Trends of Non-Foodgrains Cultivation in India: A State Level Analysis

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1 Trends of Non-Foodgrains Cultivation in India: A State Level Analysis Samir Show Research Scholar, Department of Economics, Vidyasagar University. Received: June 01, 2018 Accepted: July 26, 2018 ABSTRACT The proportion of area under non-foodgrains increased in almost all the states of India during to , Percentage of area under oilseeds registered an increase in states like Madhya Maharashtra, and West Bengal during this period. Percentage of area under cotton witnessed an increase in states like Andhra Gujarat, Haryana, Karnataka, Maharashtra and Orissa during this period that under jute decreased in almost all the states during the study period. The variables considered explain the variations in percentage of non-foodgrains area across the states are road density, percentage of urban population, poverty ratio, average size of holdings and rainfall. Keywords: Non-foodgrains, urban population, poverty ratio, size of holdings and population density. 1. Introduction A shift in area broadly from foodgrain crops to non-foodgrain crops, especially after the mid-sixties took place in states of India (Pandey and Sharma, 1996; Vyas, 1996). During the decade of 1980s, non-food grain crops like potatoes, oilseeds and sugarcane experienced quite high rate of growth in their areas (Chand et al., 2008). With India achieving self-sufficiency in foodgrains production by late 1970s, there was a turnaround in policy towards diversification as a result of which the area under cereal crops started declining after From early1990s, diversification towards horticulture received a real boost (Chand and Chouhan, 2002; De, 2003; Sharma, 2005; Kumar et al., 2012; Mandal and Bezbaruah, 2013). Assured irrigation helped the farmers avoid uncertainty of the output and thus reduce the production risk which was associated with high value crops. So, greater availability of irrigation induced the farmers to allocate larger areas to high value crops which were less risky under irrigation (Kumar et al., 2012). However, there are some studies which have found irrigation to exert a non-significant or negative influence on crop diversification (Joshi et al., 2007; Rao et al. ). A shift from cereal-based system to high value agriculture requires capital to acquire assets, new technology and infrastructure. Results of the existing studies suggest that as intensity of credit from institutional sources increases diversification in terms of the Simpson s Index also increases (Jha et al, 2009).The negative effect is also plausible because of the fact that many non-foodgrain crops which are also more remunerative are selfliquidating in nature and no institutional loans are easily available for this purpose. Jha, et al. (2009) examined in India the pattern of agricultural diversification measured by increase in percent of non-food crops, significant changes occurred at the marginal level in the pattern of agricultural diversification. The study labelled the usual notion of crop diversification as a risk management practice. Dasgupta and Bhaumik (2014) observed that crop diversification in West Bengal took place largely in favour of boro rice, potatos and oilseeds. The majority of small and marginal farmers using benefits of modern technology, subsidised fertilisers, improved variety of seeds, and most of all availability of water through minor irrigation schemes played a leading role in diversification of agriculture in the state. It appears from study that agricultural growth in West Bengal in general varied positively with the level of crop diversification. Thus a lot of literature has developed on crop diversification in India across states but there is hardly any literature on trends in non-foodgrains production across the states, particularly the factors that influences the varying percentages of foodgrians area among them. The present note seeks to remedy some of the deficiencies in the literature on the theme. The rest of the paper is organized as follows. Second 2 presents the objectives of the study and Section 3 the databse and methodology. Section 4 is concerned with the results and discussion. Section 5 summarises the whole discussion and makes conclusion. 2. Objectives of the study The objectives of the study are as follows. i) To examine the trends and nature of change in non-foodgrains area across the states of India, ii) To analyze the factors those are responsible for the variation in percentage of area under non-foodgrains across the states. 922y IJRAR- International Journal of Research and Analytical Reviews Research Paper

