per cent of them had no knowledge on the 

percentage of area that a single clone variety should 

occupy. Unfortunately, these are the yield 

determining factors in tea cultivation and non adoption 

of which leads to low yields. 

REFERENCES 

Anonymous. 2010. Smarika: Tea and Coffee. National 

Tea and Coffee Development Board. New 

Baneshwor, Kathmandu. 

Thapa, Ajit N. S. 2005. Concept paper on study of 

Nepalese tea industry- Vision 2020. Nepal Tree 

Crop Global Development Alliance (NTCGDA), 

Winrock International, Baneshwor, 

Kathmandu, Nepal. 

Verma Pramod, Sonalika Gupta and D. K. Sharma. 

2010. Economic analysis of Himachal tea 

industry- A study of co-operative factories and 

tea planters. Journal of Plantation Crops. 

38(3):194-200. 

128



AN ECONOMIC ANALYSIS OF VALUE ADDITION TO COTTON 

E. RADHIKA, R. VIJAYA KUMARI and D.V. SUBBA RAO 

Department of Agricultural Economics, College of Agriculture 

ANGR Agricultural University, Rajendranagar, Hyderabad – 500 030 


The processing of cotton is a business which 

is undertaken for the purpose of value addition to the 

produce. The value addition to cotton takes place at 

three main stages of processing viz., ginning, 

spinning and weaving. 

The ginning of cotton is important for value 

addition to the produce, as the spinning mills accept 

cotton only after ginning. Indian ginning industry is 

very large in size and is spread over a large area in 

cotton growing states. An attempt was made to study 

the cost and returns, value addition in case of cotton 

ginning and spinning industries and also the benefit 

cost analysis, which gives an intensified idea about 

the profitability condition the unit. 

The study was undertaken in Adilabad and 

Guntur districts of Andhra Pradesh. The study is 

based on primary data (for the year 2010-2011) 

collected from ginning and spinning units. A 

multistage random sampling technique was employed 

for the selection of sample units. 20 ginning units 

and 5 spinning units were selected for the study. The 

data collected was subjected to analysis through 

tabular analysis. 

On an average, the total cost incurred in the 

processing of kapas to lint worked out to Rs. 4630.87 

per quintal of kapas. It is worth noting that the total 

variable cost (Rs. 4545.75 per quintal) formed a 

substantial component (98.2%) of the total cost of 

processing of kapas to lint. The total fixed cost being 

Rs. 85.12 per quintal, accounted for only 1.8 per cent 

of the total cost of processing. In the total fixed cost 

(Rs. 85.12), salaries to permanent staff (Rs. 33.56) 

found to be the major component and accounted for 

0.72 per cent of total processing cost followed by 

interest on fixed capital, insurance and depreciation 

on building and machinery, which accounted for 0.43 

per cent, 0.34 per cent and 0.2 per cent of the total 

fixed cost respectively. Licence fee and taxes 

together accounted for 0.12 per cent of the total cost 

of processing of kapas to lint. Of the total variable 

costs, the cost of raw material (Rs. 4238 / quintal) 

accounted for 91.51 per cent of the total processing 

cost, followed by interest on working capital (Rs. 

216.75 / quintal) accounting for 4.68 per cent, 

electricity charges (Rs. 49.97 / quintal) accounting 

for 1.08 per cent and wages to casual labour (Rs. 

22.3 / quintal) for 0.48 per cent. The repair and 

maintenance (Rs. 15.91 / quintal) and telephone 

charges (Rs. 2.82 / quintal) altogether accounted for 

0.45 per cent of the total cost incurred in the 

processing of kapas. These results are in line with 

the results of Mundinamani (2000) and Dodamani 

(2007). 

Table 1. Returns from processing of kapas to lint (for one quintal of kapas ginned) 

S.No 

email: etttediredhikareddy@gmail.com 

Particulars 

129 

Amount 

(Rs) 

1 Returns from main product(lint) 3978.81 

2 Returns from by-product (seed ) 991.6 

3 Gross returns 4970.41 

4 Raw material cost (kapas) 4238 

5 Value addition 732.41 

6 Processing cost 392.87 

7 Net value addition 339.54 

8 Benefit-cost ratio 1.86

AN ECONOMIC ANALYSIS OF VALUE ADDITION TO COTTON 

The processing of one quintal of kapas 

resulted in 33 kg of lint, 65 kg of seed and 2 kg of 

waste. The gross returns obtained from ginning one 

quintal of kapas were Rs. 4970.41 of which the returns 

from main product (lint) were Rs. 3978.81 and that 

from byproduct (seed) were Rs. 991.6. Cost of raw 

material (kapas) was Rs. 4238 with a value addition 

to the product in the process being Rs. 732.41 and 

cost of processing accounting Rs. 392.87. The net 

value added as a result of processing of kapas to lint 

was Rs. 339.54 per quintal of kapas processed. The 

benefit cost ratio worked out to 0.86 in kapas 

processing. Similar results were observed with 

Mundinamani (2000) and Dodamani (2007). 

Among all the costs incurred in marketing of 

ginned cotton, the maximum cost was incurred on 

packing material Rs.30.36 per quintal, accounting for 

37.47 per cent of the total cost of marketing. As the 

packing material was very important in case of lint 

marketing, it constituted the maximum percent. This 

was followed by sales tax, miscellaneous costs and 

selling expenditure, which accounted for 25.02 per 

cent, 20.33 per cent and 17.18 per cent of the total 

cost of marketing of one quintal lint, respectively. 

These results are on par with the results of 

Shivakumar et al. (2001). 

The average total cost incurred in the 

processing of lint to yarn was Rs.17201.64 per quintal, 

of which the total variable cost was Rs.15497.16 

forming the major component (90.09%) of the total 

cost of processing of lint. The total fixed cost being 

Rs.1704.48 per quintal accounted for 9.91 per cent 

of the total cost of processing. Of the variable cost 

the cost of raw material (Rs.12000/quintal) accounted 

for 69.76 per cent followed by electricity charges 

(9.82%) and interest rate on working capital (5.72%). 

