Economics of lentil cultivation in Nadia district of West Bengal

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1 Journal Crop and Weed, ():38-42(205) Economics of lentil cultivation in Nadia district of West Bengal S. CHATTERJEE, J. RAY, R. NATH, S. K. GUNRI, 2 3 T. BISWAS AND A. SARKER 2 Dept. of Ag. Economics, Dept. of Agronomy, Dept. of Ag. Chemistry and Soil Science Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, 74252, Nadia, West Bengal 3 ICARDA Sou Asia- China Regional Program, New Delhi Received: , Revised: , Accepted: ABSTRACT The diversification of cereal based production systems, adding legumes to e mix, is a strategy at boost nutritional and food security, improve incomes and livelihoods in rural communities of West Bengal. Lentil is one of e most nutritious cool season pulse crop in West Bengal. Lentil productivity in West Bengal is higher (762 kg ha ) compared to all India average (697 kg ha ). The economic analysis of lentil production along wi identification of constraints in its way has been studied. The study was based on e data for e year Simple tabular analysis was carried out for calculating inputs and materials used, cost of cultivation, gross return, net return and benefit - cost ratio. Crop performance was studied rough composite index score. The Garret s ranking technique was used to identify and prioritize e constraints of lentil production. Results revealed at average cost of production was 22479/- ha and average gross and net return were in e tune of 42640/- and 206/- ha and benefit cost ratio was 2.00 respectively. The main constraints were non availability of quality lentil seeds in time, lack of soil testing facilities, high price of seeds, lack of processing units and storage facilities disease and pest incidence and lack of credit facilities etc. Keywords: Constraints, cost of cultivation, crop performance indices, lentil, return The green revolution in India provided e driving force to our country to scale up agricultural productivity after seventies and eighties. It has made India self sufficient in food production as well as brought rural prosperity. Despite of achievements in e overall productivity of crop sector, it is argued at malnutrition still exists as a predominant vice in e country because of e excessive rate of population grow (Chatterjee et al., 204). In is context, sustainable agricultural development catering to e nutrition needs of e country is of prime necessity. While studying on e role of pulse production in India in e light of food and nutritional security, Shalendra et al. (203) came into conclusion at in spite of impressive grow of Indian agriculture after Green Revolution, e challenge of food and nutritional security still exists due to imbalanced grow in agriculture which was biased towards wheat and rice production. In is context, Vishwaji et al. (204) has also reported at in a populous developing country like India, production of pulses can play a pivotal role in nutritional security of e country as it has still been treated as poor man s meat wi comparatively cheaper sources of protein in balancing human diet. It has been examined at various levels of field crop researches at e production of pulses in e recent decade has increased but not in a pace wi e increase in population. To add furer, it has also been pointed out at e decline in pulse soumitra.soum2323@gmail.com consumption (5 MT in to 6 MT in 202) leads to malnutrition which would be abolished by a well built institutional and policy support, wider adoption of HYV pulses, and adoption of low cost technologies. In is context, Singh et al. (203) has also commented at farmers should be trained and aware properly about improved production technology for e overall productivity enhancement in pulses as well as nutritional security. Keeping e above views in mind, e present study attempts to analyze and work out various input used in lentil cultivation, eir break-up cost components and expected returns across six major villages in Nadia district, West Bengal. The auor has also tried to measure e composite crop performance scoring amongst lentil growers under different villages and to identify and prioritize e major constraints faced in lentil cultivation in is region. MATERIAL AND METHODS Selection of study area The study is based on e data for e year A sample of 0 households has been selected by multistage random sampling from 6 selected villages of 3 blocks making e total sample of 60 households (2 villages each from block). Simple tabulation meod was carried out for analyzing e materials and inputs used in lentil cultivation, its cost of cultivation, gross return, net return and benefit cost ratio of e sample lentil growers. 38