2 [VOLUME 5 I ISSUE 3 I JULY SEPT 2018] e ISSN , Print ISSN Cosmos Impact Factor Database and Methodology The study is based on secondary data. Secondary data relating to non-foodgrains have been collected from different sources, namely Census of India, Economic Census, Data from Centre for Monitoring Indian Economy (CMIE), Statistical Abstract, Reserve Bank of India Bulletin, Ministry of Agriculture Government of India. To examine the factor relationship regression analysis is used. The functional form of regression used is Y = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + β 5 X 5 where, Y is the dependent variable and X 1, X 2, X 3... Xn are the independent variables. Here the dependent variable is percentage of area under non-foodgrains (Y) in states of India. The independent variables are percentage of urban population(x 1), poverty ratio (X 2), average size of holdings (X 3), road density (X 4) and rainfall (X 5) 4. Results and Discussion This section is devoted to the examination of the changes in percentage of area under nonfoodgrains in states of India during to For the purpose of analysis, first of all, changes in proportion of area under non-foodgrains to total gross cropped area are considered. The proportion of area under non-foodgrains increased in almost all the states during to In India as a whole it was per cent in and per cent in In the states of Punjab, however, it decreased during this period. In the percentage of area under non-foodgrains was highest in Kerala (79.56) followed by Goa (62.37), Gujarat (53.34), Meghalaya (44.54), Tripura (35.83), Karnataka (33.89), Andhra Pradesh (32.35), Tamil Nadu (31.68), Haryana (30.61) Assam (28.59), Sikkim (28.72), Maharashtra (27.31), Rajasthan (24.98), Arunachal Pradesh (23.81), Punjab (23.33), West Bengal (21.79), Manipur (19.40) anad lowest in Bihar (1.34). In the percentage of area under non-foodgrains was also highest in Kerala (87.92) followed by Gujarat (70.79), Goa (59.82), Meghalaya (51.19), Tamil Nadu (44.76), Rajasthan (40.86), Andhra Pradesh (43.35), Madhya Pradesh (39.70) and lowest in Bihar (10.94). In also the percentage of area under non-foodgrains was highest in Kerala (91.70) followed by Goa (66.00), Gujarat (63.08)), Meghalaya (60.77), Mizoram (55.62), Sikkim (49.87), Tamil Nadu (44.83), Andhra Pradesh (44.67), Maharashtra (43.78), Tripura (43.33) and lowest in Bihar (13.32) and also in the percentage of area under non-foodgrains was highest in Kerala (93.39) followed by, Gujarat (72.39), Goa (68.04), Mizoram (67.72), Meghalaya (59.27), Sikkim (52.43), Maharashtra (51.22), Tamil Nadu (40.98), Andhra Pradesh (48.46) and lowest in Bihar (12.35). Percentages of area under non-foodgrains registered an increase in states like Andhra Arunachal Assam, Bihar, Goa, Gujarat, Himachal Jammu and Kashmir, Kerala, Madhya Maharashtra, Manipur, Meghalaya, Nagaland, Orissa, Rajasthan, Sikkim, Tamil Nadu, Tripura, Uttar and West Bengal during to Punjab was a special state where percentage of area under non-foodgrains rapidly declined during to Percentages of area under nonfoodgrains registered decrease in states like Punjab and Karnataka during to Mizoram recorded the highest change in non-foodgrains area (40.54 percentage point), followed by Maharashtra (23.91percentage point), Sikkim (23.71 percentage point), Rajasthan (22.06 percentage point), Nagaland (19.83 percentage point), Madhya Pradesh (19.18 percentage point), Gujarat (19.05 percentage point), Andhra Pradesh (16.01 percentage point), West Bengal (14.97 percentage point), Meghalaya (14.73 percentage point), Kerala (12.83 percentage point), Bihar (11.01 percentage point), Orissa (9.4 percentage point), Tamil Nadu (9.3 percentage point), Himachal Pradesh (9.2 percentage point) Uttar Pradesh (8.79 percentage point), Manipur (6.68 percentage point), Goa (5.67 percentage point), Jammu and Kashmir (5.43percentage point), Assam (5.23 percentage point) lowest in Punjab ( 7.14 percentage point declined) (Table 1). Trends of percentage of area under non-foodgrains during and are shown in Figure 1. Figure 2 presents the trends of percentages of area under oilseeds and sugarcane in Table 1 Percentage of Area under Non-Foodgrains by State in India, to States/ Union Territories Research Paper Change in to Andhra Pradesh Arunachal Pradesh Assam IJRAR- International Journal of Research and Analytical Reviews 923y

3 Bihar Goa Gujarat Haryana Himachal Pradesh Jammu and Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Manipur Meghalaya Mizoram Nagaland Orissa Punjab Rajasthan Sikkim Tamil Nadu Tripura Uttar Pradesh West Bengal India Source: Handbook of Statistic on Indian States Two states, namely Goa and Kerala belonged to the outstanding category of percentage of nonfoodgrains area in , and in they retained their position. Three states (Meghalaya, Mizoram and Gujarat) were added to this category in Meghalaya, Mizoram and Gujarat got promoted to the outstanding category of percentage of non-foodgrains area in Punjab state got demoted to the low category of percentage of non-foodgrains area in Manipur and Uttar Pradesh states got promoted to the Moderate category of percentage of non-foodgrains area in Orissa state got promoted to the Moderate category of percentage of non-foodgrains area in but in it got demoted to the low category. Andhra Maharashtra, Sikkim and Rajasthan got promoted to the very high category of percentage of non-foodgrains area in Jammu and Kashmir and Bihar belonged to the very low category of percentage of non-foodgrains area in , and in they retained their position. Madhya Tamil Nadu and West Bengal states got promoted to the high category of percentage of non-foodgrains area in Similarly, Karnataka state got promoted to the high category of percentage of non-foodgrains area in but in it got demoted to the moderate category (Table 2) Table 2 Distribution of States by Percentage of Non-foodgrains Area, to Pe rce ntage o f Range o f State s Na me no n- Pe rce ntage food grai ns O f non - a re a food grai ns Catego rie s a re a Ve ry Lo w Les s tha n 1 1 Bihar, Himachal Pradesh Bihar Low Mod erate Jammu and Kashmir, Madhya Uttar Nagaland, Odisha, Manipur (Total = 6) Andhra Arunachal Assam, West Bengal, Tamil Nadu, Himachal Jammu and Kashmir, Tripura, Manipur, Punjab, Uttar Pradesh (Total = 6) Arunachal Assam, Haryana, Mizoram, Nagaland, Odisha, Sikkim, Bihar, Himachal Jammu and Kashmir, Odisha, Punjab, (Total = 5) Arunachal Assam, Haryana, Karnataka, Manipur, Uttar Maharashtra, Mizoram, Punjab, Sikkim, Rajasthan, Karnataka, Haryana (Total = 12) 924y IJRAR- International Journal of Research and Analytical Reviews Research Paper

4 [VOLUME 5 I ISSUE 3 I JULY SEPT 2018] e ISSN , Print ISSN Cosmos Impact Factor West Bengal (Total = 8) Pradesh (Total = 6) Hi gh Ve ry High Tripura, Meghalaya, (Total = 2) Andhra Karnataka, Madhya Rajasthan, Maharashtra, Tamil Nadu (Total = 6) Madhya Nagaland, Tamil Nadu, Tripura, West Bengal (Total = 5) Gujarat, Meghalaya And h ra Prades h, Ma ha rash t ra, Si kki m, Rajas th an (Total = 4) Ou ts tandi ng 5 9 a nd abo ve Goa, Kerala Goa, Gujarat, Kerala Meghalaya, Mizoram, Goa, Gujarat, Kerala (Total = 5) Figure 1 Trends of the Percentage of Area under Non-foodrgains by States of India, to Figure 2 Trends of the Percentage of Area under Oilseeds and Sugarcane by States of India in Research Paper IJRAR- International Journal of Research and Analytical Reviews 925y

5 Percentage of area under oilseeds registered an increase in states like Arunachal Goa, Madhya Maharashtra, Manipur, Meghalaya, Nagaland and West Bengal during to Madhya Pradesh is a special state where percentage of area under oilseeds witnessed robust increase during to (16.65 % GCA under oilseeds in and 29.68% in ). Percentages of area under oilseeds registered decrease in states like Andhra Assam, Bihar, Gujarat, Haryana, Himachal Jammu and Kashmir, Karnataka, Kerala, Mizoram, Orissa, Punjab, Sikkim, Tamil Nadu, Tripura and Uttar Pradesh during to In the percentage of area under oilseeds is highest in Gujarat (25.66) followed by Andhra Pradesh (23.65), Karnataka (21.68), Tamil Nadu(17.32), Madhya Pradesh (16.65), Rajasthan (15.89) Maharashtra(13.02), Orissa(11.89), Sikkim (9.06), Arunachal Pradesh (8.58), Assam (8.40), Haryana (8.22), Mizoram (7.41), Nagaland (7.06), Uttar Pradesh (6.63), Jammu and Kashmir (6.41), West Bengal (5.93), Meghalaya (3.67), Tripura (3.11), Bihar (2.31), Himachal Pradesh (1.84) and Punjab (1.54). In the percentage of area under oilseeds is highest in Madhya Pradesh (29.68) followed by Gujarat (19.93), Rajasthan(18.39), Maharashtra(18.07), Andhra Pradesh (13.94), Nagaland (12.99), Arunachal Pradesh (11.68) Karnataka (11.21), Manipur (9.58), West Bengal (8.01) and lowest in Kerala (0.03). Percentages of area under cotton registered an increase in states like Andhra Gujarat, Haryana, Karnataka, Maharashtra and Orissa during to Gujarat is a special state where percentage of area under cotton witnessed robust increase during to (7.71 % GCA under oilseeds in and 21.71% in ). Percentages of area under cotton registered decrease in states like Madhya Kerala, Meghalaya, Mizoram, Punjab, Rajasthan, Tamil Nadu and Tripura during to In the percentage of area under cotton is highest in Maharashtra (12.49) followed by Punjab(9.35), Gujarat (8.71), Haryana (8.28), Karnataka (5.29), Andhra Pradesh (4.97), Tamil Nadu (3.61), Meghalaya(3.08), Madhya Pradesh (2.55) and Rajasthan (2.35). In the percentage of area under cotton is highest in Gujarat (21.71) followed by Maharashtra (17.85), Andhra Pradesh (10.68), Hariyana (9.91), Karnataka (7.14), Punjab (5.35) Tamil Nadu (3.12) and Orissa (2.45) Jute and allied fibers constitute the second most important natural fibers next to cotton. The jute cultivation is a significant source of income in rural economy. This cultivation provided employment opportunity to large number of people in different regions of rural areas in the country. The worldwide awareness on environment is the reason for the opportunities of Jute, due to environment friendly characteristics. Jute, a natural fiber that can be used in many different areas, supplementing or replacing synthetics, has been receiving increasing attention from the industry. Jute is an annually renewable energy source with high a biomass production per unit land area. It is biodegradable and its products can be easily disposed without causing environmental hazards. The roots of jute plants play a vital role in increasing the fertility of the soil. Jute plants have carbon dioxide assimilation rate and it clean the air by consuming large quantities of carbon dioxide. (International Jute Study Group, 2011). The proportion of area under jute decreased in almost all the states during to , in India it was 0.55 per cent in to 0.44 per cent in In the percentage of area under jute cultivation is highest in West Bengal (5.88) followed by Meghalaya (4.08), Assam (2.70) Tripura (1.90), Bihar (1.57), Orissa (0.70) Andhra Pradesh (0.69) and Karnataka (0.13). Percentage of area under jute cultivation in the states except Nagaland and West Bengal decreased during to The share of jute area in gross cropped area increased in Nagaland (0.9 % in to in ) and West Bengal (5.88% in to 5.95% in ) states during this period. Rank of Nagaland state improved much during this respect compared to other states. In the percentage of area under jute cultivation is highest in West Bengal (5.95) followed by Meghalaya (3.24), Assam (1.84), Bihar (1.45), Nagaland(0.98).Tripura(0.27) Orissa (0.25) Arunachal Pradesh (0.10) Andhra Pradesh(0.09) and Karnataka (0.01). Percentages of area under sugarcane registered an increase in states like Andhra Gujarat, Karnataka, Madhya Maharashtra, Manipur, Mizoram, Tamil Nadu, Uttar Pradesh and West Bengal during to Nagaland is a state where percentage of area under sugarcane rapidly declined during the study period. Percentages of area under sugarcane registered decrease in states like Assam, Goa, Haryana, Nagaland, Orissa, Punjab and Rajasthan (Table 3). Table 3 Percentage of Area under Major Non-foodgrains in States of India, to States Oilseed Cotton Sugarcane Jute y IJRAR- International Journal of Research and Analytical Reviews Research Paper Andhra Pradesh Arunachal Pradesh

6 [VOLUME 5 I ISSUE 3 I JULY SEPT 2018] e ISSN , Print ISSN Cosmos Impact Factor Assam Bihar Goa Gujarat Haryana Himachal Pradesh Jammu and Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Manipur Meghalaya Mizoram Nagaland Orissa Punjab Rajasthan Sikkim Tamil Nadu Tripura Uttar Pradesh West Bengal All India Source: Handbook of Statistic on Indian States Factors affecting the change in area under non-foodgrains Some socio-economic, environmental and infrastructural factors are seen to influence the cropping pattern across the states of India. The variables considered for the study are road density, percentage of urban population, poverty ratio, and average size of holdings (see Table 4). The size of land owned by the farmer has a very significant effect on the area under non-foodgrains cultivation with an increase in average size of landholdings to decrease in the non-foodgrains area. In the poverty ratio is highest in Bihar (53.50) so percentage of area under non-foodgrains is lower. Poor people are not interested to cultivate nonfoodgrains. Higher poverty ratio state like Manipur, Assam, Madhya Orissa and Uttar Pradesh has lower area under non-foodgrains. Road density has also an indirect impact on non-foodgrains cultivation through the inter-linkages between the output and commodity market and labour market that is positive impact on non-foodgrains cultivation. Most of non-foodgrains like oilseeds, sugarcane and cotton depends on rainfall, large portion of area under Rajashan, Orissa, Manipur and Assam are only depends on rainfall, rainfall is one of the factors of non-foodgrains cultivation. Percentage of urban population is one of the important factors non-foodgrains cultivation because urban population creates demand of non-foodgrains, it has positive impact on non-foodgrains cultivation. Table 4 Percentage of Area under Non-foodgrains, Road Density, Poverty Ratio, Percentage of Urban Population, Average Size of Holdings and Rainfall in States of India, States Percentage of Road density Poverty Average size Percentage of area under non-foodgrains (km/sq km) ratio of holdings (Ha) urban population Rainfall (mm) Andhra Pradesh Arunachal Pradesh Assam Bihar Research Paper IJRAR- International Journal of Research and Analytical Reviews 927y

7 Goa Gujarat Haryana Himachal Pradesh Jammu and Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Manipur Meghalaya Mizoram Nagaland Orissa Punjab Rajasthan Sikkim Tamil Nadu Tripura Uttar Pradesh West Bengal Source: Handbook of Statistic on Indian States and Ministry of Road Transport and Highways, GOI Specification of the Model The empirical analysis of the percentage of area under non-foodgrains (PANF) is made by multiple regression which is used to identify the important factors affecting the percentage of non-foodgrains area. The dependent variable is percentage of area under non-foodgrains in states of India. The independent variables are percentage of urban population (PUP), poverty ratio (PR), average size of holdings (ASH), rainfall (RF) and road density (RD). PANF = β 0 + β 1 RD + β 2 ASH + β 3 PR + β 4 RF + β 5 PUP Poverty ratio and average size of holdings tend to reduce the incentive to cultivation in nonfoodgrains. Higher population density in rural area supplies larger number of workers and these workers participate in non-foodgrains cultivation which is highly labour-intensive. We may now examine how far the variations in percentage of area under non-foodgrains (PANF or Y) are explained by those in PR, RD, RF, ASH and PUP. Table 5 reveals that the variation in PANF is explained by these five variables to the extent of 54 per cent in The average size of land holdings has a negative and significant effect on the percentage of non-foodgrains area. The negative coefficient for the average size of land holdings help us conclude that states with relatively higher proportion of land holdings will have lower magnitude of non-foodgrains cultivation. Similarly road density has a positive regression coefficient; that is, states with higher road density also have relatively higher scope for non-foodgrains cultivation. It is significant at 10 percent level. The coefficient of rainfall is positive and significant at 10 per cent level, which implies that percentage of area under non-foodgrains increases with increasing rainfall in Similarly percentage of urban population has a positive regression coefficient implying that higher percentage of urban population creates larger non-foodgrains demand; it is significant at 10 percent level in The coefficient of poverty ratio is negative but not statistically significant. It implies that percentage of area under non-foodgrains increases with decreasing poverty ratio. The whole model is significant at 5 per cent level, F value being 3.76 Table 5 also reveals that the variation in PANF is explained by these five independent variables to the extent of 63 per cent in The average size of land holdings is seen to have a negative and 928y IJRAR- International Journal of Research and Analytical Reviews Research Paper

8 [VOLUME 5 I ISSUE 3 I JULY SEPT 2018] e ISSN , Print ISSN Cosmos Impact Factor significant effect on the percentage of non-foodgrains area. The negative coefficient for the average size of land holdings make us conclude that states with relatively higher proportion of land holdings will have lower magnitude of non-foodgrains cultivation. Similarly road density has a positive regression coefficient, that is states with higher road density also have relatively high scope for non-foodgrains cultivation it is significant at 10 percent level in The coefficient of rainfall is seen to be positive and significant at 5 per cent level implying that percentage of area under non-foodgrains increases with increasing rainfall in Similarly percentage of urban population has a positive regression coefficient, which implies that higher percentage of urban population creates larger non-foodgrains demand. It is significant at 1 percent level in The coefficient of poverty ratio is negative but not statistically significant implying that percentage of area under non-foodgrains increases with decreasing poverty ratio. The whole model is significant at 1 per cent level, F value being Table 5 Regression Equaion concerning Percentage of Area under Non-foodgrains in States of India, and Period Regression Equation R-square F value PANF = ** RD ASH PR * RF * PUP (0.40) (2.63) (-0.40) (-0.36) (1.71 ) (1.80) [0.02] PANF = * RD ASH PR ** RF *** PUP (0.42) (1.77) (-0.43) (-0.51) (2.38) (3.07) [0.00] Notes: Figures within parentheses indicates t values, *** Indicates coefficient significant 1 percent level. ** Indicates coefficient significant 5 percent level. *Indicates coefficient significant 10 percent level. PANF = Percentage of area under non-foodgrains. PUP = percentage of urban Population, PR = Poverty ratio, ASH = Average size of holdings, RF = Rainfall, RD = Road density. 5. Conclusion The proportion of area under non-foodgrains increased in almost all the states during to , Percentage of area under oilseeds registered an increase in states like Arunachal Goa, Madhya Maharashtra, Manipur, Meghalaya, Nagaland and West Bengal during this period while percentage of area under sugarcane registered an increase in states like Andhra Gujarat, Karnataka, Madhya Maharashtra, Manipur, Mizoram, Tamil Nadu, Uttar Pradesh and West Bengal. Percentage of area under cotton registered an increase in states like Andhra Gujarat, Haryana, Karnataka, Maharashtra and Orissa during this period while the proportion of area under jute decreased in almost all the states. The variables considered to explain the variation in the proportion of area under nonfoodgrains are road density, percentage of urban population, poverty ratio, average size of holdings and rainfall. The size of land owned by the farmer is sen to have a very significant effect on the percentage of area under non-foodgrains cultivation implying that with an increase in average size of landholdings there is a decrease in the proportion of non-foodgrains area. Similarly road density has a positive regression coefficient, implying that states with higher road density also have relatively high scope for non-foodgrains cultivation. Likewise, percentage of urban population has a positive regression coefficient, which implies that higher percentage of urban population creates larger non-foodgrains demand. The coefficient of poverty ratio is negative implying that percentage of area under non-foodgrains increases with decreasing poverty ratio. From the discussion made so far the following policy conclusions are derived to boost up change in non-foodgrains area and production and crop diversification which have positive impact on agricultural growth. 1. Infrastructural development including road in the rural areas needs to be enhanced. 2. Waste lands have to be brought under farm development so that net cropped area increases and farm productivity rises. 3. Urbanization has a vital role to play in the shift in cropping pattern in favour of non-foodgrains and it has to be encouraged. 4. Poverty ratio has to be reduced further to enhance percentage of area under non-foodgrains. 5. Agricultural development needs to be environment-friendly through encouraging organic farming so that adverse impact of HYVs is substantially reduced and favourable rainfall is ensured. Research Paper IJRAR- International Journal of Research and Analytical Reviews 929y

9 Reference 1. Birthal, Pratap S., A.K. Jha, P.K. Joshi and D.K. Singh (2006), Agricultural Diversification in North Eastern Region of India: Implications for Growth and Equity, Indian Journal of Agricultural Economics, Vol.61, No.3. July-September 2. Birthal, P.S., P.K. Joshi, Devesh Roy and Amit Thorat (2007), Diversification in Indian Agriculture towards high value crops: The role of small holders, IFPRI Discussion paper (Nov 2007) IFPRI Research Institute, Washington D.C, U.S.A. 3. Birthal, Pratap S., P.K. Joshi, Sonia Chauhan and Harvinder Singh (2008), Can Horticulture Revitalize Agricultural Growth?, Indian Journal of Agricultural Economics, Vol 63, No3. July-Sept, pp Biswas.B.C and Khambete.N.N(1980), Reorientation of the Cropping Pattern on the Basis of Probabilistic Moisture Availability Index, Indian Journal of Agricultural Economics, Vol.35,No Chand, Ramesh (1996), Diversification through High Value Crops in Western Himalayan Region: Evidence from Himachal Pradesh, Indian Journal of Agricultural Economics, Vol.51, No.4, Oct-Dec, pp De, U.K (2003),"Changing Cropping System in Theory and Practice: An Economic Insight into the Agrarian West Bengal", Indian Journal of Agricultural Economics, Vol. 58, No. 1, January- March. 7. Ghosh, B.K. and Kuri, P.K. (2005), "Changes in Cropping Pattern in West Bengal during to '", IASSI Quarterly, Vol. 24, No. 2, October-December Joshi, P.K., P.S. Birthal and V. Bourai (2002), Socioeconomic Constraints and Opportunities in Rain fed Rabi Cropping in Rice Fallow Areas of India, International Crops Research Institute for the Semi-arid Tropics, Patancheru, India. 9. Joshi, P.K., Ashok Gulati, Pratap S. Birthal and L. Tewary (2004), Agriculture Diversification in South Asia: Patterns, Determinants, and Policy Impications, Economic and Political Weekly, June Joshi, P.K., Joshi.L and Birthal,P.S (2006), Diversification and Its Impact on Smallholders: Evidence from a Study on Vegetable Production Agricultural Economics Research Review, vol.19 pp y IJRAR- International Journal of Research and Analytical Reviews Research Paper