The cost on wages to casual labour, repair and 

maintenance, office maintenance, telephone charges 

together accounted for 4.76 per cent of the total cost 

of processing. 

In the total fixed cost (Rs.1704.48), 

depreciation amounts Rs.1427.06 (8.27%), which was 

found to be major component. This was followed by 

salary to permanent staff i.e., Rs.176.9 (1.02%) and 

interest on fixed capital, insurance, taxes, license 

fee, together accounting 0.58 per cent of the total 

cost of lint to yarn. These results are in line with 

Mundinamani (2000) and Shivakumar et.al (2001). 

The processing of one quintal of lint on an average 

yielded 73 kg of yarn and 27 kg of waste material. 

The gross returns obtained from processing (spinning) 

of one quintal of lint were Rs.20435, which comprised 

of mainly returns from yarn (Rs.18250) and wastage 

(Rs.2185). The value addition in the process was 

Rs.8435. The net value added as a result of 

processing of lint to yarn was Rs.5933.36 per quintal 

of lint processed. The resultant benefit-cost ratio was 

1.62. 

Table 2. Returns in processing of lint to yarn (for one quintal of lint spinned) 

S.No Particulars Amount (Rs) 

1 Returns from main product(yarn) 18250 

2 Returns from wastage 2185 

3 Gross returns 20435 

4 Raw material cost (kapas) 12000 

5 Value addition 8435 

6 Processing cost 5201.64 

7 Net value addition 5933.36 

8 Benefit-cost ratio 1.62 

Among all the costs incurred in marketing of 

spinned cotton, the maximum cost was incurred on 

packing material, Rs.275.48 per quintal, accounting 

for 47.9 per cent of the total cost of marketing. This 

was followed by commission charges Rs.246.45 

(42.85%) and export expenses, yarn sale expenses, 

yarn freight together accounting for 9.22 per cent of 

the total cost of marketing of one quintal yarn. These 

results are in line with the results of Shivakumar et 

al. (2001). 

130

RADHIKA et al 

Thus, the results of analysis indicated that an 

additional value to the extent of Rs.2297.54 was 

created in the course of processing cotton kapas in 

to yarn. The breakup of the same at different levels 

of processing i.e., at ginning was Rs.339.54 (14.78%) 

and spinning Rs.1958 (85.22%). 

Table 3. Total net value addition to one quintal of cotton by processing 

S.No Stage of processing Net value addition (Rs) Per cent 

1 Ginning 339.54 14.78 

2 Spinning 1958 85.22 

Total net value addition to cotton 2297.54 100 

REFERENCES 

Dodamani, M.T and Kunnal L.B. 2007. Value addition 

to organically produced naturally- coloured 

cotton under contract farming. Agricultural 

Economics Research Review. 20:521-528. 

Mundinamani, R.M. 2000. An economic analysis of 

value addition to Cotton in Gadag district. 

M.Sc. (Ag) Thesis submitted to University of 

Agricultural Sciences, Dharwad. 

Shivakumar, S., Sonnad, J.S and Basavaraj, H. 

2001. Economics of cotton ginning and 

pressing in Bellary District. Agricultural 

marketing. 43(4): 9-12. 

131



DEVELOPMENT OF PHYTOSTEROL ENRICHED FLAVOURED MILK 

M. PENCHALA RAJU , ANURAG CHATHURVEDI and APARNA KUNA 

Department of Food Technology, Post Graduate and Research Centre, 

Acharya N.G. Ranga Agricultural University, Rajendranagar, Hyderabad-500 030 


Phytosterol potency in decreasing serum low 

density lipoprotein (LDL) cholesterol levels and thus 

in protecting against cardiovascular diseases, has 

led to the development of functional foods enriched 

with plant sterols. At present, several functional food 

product types such as spreadable fats, yoghurts and 

milk, with free phytosterols or phytosteryl fatty acid 

esters or phytostanyl fatty acid esters added at high 

levels are available in the market especially in several 

European countries (Laakso, 2005). 

When phytostanols and phytosterols are 

included in the diet in sufficient amounts, i.e. 2–3 

g/d, they efficiently decrease serum cholesterol 

concentration by reducing the absorption of 

cholesterol from the digestive tract. The average 

reduction in total cholesterol is 10%, and 15% in LDL 

cholesterol. No changes occur in serum HDL 

cholesterol or triacylglycerol concentrations (Katan 

et al., 2003). In addition to the blood cholesterollowering 

effect, phytosterols have shown the following 

activities in animals:anti-cancer properties (with a 

beneficial effect upon the inhibition of colon cancer 

development) (Awad et al., 2003) and 

antiatherosclerotic, anti-inflammatory (Bouic, 2001) 

and anti-oxidative effects (van Rensburg et al., 2000). 

Sterols make up the largest proportion of the 

unsaponifiable fraction of lipids. Plant fats and oils 

contain phytosterols as naturally occurring 

constituents. The most important natural sources of 

plant sterols in human diets are oils and margarines, 

although they are also found in a range of seeds, 

legumes, vegetables and unrefined vegetable oils. 

Cereal products are a significant source of plant 

sterols, their contents, expressed on a fresh weight 

basis, is higher than in vegetables (Phillips et al., 

2005). 

The exact mechanism by which phytosterols 

decrease serum cholesterol levels is not completely 

understood, but several theories have been proposed. 

One of them suggests that cholesterol in the intestine, 

already marginally soluble, is precipitated into a 

nonabsorbable state in the presence of added 

phytosterols and stanols (Jones and AbuMweis, 

2009). Another theory is based on the fact that 

cholesterol must enter bile-salt and phospholipidcontaining 

‘mixed micelles’ in order to pass through 

intestinal cells and to be absorbed into the 

bloodstream. Moreover, phytosterols may modulate 

the action of key transporters involved in cholesterol 

absorption. Cholesterol absorption is a very important 

physiological mechanism that regulates cholesterol 

metabolism (Rozner and Garti, 2006). Phytosterols 

may reduce cholesterol absorption by competing with 

cholesterol for incorporation into the bile salts micelles 

or for uptaking of cholesterol by enterocytes through 

Neiman Pick C1 Like1 (NPC1L1) transporter. In 

addition, phytosterols may enhance cholesterol 

excretion back into the intestinal lumen through the 

adenosine triphosphate binding cassette G 5 

(ABCG5) and G 8 9ABCG8) transporters. Phytosterol 

could also prevent esterification of the free cholesterol 

into cholesterol esters and thus it’s assembling into 

the chylomicrons. As a result of reducing cholesterol 

absorption by phytosterols, the cholesterol synthesis 

rate increase, but the net effect is a reduction in LDLcholesterol 

levels (Jones and AbuMweis, 2009). 

Phytosterol have been shown to inhibit the uptake of 

both dietary and endogenously produced (biliary) 

cholesterol from intestinal cells. Such inhibition 

results in a decrease in serum total and LDLcholesterol 

levels. Levels of HDL cholesterol and 

triglycerides do not appear to be affected by dietary 

phytosterol consumption (AbuMweis et al., 2008). The 

email: mpraju05@gmail.com 

132

RAJU et al 

estimated daily dietary intakes of plant sterols among 

different populations range from 160 to 400 mg. 

(Berger et al., 2004). The average intakes of 

phytosterols have been estimated between 140 and 

360 mg/day in Finland and 163 mg/day in the United 

Kingdom. (Piironen et al., 2004). 

The amount of phytosterols we consume 

from the foods is not sufficient for attaining health 

benefits. Hence, incorporation of phytosterols in the 

foods consumed can benefit in reducing the plasma 

cholesterol levels and reduce the risk of coronary 

artery diseases. There is a lot of research evidence 

showing that maximum cholesterol lowering benefit 

is achieved with phytosterols at doses of 2-3 gm per 

day (Hallikainen et al., 2000, Jones et al, 2000, Maki 

et al., 2001). Phytosterols might also protect against 

certain types of cancers such as colon, breast & 

prostate. (Awad and Fink, 2000). 

The enrichment of foods such as margarines 

with phytosterols is one of the recent developments 

in functional foods to enhance the cholesterol 

lowering ability of traditional food products 

(Anonymous, 2005). The phytosterol milk products 

inhibit the uptake of cholesterol in intestinal Caco-2 

cells in vitro. Plant sterols in the milk matrix get 

stabilized using a proprietary crystal retardation and 

emulsification system (Poteau et al., 2003). 

Flavoured milk is the milk in which little 

flavour and colour has been added to make it more 

palatable. The most common flavour for flavored milk 

is chocolate, with cocoa powder as ingredient. Other 

common flavours for flavoured milk include 

strawberry, banana and coffee. Less commonly use 

flavors that are available are lime, malt, mango, 

papaya, root beer, tropical fruits and vanilla. With 

the exception of chocolate milk, many of these flavors 

are artificial. Flavoured milk should contain milk fat 

percent equal to the minimum legal requirement 

prescribed for that milk. Nowadays, chocolate 

flavoured milk, fruit flavoured milk and many more 

varieties are more popular in the market. 

Objectives of the investigation 

· To standardize and develop phytosterol 

incorporated flavoured milk. 

· To study the acceptability of the developed 

products by sensory evaluation. 

· To estimate the physico-chemical and nutritional 

properties of developed product. 

The study was planned and conducted in the 

department of Food Technology, Post Graduate and 

Research Centre, Acharya N.G. Ranga Agricultural 

University, Rajendra Nagar, Hyderabad. For the 

present investigation, toned milk, cocoa powder, 

stabilizer (CMC-Carboxy Methyl Cellulose), 

Phytosterol powder was procured from Reducol TM 

Original Powder ( Forbes medi – Tech lnc) USA based 

company. Three products (flavoured milk) namely T1, 

T2, T3 and one control were prepared and 

standardized. Phyotsterol powder was incorporated 

in test samples at various levels as shown in 

Table 1. 

Table 1. Composition of different flavoured milk preparations 

Ingredients used 

Flavoured milk 

T1 T2 T3 Control 

Toned milk 500ml 500ml 500ml 500ml 

Cocoa powder 4g 5g 6g 4g 

Sugar 35g 45g 55g 35g 

Stabilizer(CMC) 0.2g 0.3g 0.2g 0.2g 

Phytosterol powder 2g/100ml 2.5g/100ml 3g/100ml - 

Flavoured milk was prepared by mixing all 

ingredients which are mentioned in the Table 1.The 

milk (toned milk) was preheated to 60°C/1 minute 

and homogenized at 2500 psi at 55-60ºC/1 min and 

then clarified. To the warm milk, the desired amount 

of cocoa-mix, sugar and stabilizer were slowly added 

and stirred so as to dissolve them properly. The cocoa 

powder was added in the form of syrup, and the 

stabilizer in the form of solution. The mixture was 

then pasteurized at 71ºC/30 minutes, cooled rapidly 

133


to 5°C. The phytosterol enriched flavoured milk was 

prepared by incorporating the phytosterols into the 

flavoured milk. The phytosterols powder was 

incorporated into the flavoured milk at various levels 

as shown in Table 1. Phytosterol powder was added 

(2g, 2.5 and 3g /100ml), homogenized at 2000 psi at 

room temperature per 2 minutes, bottled by using 

glass bottles and kept under refrigeration (5ºC) until 

used. The received milk was homogenized to prevent 

or delay the rising of cream. It could be homogenized 

after addition of cocoa and sugar, but this increases 

sedimentation. Stabilizer was added to delay or 

prevent settling cocoa particles and also preventing 

cream rising. 

The developed products were subjected to 

organoleptic evaluation for parameters like colour/ 

appearance, flavour, taste, texture/consistency and 

overall acceptability by twelve (12) trained panel 

members from Post Graduate and Research Centre, 

Acharya N.G. Ranga Agricultural University, Rajendra 

Nagar, Hyderabad. A score card with five point 

hedonic scale was used for the purpose. Organoleptic 

scores for different parameters of sensory evaluation 

are presented in Table 2. As per the mean score 

obtained the experimental product T1 was rated higher 

than experimental products T2 and T3. The colour, 

taste, flavour and overall acceptability of the 

experimental product T1 did not differ much from the 

control. When compared to T1 (2g/100ml), phytosterol 

powder per cent was high in experimental products 

T2 (2.5g/100ml) and T3 (3g/100ml). As a result all 

the variables scored lower than the control and T1. 

The overall acceptability scores was observed in 

which T1 (4.5) scored higher followed by control (4.4) 

and lowest score was observed for T2 and T3 (3.7%). 

After product development and acceptability studies, 

it was observed that the product T1 (combination of 

toned milk, cocoa, sugar, stabilizer (500:4: 35:0.2) 

and phytosterol powder (2g/100ml)) was found to be 

superior in all aspects. Hence T1 product was selected 

for further study. 

Table 2. Mean scores obtained for control and experimental products 

S.No. 

Variables 

Products 

Control T1 T2 T3 

1 Colour/appearance 4.3±0.8 4.4±0.8 3.6±0.6 3.6±0.6 

2 Flavour 4.0±0.6 4.2±0.7 4.0±0.5 3.9±0.7 

3 Taste 4.1±0.8 4.2±0.7 4.0±0.5 3.8±0.7 

4 Texture/consistency 4.0±0.7 4.0±0.7 3.5±0.5 3.4±0.5 

5 Overall acceptability 4.4±0.6 4.5±0.6 3.7±0.4 3.7±0.4 

Note: Values are expressed as mean ± SD. 

Control: Flavoured milk with out phytosterols 

T1: Phytosterols (2g) enriched flavoured milk, 

T2: Phytosterols (2.5g) enriched flavoured milk, 

T3: Phytosterols (3g) enriched flavoured milk. 

Experimental product T1 and control 

samples were subjected to Physico- chemical and 

nutritional analysis. Physico- chemical and nutritional 

composition of the phytosterol enriched flavoured milk 

(T1) and control samples are presented in Table 3. 

134

RAJU et al 

Table 3. Physico-chemical and nutritional parameters of experimental and control products (per 100g 

sample) 

Parameter 

Samples 

T1 

Control 

Fat (g) 3.0 3.1 

SNF (g) 12.0 12.4 

Specific gravity 1.043 1.044 

Total solids (g) 14.52 15.50 

Acidity (% of lactic acid) 0.18 0.18 

pH 6.6 6.5 

Protein (g) 2.98 2.96 

Calcium (mg) 137.37 137.47 

Phosphorus (mg) 123.54 123.34 

Carbohydrates (g) 4.60 4.64 

Sugars (g) 6.32 6.37 

There was a slight variation between the 

experimental and control values of Fat, SNF, Total 

solids, Specific gravity, Acidity and pH. Protein, 

calcium, Phosphorus, carbohydrate (CHO) and sugars 

content of control and experimental samples are 

almost similar .Physico-chemical and nutritional 

parameters of the experimental product did not differ 

much from the control. The amounts of phytosterol 

we consume from the foods are not sufficient for 

attaining health benefits. So incorporation of 

phytosterols in the foods consumed can benefit in 

reducing the plasma cholesterol levels and reduce 

the risk of coronary artery diseases. Plant sterols 

have gained a prominent position in strategies to lower 

CHD (Coronary Heart Diseases) risk because of their 

serum LDL-Cholesterol lowering effects. So that the 

phytosterol enriched flavoured milk can be used as 

a good vehicle for reducing plasma cholesterol in 

hypercholesterolemic subjects. We can also use the 

incorporation of phytosterol enriched flavoured milk 

into a balanced diet represents a practical dietary 

strategy in the management of serum cholesterol 

levels. 

REFERENCES 

AbuMweis, S.S., Barake, R and Jones, P. 2008. Plant 

sterols/stanols as cholesterol lowering agents: 

a meta-analysis of randomized controlled trials. 

Food and Nutrition Research. 52-56. 

Anonymous.2005. Phytosterol esters (plant sterol and 

stanol esters). Available: http://www.ifst.org/ 

hottop29.htm. 

Awad, A.B and Fink, C.S. 2000. Phytosterols as 

anticancer dietary components: evidence and 

mechanism of action. Journal of Nutrition. 130: 

2127-2130. 

Awad, A.B., Roy, R and Fink, C.S. 2003. Betasitosterol, 

a plant sterol, induces apoptosis 

and activates key caspases in MDA-MB-231 

human breast cancer cells. Oncology reports. 

10: 497-500. 

Berger, A., Jones, P.J.H and Abumweis, S.S. 2004. 

Plant sterols: factors affecting their efficacy 

and safety as functional food ingredients. 

Lipids in Health and Disease. 3:5. 

http://www.lipidworld.com/content/3/1/5. 

135


Bouic, P.J. 2001. The role of phytosterols and 

phytosterolins in immune modulation: a review 

of the past 10 years. Current opinion in clinical 

nutrition and metabolic care. 4: 471–475. 

Hallikainen M.A., Sarkkinen, E.S and Uusitupa, M.I.J. 

2000. Plant stanol eaters affect 

serumcholesterol concentrations of 

hypercholesterolemic men and women in a 

dose dependent manner.Journal of Nutrition. 

130(4): 767-776. 

Jones, P.J.H and Abumweis, S.S. 2009. Phytosterol 

as functional food ingredients: linkages to 

cardiovascular disease and cancer. Current 

Opinion in Clinical Nutrition and Metabolic Care. 

12: 147-151. 

Jones P.J., Raeini-Sarjaz, M and Ntanios, F.Y. 2000. 

Modulation of plasma lipid levels and 

cholesterol kinetics by phytosterol versus 

phytostanol esters. Journal of Lipid Research. 

41(5): 697-705. 

Katan, M.B., Grundy, S.M., Jones, P., Law, M., 

Miettinen, T and Paoletti, R. 2003. Efficacy 

and safety of plant stanols and sterols in the 

management of blood cholesterol levels. Mayo 

Clinic Proceedings. 78: 965-978. 

Laakso, P. 2005. Analysis of sterols from various 

food matrices. European Journal of Lipid 

Science and Technology. 107: 402-410. 

Maki, K.C., Davidson, M.H and Umporowicz, D.M. 

2001. Lipid responses to plant-sterolenriched 

reduced-fat spreads incorporated into a 

National Cholesterol Education Program Step 

I diet. American Journal of Clinical Nutrition. 

74(1): 33-43. 

Phillips, K.M., Ruggio, D.M and Ashraf-Khorassani, 

M. 2005. Phytosterol composition of nuts and 

seeds commonly consumed in the United 

States. Journal of Agricultural Food Chemistry. 

53: 9436-9445. 

Piironen, V and Lampi, A.M. 2004. Occurrence and 

levels of phytosterols in foods. In: 

Phytosterols as Functional Food Components 

and Nutraceuticals. Ed. P. C. Dutta, Marcel 

Dekker, Inc., New York (USA). 1–32. 

Poteau, E.B., Monnard, I.E., Piguet-Welsch, C., 

Groux, M.J.A., Sagalowicz, L and Berger, A. 

(2003). Non-esterified plant sterols solubilized 

in low-fat milks inhibit cholesterol absorption. 

European Journal of Nutrition. 42: 154–164. 

Rozner, S and Garti, N. 2006. The activity and 

absorption relationship of cholesterol and 

phytosterols. Colloids and surfaces. A 

physicochemical and engineering aspects. 

282-435. 

Van Rensburg, S.J., Daniels, W.M., Van Zyl, J.M and 

Taljaard, J.J. 2000. A comparative study of 

the effects of cholesterol, beta-sitosterol, betasitosterol 

glucoside, dehydroe piandrosterone 

sulphate and melatonin on in vitro lipid 

peroxidation. Metabolic brain disease. 15(4): 

257-265. 

136



CORRELATION AND PATH ANALYSIS FOR YIELD AND ITS 

COMPONENTS IN RICE (Oryza Sativa L.) 

C.MANIKYA MINNIE, T.DAYAKAR REDDY and CH.SURENDER RAJU 

Department of Genetics and Plant Breeding, College of Agriculture, 

Acharya N.G.Ranga Agricultural University, Rajendranagar, Hyderabad-500030 


Path analysis measures the direct and 

indirect effects of independent variables on dependent 

variables. Knowledge of cause and effect relationship 

makes selection more effective. In the present 

investigation an attempt was made to find out the 

effects of component traits on grain yield of rice. 

The experimental material comprising of 81 

genotypes (including 3 checks) obtained from 

different sources was cultivated during kharif, 2008 

at Rice section farm, Agriculture Research Institute, 

Rajendranagar, Hyderabad. All the genotypes were 

sown separately in the nursery on raised beds. Thirty 

days old seedlings of each genotype were 

transplanted in five rows of 6 m length by adopting a 

spacing of 15 cm between plants and 15cm between 

rows in a Randomized Block Design replicated twice. 

Recommended agronomic practices and plant 

protection measures for raising a healthy crop were 

taken up during experiment. Five plants of each 

genotype in each replication selected randomly from 

central rows were used to record data. The mean 

values were considered for statistical analysis. 

Genotypic correlations in general were high 

as compared to their phenotypic correlations 

indicating strong inherent association between the 

characters which might be due to masking or 

modifying effects of environment. 

The correlation analysis indicated that grain 

yield was significantly associated with number of 

productive tillers per plant, plant height, number of 

grains per panicle and panicle length. Similar kind of 

association was reported by Satish Chandra et al. 

(2009) for number of productive tillers per plant, 

number of grains per panicle and panicle length and 

Madhavi Latha (2002) for plant height. 

The data indicated that days to 50 percent 

flowering and 1000 gram weight had no association 

with grain yield. 

The characters that showed positive and 

significant association with grain yield could be 

considered as criteria for selection for yield 

improvement as these were mutually and directly 

associated with grain yield. 

Days to 50 per cent flowering had significant 

positive association with number of grains per 

panicle. Similar result was reported by Madhavi Latha 

(2002). 

Plant height registered positive and 

significant association with number of productive 

tillers per plant, panicle length, 1000 grain weight and 

number of grains per panicle, indicating that the 

increase in panicle length and number of grains per 

panicle and 1000 grain weight can be possible with 

an increase in plant height. Similar results were also 

obtained by Janardhan et al. (2001) for number of 

productive tillers per plant, panicle length and number 

of grains per panicle and Yogameenakshi et al. (2004) 

for 1000 grain weight. 

Number of productive tillers per plant was 

positively and significantly correlated with number of 

grains per panicle and panicle length. These results 

are in consonance with the earlier findings of 

Janardhanam et al. (2001). It showed positive 

correlation with 1000 grain weight. 

Panicle length had high significant positive 

association with 1000 grain weight and number of 

grains per panicle. Similar results were also obtained 

by Yogameenakshi et al. (2004). 

email: minnie_chitturi@yahoo.co.in 

137

CORRELATION AND PATH ANALYSIS FOR YIELD AND ITS COMPONENTS 

Path coefficient analysis was used to 

compute direct and indirect effects of six characters 

on grain yield. The characters number of productive 

tillers per plant, panicle length and number of grains 

per panicle with positive direct effects on yield could 

be considered as major yield contributing characters 

in rice. These findings were in agreement with the 

reports made by Karad and Pol (2008) for number of 

productive tillers per plant and panicle length and 

Satish Chandra et al. (2009) for number of grains per 

panicle. 

On the contrary negative direct effects were 

existed by days to 50 per cent flowering, plant height 

and 1000 grain weight. Gupta et al. (1998) also 

recorded similar kind of negative direct effect of these 

traits on yield. 

The characters, panicle length, number of 

grains per panicle showed positive indirect effect 

through number of productive tillers per plant on grain 

yield. Similar results were obtained by Gupta et al. 

(1998). The panicle length exhibited positive indirect 

effect through number of productive tillers per plant 

and number of grains per panicle. Number of 

productive tillers per plant, 1000 grain weight and 

panicle length showed positive indirect effect on grain 

yield through number of grains per panicle. These 

results were in accordance with the results obtained 

by Madhavilatha (2002). 

The characters days to 50 per cent flowering, 

plant height and 1000 grain weight were not only 

having negative direct effect on grain yield but also 

had negative association with the yield contributing 

characters. This was in consonance with the results 

of Gupta et al. (1998). 

Path analysis revealed the importance of the 

characters, number of productive tillers per plant, 

panicle length and number of grains per panicle in 

influencing the grain yield. Hence, selection should 

be practiced for these characters in order to isolate 

superior plant types for improvement of grain yield. 

Table 1.Estimation of correlation coefficients between yield and yield attributing characters 

Character 

Days to 

50 % 

flowering 

Plant 

Height 

(cm) 


productive 

tillers per 

plant 

Panicle 

Length 

(cm) 


grains per 

panicle 

1000 Grain 

Weight (g) 

Grain 

Yield/ 

Plant (g) 

Days to 50% P 1.0000 0.0622 0.0434 0.0992 0.2648** -0.2933** -0.0001 

Flowering G 1.0000 0.0727 0.0109 0.0987 0.2590** -0.3024** -0.0181 

Plant Height P 1.0000 0.3113** 0.2865** 0.1525 0.1620* 0.3197** 

(cm) G 1.0000 0.5046** 0.2958 ** 0.1606* 0.1845* 0.3964** 

Number of P 1.0000 0.1010 0.2048** -0.0175 0.8501** 

productive 

tillers/plant 

G 1.0000 0.1508 0.2512** 0.0233 1.0014** 

Panicle P 1.0000 0.2383** 0.3725** 0.1047 

Length (cm) G 1.0000 0.2546** 0.4021** 0.1599* 

Number of P 1.0000 -0.3270** 0.2483** 

grains/panicle G 1.0000 -0.3425** 0.2711** 

1000 Grain 

Weight 

(g)plant 

P 1.0000 -0.0329 

G 1.0000 -0.0157 

* Significant at 5% level ** Significant at 1% level

MINNIE et al 

Table 2. Estimates of genotypic direct and indirect effects between yield and yield contributing 

characters 

Character 

Days to 50% 

Flowering 

Plant Height 

(cm) 


productive 

tillers/plant 

Panicle Length 

(cm) 


grains/panicle 

1000 Grain 

Weight (g) 

Days to 

50 % 

flowering 

Plant 

Height (cm) 


productive 

tillers per 

plant 

Panicle 

Length 

(cm) 


grains per 

panicle 

1000 

Grain 

Weight 

(g) 

Grain 

Yield/ 

Plant (g) 

-0.0418 -0.0109 0.0116 0.0067 0.0008 0.0156 -0.0181 

-0.0030 -0.1504 0.5389 0.0199 0.0005 -0.0095 0.3964** 

-0.0005 -0.0759 1.0680 0.0102 0.0008 -0.0012 1.0014** 

-0.0041 -0.0445 0.1611 0.0674 0.0008 -0.0207 0.1599* 

-0.0108 -0.0242 0.2682 0.0172 0.0031 0.0176 0.2711** 

0.0126 -0.0278 0.0249 0.0271 -0.0011 -0.0515 -0.0157 

Bold = direct effects Residual effect = -0.1520 

REFERENCES 

Gupta, J. C., Kotoch, P. C., Kaushik, R. P and 

Sharma, S. L. 1998. Cause and effect 

relationship of yield and its components under 

cold stress condition in rice (Oryza sativa L.). 

Indian Journal of Agricultural Sciences. 68 (1) 

: 13-15 

Janardhanam, V., Nadarajan, N and Jebaraj, S. 2001. 

Correlation and path analysis in rice (Oryza 

sativa L.). Madras Agricultural Journal. 88 : 

719-720 

Karad, S. R and Pol, K. M. 2008. Character 

association, genetic variability and path 

coefficient analysis in rice (Oryza sativa L.). 

International Journal of Agricultural Sciences. 

4 (2) : 663-666 

Madhavilatha, L. 2002. Studies on genetic divergence 

and isozyme analusis on rice (Oryza sativa 

L.). M.Sc. (Ag). Thesis submitted to Acharya 

N. G. Ranga Agricultural University, 

Hyderabad. 

Satish Chandra, B., Dayakar Reddy, T., Ansari, N. 

A and Sudheer Kumar, S. 2009. Correlation 

and path analysis for yield and yield 

components in rice (Oryza sativa L.). 

Agricultural Science Digest. 29 (1) : 45-47 

Yogameenakshi, P., Nadarajan, N and 

Anbumalarmathi, J. 2004. Correlation and path 

analysis on yield and drought tolerant attributes 

in rice (Oryza sativa L.) under drought stress. 

Oryza. 41 (3&4) : 68-70

THE JOURNAL OF RESEARCH ANGRAU 

DECLARATION CERTIFICATE TO BE SUBMITTED BY THE AUTHOR(S) 

Certified that the article entitled ___________________________________________________________ 

____________________________________________________________________________________ 

1. is based on my / our original research work / M.Sc / Ph.D thesis (strike off whichever is not applicable) 

2. The article has been seen by all the authors and the order of authorship is agreed. 

3. The results presented have not been published or submitted for publication else where in part or full 

under the same or other title 

4. The names of the authors are those who made a notable contribution. 

5. No authorship is given to anyone who did not make a notable contribution. 

S.No. Name/s Present address Permanent address Signature 

1. 

2. 

3. 

CERTIFICATE BY THE COMPETENT AUTHORITY 

( Professor & Head of the Department/ Principal Scientist of the station/ Associate Director of Research). 

Certified that the article ————————————————————————————————— 

—————————————————————————————————————————————— 

authored by —————————————————————————————————————————— 

——————————————————————— is fit for publication. It fulfills all the requirements for 

publication in the Journal of Research ANGRAU. 

Name : 

Signature : 

Office seal : 

Note: 

In case it is not possible to obtain the signature of a particular author for reasons beyond his/her 

reach, the reasons thereof should be explained. 

140

Statement about ownership and other particulars about 

THE JOURNAL OF RESEARCH ANGRAU 

Form IV (See Rule 8) 

1. Place of Publication : The Acharya N.G. Ranga Agricultural University, 

Rajendranagar, Hyderabad - 500 030 

2. Periodicity of Publication : Quarterly 

3. Printer’s Name : Dr. P. Chandrasekhar Rao 

Nationality : Indian 

Address : Dean of Agriculture and Editor of Journal of Research, 

ANGRAU 

Acharya N.G. Ranga Agricultural University 


4. Publisher’s Name : Dr. P. Chandrasekhar Rao 


Address : Dean of Agriculture i/c and Editor of Journal of Research, 




5. Editor’s Name : Dr. P. Chandrasekhar Rao 


Address : Dean of Agriculture and Editor of Journal of Research, 




6. Name and address of the : The Acharya N.G. Ranga Agricultural University, 

individuals who own the Rajendranagar, Hyderabad - 500 030 (A.P.) 

newspaper & partners or 

share holders holding more 

than one per cent of the 

total capital 

I, Dr. P. Chandrasekhar Rao hereby declare that the particulars given above are true to 

the best of my knowledge and belief. 

Dated : 

Signature of Publisher 

141

SUBSCRIPTION ENROLLING FORM 

I/we, herewith enclose D.D. No...................................................................... ............. 

dated..................................for Rs. ............................... drawn in favour of Managing Editor, Journal of 

Research ANGRAU, Agricultural Information & Communication Centre, ARI Campus, Acharya N.G. Ranga 

Agricultural University, Rajendranagar, Hyderabad - 500 030 as individual annual/individual life/Institutional 

annual Membership for Journal of Research ANGRAU for the calendar year (January - December) .................. 

S.No. Name of the Address for Name of the article Signature 

authors Correspondence contributed 

1. 

2. 

3. 

4. 

Note : 

The receipt of payment will be sent only if a self addressed and stamped envelope is enclosed 

along with your DD. 

142

GUIDELINES FOR THE PREPARATION OF MANUSCRIPT 

1. Title of the article should be short, specific, phrased to identify the content and indicate the nature of 

study. 

2. Names should be in capitals prefixed with initials and separated by commas. For more than two authors 

the names should be followed by ‘and’ in small letters before the end of last name. Full address of the 

place of research in small letters should be typed below the names. Present address and E-mail ID of 

the author may be given as foot note. 

3. The full length paper should have the titles ABSTRACT, MATERIALS AND METHODS, RESULTS 

AND DISCUSSION, REFERENCES-all typed in capitals and bold font - 12. The research note will 

have only one title REFERENCES. 

4. ABSTRACT: The content should include the year, purpose, methodology and salient findings of the 

experiment in brief not exceeding 200 words. It should be so framed that the reader need not refer to 

the article except for details. 

5. INTRODUCTION : Should be without title and indicate the reasons which prompted the research, 

objectives and the likely implication. The review of recent literature should be pertinent to the problem. 

The content must be brief and precise. 

6. MATERIALS AND METHODS : Should include very clearly the experimental techniques and the 

statistical methods adopted. Citation of standard work is sufficient for the well known methods. 

7. RESULTS AND DISCUSSION : Great care should be taken to highlight the important findings with 

support of the data well distinguished by statistical measures like CD, r, Z test etc. Too descriptive 

explanation for the whole data is not desirable. The treatments should be briefly expressed instead of 

abbreviations like T 1 

, T 2 

etc. The discussion should be crisp and relate to the limitations or advantages 

of the findings in comparison with the work of others. 

8. REFERENCES : Literature cited should be latest. References dating back to more than 10 years are 

not desirable. Names of authors, their spelling and year of publication should coincide both in 

the text and references. The following examples should be followed while listing the references from 

different sources. 

Journals and Bulletins 

Abdul Salam, M and Mazrooe, S.A. 2007. Water requirement of maize (Zea mays L.) as influenced by 

planting dates in Kuwait. Journal of Agrometeorology. 9 (1) : 34-41 

Hu, J., Yue, B and Vick, B.A. 2007. Integration of trap makers onto a sunflower SSR marker linkage map 

constructed from 92 recombinant inbred lines. Helia. 30 (46) :25-36. 

Books 

AOAC. 1990. Official methods of analysis. Association of official analytical chemists. 15 th Ed. Washington 

DC. USA. pp. 256 

Federer, W.T. 1993. Statistical design and analysis for intercropping experiments. Volume I: two crops. 

Springer – Verlag, Cornell University, Ithaca, New York, USA. pp. 298-305 

Thesis 

Ibrahim, F. 2007. Genetic variability for resistance to sorghum aphid (Melanaphis sacchari, Zentner) in 

sorghum. Ph.D. Thesis submitted to Acharya N.G. Ranga Agricultural University, Hyderabad. 

143

Seminars / Symposia / Workshops 

Naveen Kumar, P.G and Shaik Mohammad 2007. Farming Systems approach – A way towards organic 

farming. Paper presented at the National symposium on integrated farming systems and its role 

towards livelihood improvement. Jaipur, 26 – 28 October 2007. pp.43-46 

Proceedings of Seminars / Symposia 

Bind, M and Howden, M. 2004. Challenges and opportunities for cropping systems in a changing climate. 

Proceedings of International crop science congress. Brisbane –Australia. 26 September – 1 October 

2004. pp. 52-54 

(www.cropscience 2004.com 03-11-2004) 

Tables and Graphs : The data in tables should not be duplicated in graphs and vice versa. Mean data for 

main treatment effects should be presented with appropriate SE± and CD values wherever necessary. 

The 2 or 3 way tables should be furnished only if the results are consistent over years and are 

distinguished to have consideration of significant practical value. SE± and CD values however, 

should be furnished in the tables for all interactions and should be explained in the results and 

discussion. The treatments should be mentioned atleast in short forms if they are lengthy, but not 

abbreviated as T 1 

, T 2 

and T 3 

etc. The weights and measures should be given in the metric system 

following the latest units eg. kg ha -1 , kg ha –1 cm, mg g -1 , ds m -1 , g m -3 , C mol kg -1 etc. 

Typing : 

Note : 

The article should be typed in 12 pt font on A 4 

size paper leaving a margin of 5 cm on all sides. 

There should be a single line space between the rows in abstract and double line in rest. Verify 

the manuscript thoroughly for errors before submitting it for publication. 

Latest issue of the Journal may be consulted. Further details can be obtained from the book 

“Editors style Manual, edn 4. American Institute of Biological Sciences, Washington DC”. 

URL : http://www.angrau.ac.in/Publications.aspx 

ESSENTIAL REQUIREMENTS FOR CONSIDERATION OF PUBLICATION OF ARTICLES 

1. Research of not less than 2 years and of high standard will be considered as full length paper. 

If necessary, it will be considered for short communication. 

2. Research of one year should be submitted in the style and format of short communication. 

3. The total number of pages should not exceed 10 for full paper and 5 pages for short communication 

including tables and figures. The figures should be legible. 

4. Old research which terminated 5 years before the date of submission will not be considered. 

5. All the authors should subscribe for the Journal 

6. The manuscript should be submitted in triplicate as per the guidelines of the Journal to The Dean of 

Post Graduate Studies and Editor, The Journal of Research ANGRAU, Administrative Office, 

Rajendranagar, Hyderabad – 500 030. 

7. The manuscript should accompany the declaration certificate and subscription enrolment form. 

8. The authors should accept the editorial / referees comments until the quality of the paper is 

improved. 

9. The revised manuscript should be submitted in duplicate along with a compact disk. 

REVIEW PROCESS 

The articles will be initially screened by the editors. It will be sent to an expert for peer review 

only if it contains adequate original information and is prepared as per the guidelines. The author, 

then, may also be asked to revise it if the expert desires. After getting the article suitably revised and 

edited, it will be placed before the editor for a final decision. The accepted article will be finally 

checked for language and grammar by the English editor before being sent to the press. The decision 

however to publish the paper lies with the editor. Any article which is not able to meet the expected 

standard or is not prepared in conformity with guidelines will be rejected without assigning any 

reason. 

144

ESSENTIAL REQUIREMENTS 

FOR CONSIDERATION OF PUBLICATION OF ARTICLES 

1. Research of not less than 2 years and of high standard will be considered as full length paper. If 

necessary, it will be considered for short communication. 

2. Research of one year should be submitted in the style and format of short communication. 

3. The total number of pages should not exceed 10 for full paper and 5 pages for short communication 

including tables and figures. The figures should be legible. 

4. Previous research which terminated 5 years before the date of submission will not be considered. 

5. All the authors should subscribe for the Journal 

6. The manuscript should be submitted in duplicate as per the guidelines of the Journal to The Editor, the 

Journal of Research of Research ANGRAU, O/o Principal Agricultural Information Officer, AI&CC and 

ANGRAU Press, ARI Campus, Rajendranagar, Hyderabad. 

7. The manuscript should accompany the declaration certificate and subscription enrolment form. 

8. The authors should accept the editorial / references comments until the quality of the article is improved. 

9. The revised manuscript should be submitted in duplicate along with a compact disk. 

10. DD may be drawn in favour of “Managing Editor, Journal of Research, ANGRAU” Payable at Hyderabad. 

SUBSCRIPTION TARIFF 

ANNUAL 

Individual : Rs. 300/- author 

Institution : Rs. 1200/- 

LIFE 

Individual (till retirement) : Rs. 1200/- 

Reprints Charges : Rs. 100/- per page 

1. Publications : The Editor - Journal of Research ANGRAU O/o Principal Agricultural Information 

Officer, AI&CC and ANGRAU Press, ARI Campus, Rajendranagar, Hyderabad. 

2. Publications : The DD should be mailed to the Managing Editor - Journal of Research, ANGRAU 

- Press Agricultural Research Institute, Rajendranagar, Hyderabad - 500 030, A.P. 

least in short forms if they are lengthy, but not abbreviated as T 1 

, T 2 

and T 3 

etc. The weights and 

measures should be given in the metric system following the latest units eg. kg ha -1, kg ha -1 cm, mg 

g -1 , ds m -1 , g m -3 , C mol kg -1 etc. 

Typing : The article should be typed in 12pt font on A 4 

size paper leaving a margin of 10 cm on all 

sides. There should be a single line space between the rows in abstract and double line in rest. 

Note : Latest issue of the Journal may be consulted. Further details can be obtained from the book 

“Editors style Manual, edn 4. American Institute of Biological Sciences, Washington DC”. 

URL : http://www.angrau.ac.in/Publications.aspx 

145

The Journal of Research ANGRAU

Create successful ePaper yourself

Delete template?

Save as template?