2 Chatterjee et al. Cost concepts The present study has followed e concept of costs as proposed by e Commission for Agricultural Costs and Prices (CACP), Ministry of Agriculture, Govt. of India. Here only e components of paid out cost plus imputed value of family labour have been considered for convenience in e research study. The various cost components used here are as follows: Cost A : It covers all actual expenses of cash and kind incurred in production of lentil by e owner. It includes various components like: i) Value of hired human labour (bo casual and attached labour) ii) Value of hired bullock labour iii) Value of owned bullock labour iv) Value of owned machinery labour v) Hired machinery charges vi) Value of seed (bo farm produced and purchased) vii) Value of insecticides and pesticides viii) Value of manure (owned and purchased) ix) Value of inorganic fertilizer x) Depreciation on implements and farm buildings xi) Irrigation charges xii) Land revenue, cesses and oer taxes xiii) Interest on working capital xiv) Miscellaneous expenses (Artisans etc.) Cost A : Cost A + Rent paid for leased-in-land 2 But, Cost A = Cost A (as, ere is no leased- in- land 2 for e sample farmers under e study) Final cost = Cost A + FL Where, FL signifies e imputed value of family labour at has been taken in consideration for marginal and small farming community who has no capacity to hire labour from outside. So, cost A + FL includes e realistic cost and at has been considered as e final cost for is research study. However, cost B, B2 includes rental value of own land and operational cost of land wi interest on own fixed capital, which has not been considered realistic for is study. Net return= Gross return- Cost of cultivation Benefit- cost analysis For measuring e production efficiency of lentil amongst e lentil cultivators, benefit cost ratio worked out as follows Benefit cost ratio = Gross return from sale of output Total cost of input used Meodology for performance indices The criterion for judging e farmer-wise performance index scoring on lentil cultivation has been worked out by aggregating four indicators wi due weight to individual indicator. The process is better known as computing a composite index. These indicators are: (a) total operational size of e holding, (b) area under lentil cultivation, (c) level of lentil productivity and (d) return per rupee of investment. The procedure for computing a composite index follows two steps: Step I: Transformation of e original variable to a new one. Let X denotes e value of i indicator for j village (#). Then we can define a new variable Y such at Y = {X Min (X )}/{Max (X ) Min (X )}, () where, Max (X ) and Min (X ) denote e maximum and minimum values of i indicator for j village. Value of e newly transformed variable (Y ) varies from zero to one. This step is followed for oer indicators (m) of e j village for lentil. Step II: Aggregation of e newly transformed indicators for e j village as: Y = w Y (2) j# i where, w (0<w < and w = ) are arbitrary weights. i i i The calculation of weight is done as follows: w i=k/(var (Y ), where K={ (/(Var(Y )}..(3) Each indicator has been assigned to a weighted transformed indicator where a value K has been assigned in such a manner as e inverse of e sum of inversed variance of e original indicator. Finally e weight has been assigned as inverse variance of e original variable (Y ) multiplied by K. The entire meodology of calculating weighted composite scoring has been followed from e work of Ludovic et. al. (984). Garrett s ranking technique Garrett et al. (969) have proposed a ranking technique meod and at has been furer used by Rangaswamy et al. (2007) to prioritize e major constraints faced by e co-operative and private dairy plants in Tamil Nadu. However, e same technique was used in is study to prioritize e major constraints and problems faced by e lentil growers. According to is technique, e respondents were asked to assign ranks to different problems using e following formula. 39

3 Economics of lentil cultivation. Table : Frequency distribution of sample farmers raising lentil in Nadia district of West Bengal Sl. No. Selected villages in Nadia district No. of farmers. Panpur 0 2. ChapraDhantala 0 3. Mollapara 0 4. Bayre Sonakhali 0 5. Hemayetpur 0 6. Rautari 0 Total 60 Table 2: Materials and inputs used per hectare in lentil cultivation in Nadia district of West Bengal Name of e villages Components Mollapara Rautari Bayer Panpur Chapra Hemayetpur Pooled Sonakhali Dhantala Seed (kg) Fertilizer (kg nutrient) Organic manure (q) Bullock labour(pair hour) Human labour (man hour) Machine hour Table 3: Mean cost of cultivation per hectare for selected lentil growers in Nadia district of West Bengal Components Sample lentil growers of e selected villages Cost A (Materials Mollapara Rautari Bayer Panpur Chapra Hemayetpur Average and input cost) Sonakhali Dhantala Seed Fertilizer Organic manure Hired machine labour Owned machine labour Hired bullock labour Owned bullock labour Hired human labour Irrigation charges Insecticides Miscellaneous Interest on working Cost A Family labour Final Cost= Cost A + family labour Table 4: Economics of lentil cultivation in Nadia district of West Bengal Sl. No. Lentil growers Mean gross Mean cost of Surplus over Mean benefit- return (Rs. ha ) cultivation (Rs. ha ) cost (Rs. ha ) cost ratio Panpur Chapra Dhantala Mollapara Bayre Sonakhali Hemayetpur Rautari Pooled

4 Chatterjee et al. Percent position = Where R ij = Rank given for i problem by j individual, N j = Number of problems ranked by e j individual The per cent position of each rank has been converted into scores by referring table given by Garrett and Woodwor (969). Then for each problem, e scores of individual respondents were added and divided by e total number of respondents. The mean scores for all e problems were arranged in descending order and us rank were assigned to e problems faced by e respondents. RESULTS AND DISCUSSION [00 (R 0.5)] ij N j The frequency distribution of sample farmers under cultivation of lentil across e selected villages in Nadia district as well as per hectare materials and inputs used by e farm households have been illustrated in table and 2 respectively. It has observed from e table 2 at, amongst all e locations, lentil growers of Chapra Dhantala exhibits highest seed and fertilizer use (44.50 kg ha and kg-nutrients ha respectively). Break-up cost components of all paid out cost including imputed value of family labour in lentil cultivation across e selected villages in Nadia district is viewed in table 3. The average cost of cultivation for one hectare of lentil turns to be /-, however, it varies across e sample villages. The table shows at lentil growers of Chapra Dhantala village incurred maximum cost in all sorts of input use like seed, fertilizer, organic manure, hired machineries, hired bullock labour, plant protection measures and family labour use. Bayer Sonakhali has exhibited highest cost A as more cost incurred in transportation and communication (Rs 3663/-) of lentil to e market. This particular village too has exerted more cost incurred for family labour use as highest man hour of labour consumption per hectare (804.0) was recorded in is village results in highest final cost incurred for lentil cultivation. Table 4, represents e economics of lentil cultivation across six selected villages of Nadia district, West Bengal where e average gross return and net return from one hectare of lentil cultivation is 42640/- and 2039/- respectively. Farmers belong to Chapra Dhantala has exhibited e highest gross return (Rs 63004/-) as well as net return (Rs 37003/-) followed by Mollapara (Rs /- and Rs 3506/- respectively). Bayer Sonakhali and Panpur has shown miserable performances wi a moderately low level of economic return (.08 and.29 respectively). Average economic return was found to be 2.00 in e entire location under study where it features moderately high in Mollapara and Chapra Dhantala (2.69 and 2.52 respectively). Composite crop performance scoring has been performed for each lentil growers taken under consideration. The criterion based on such scoring are e operational size of holding, area under lentil cultivation, productivity of lentil and economic return per rupee of investment. Bayre Sonakhali and Rautari have shown e highest average composite scores (0.56), ensures at ere are much scope to enhance e acreage as well as productivity level of lentil in ese region followed by Panpur, Chapra Dhantala and Mollapara (0.49 each) and somewhat less (0.46) in Hemayetpur. The overall average composite score was found to be 0.5 (Table 5). Table 5: Village-wise composite crop performance scoring of lentil growers in Nadia district, West Bengal Villages Average composite score Panpur 0.49 Chapra Dhantala 0.49 Mollapara 0.49 Bayer Sonakhali 0.56 Hemayetpur 0.46 Rautari 0.56 Pooled 0.5 Regarding problems and constraints faced by e lentil growers, six major constraints over e location was identified and prioritized. It is e non-availability of quality lentil seed material which ranked first (mean score 68.7) followed by high price level at makes e barrier for e poor farmer to use quality seed material for lentil cultivation (Table 6). Also lack of soil testing facilities in time has been identified as one of e major constraints in lentil cultivation over e study locations. Lack of suitable plant protection measures and adequate credit facilities have become also e constraints and problems identified in ese locations regarding lentil cultivation. 4

5 Economics of lentil cultivation. Table 6: Garrett s ranking for various constraints faced by e lentil growers in Nadia district of West Bengal Mean Rank by Constraints score order of merit Non availability of quality lentil seeds in time 68.7 I High price of seeds II Lack of soil testing facilities in time III Lack of processing units 40.4 IV High pest and disease incidence at flowering time 3.46 V Lack of credit facilities for e lentil farmers 26.8 VI The study reveals at cultivation of lentil is e most labour-intensive. Utilization of family labour is markedly higher in comparison to at of hired labour and gainful utilization of family labour can be made possible rough e cultivation of is crop. Surpluses and benefit- cost ratios are observed to be remunerative and hence encouraging to lentil growers. Average crop performance score values ensure at ere is much scope to enhance e acreage as well as productivity level of lentil in ese regions. However, e crisis of good seed material for e farmers has become e prime barrier for e productivity gaining of lentil in Nadia district. Location specific intense research and extension is very much needed to guide e lentil growers for eir overall development. REFERENCES Chatterjee, S., Na, R., Ray, J., Ray, M., Gunri, S.K. and Bandopadhyay, P Analysis of pulse production in major states of India. J. Food Legumes, 27: Anonymous FAOSTAT - Statistical Database, 202, accessed on Garett, H.E. and Woodwor, R.S Statistics in Psychology and Education. Bombay, Vakils, Feffer and Simons Pvt. Ltd., pp Ludovic, L., Alain, M. and Kenne, M. W Multivariate Descriptive Statistical Analysis, pp. 89. Rangaswamy, N. and Dhaka, J.P Constraints faced by co-operative dairy plants in Tamil Nadu-a comparative analysis. Indian J. Dairy Sci., 60: Shalendra, G., Sharma, K.C., Purushottam and Patil, S.M Role of pulses in e food and nutritional security in India. J. Food Legumes, 26: Singh, S.K., Riyajuddeen, O., Vinay, S. and Yadav, S Area expansion under improved varieties of lentil rough participatory seed production programme in Ballia district of Uttar Pradesh. J. Food Legumes, 26:5-9. Vishwaji, K.P., Dhekale, B.S., Sahu, P.K., Mishra, P. and Noman, M.D Time series modeling and forecasting of pulses production in India. J. Crop Weed, 0: