cropping pattern change in jammu & kashmir-a case study of district kulgam

ORIGINAL ARTICLE

ISSN No :2231-5063

International Multidisciplinary Research Journal

Golden Research Thoughts

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Vol 6 Issue 6 Dec 2016

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ABSTRACTropping pattern of an area implies Cthe proportion of

area under various crops at a time. Crops are usually classified into two broad types as food crops and cash crops. Food crops are mainly grown to fulfill the basic needs the humans in the form of food and animals in the form of fodder, whereas, cash crops are mainly grown for income generation. Cropping patterns are heavily influenced by several factors l ike terrain, to p o g r a p hy, s l o p e , temperature, rainfall, soil type and availability of water for irrigation. The topography of the Jammu and Kashmir State, and Kashmir region in particular restricts the productivity of several crops to a greater extent. The region is witnessing a greater change in the cropping pattern for the past few decades, where t h e c a s h c r o p s (particularly apple) are replacing the food crop

CROPPING PATTERN CHANGE IN JAMMU & KASHMIR-A CASE STUDY OF DISTRICT KULGAM

1 2Mohd Asif Shah and A. Anbuvel1Ph.D. Research Scholar, Department of Economics, Annamalai University,

Annamalainagar , Tamil Nadu, India.2Assistant Professor, Department of Economics, Annamalai University,

Annamalainagar , Tamil Nadu, India.

(particularly paddy) at a faster rate. The aim of this paper is to study the changes in the cropping pattern in the region, where the circumstances are paving way for specialization rather than diversification. Chi-Square test has been u s e d to c h e c k t h e association of various socioeconomic variables to change in production of paddy and apple over the last seven years. The p r i m a r y d a t a i s supplemented with the secondary data from var ious sources to represent the changes in the cropping pattern over the years.

Jammu and K a s h m i r, c r o p p i n g pattern, diversification, paddy, apple, food crops,

KEYWORDS:

cash crops

INTRODUCTION :Agriculture plays a crucia l ro le in the economic growth of India, as more than 54.6 percent of the popula- t ion is involved in agriculture and its allied act iv i t ies for the i r survival. The share of a g r i c u l t u r e i n t h e country’s GDP has fallen from 43 percent (in 1970) to just 16 percent ( i n 2 0 1 1 ) . W i t h a population, growing at a rate of nearly 2 percent per annum, food grain production is raising with an annual rate of j u s t 2 . 4 2 p e rc e n t , thereby proving the intensive subsistence n a t u r e o f I n d i a n a g r i c u l t u re ; w h e re farmers can produce

food to feed themselves and their families. The share of agriculture and allied sector in the Gross Value Added (GVA) has decl ined from 18.5 percent in 2011-12 to 17.4 percent in 2014-15 at current prices. Gross Capital Formation (GCF) in agriculture and its allied sectors relative to Gross Value Added exhibited a declining trend from 18.3 percent in 2011-12 to 15.1 percent in 2012-13. So keeping the eye on the vast population of India, instead of focusing for just being a self-reliant nation, as could be seen in the policies of the last five decades, rather the focus should be on the major earners of the foreign exchange for the c o u n t r y . A n d f o r achieving this feat the commercialization of agriculture is a neces- sary step (Hazra, 2001 & Sengupta, 2008).The major breakthrough in Indian agriculture could be seen dating back to the early 1960’s in the form of Green _

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Revolution. It was a well-planned initiative in the development of agriculture, which brought all the features for agricultural development in the nation. India, which could have been seen as a subsistence economy, not even able to generate enough food production to meet the requirements, later on became self-sufficient and export promoting nation than being an import promoting country. The advent of green revolution has totally changed the old-fashioned cropping patterns in several parts of the country.

The cropping pattern usually changes over time with the development of agriculture, as is evident in the case of agriculture in India (Vyas, 1996). This type of change is largely characterized by an increasing trend towards commercial crops over the years (Nadkarni and Vedini, 1996).As stated by Farmer, B. H. (1986), the advantage of the implementation of new technology in the form of HYV’s of cereals, especially wheat and rice, in association with controlled irrigation, use of chemical fertilizers and mechanization all led to supersede the traditional way of cultivating agriculture. Slowly but surely, the agriculture in India became profitable and started to commercialize and leaving its traditional production structure, by laying the emphasis towards more remunerative crop varieties.

Crop diversification is a strategy to stabilize and raise farm income by switching off to remunerative crops; increase employment opportunities for small and marginal farmers by shifting their excess labor to off-farm sectors; boost exports by producing the cash crops instead of depending only on the production of food crops; enhance the natural resource base by changing the old fashioned cropping patterns to new ones; and the most important one is saving the soil from losing its quality and fertility and decreasing water table so as to enrich the production and productivity and a strategy to get rid of food insecurity (Vyas, 1996; Joshi et al., 20004; Sharma, 2005). The diversification towards the cash crops has the ability to change the agricultural set-up by means of income augmentation, employment generation, and export promotion (Braun, 1995; Pingali and Rosergrant 1995; Chand, 1996; Ryan and Spencer, 2001).

Diversification in agriculture takes place through various factors viz., rural credit, financing in agriculture, government price policy, climate change, decline land holding size and food security (Alka Singh). Crop diversification, is a strategy to achieve important development goals, which has received increased attention of policy makers in the country during the recent years. The strategy envisages changes in the production activities of the farm sector, to adjust to changes in the economic environment and to face the challenges of persistent unemployment and natural resources degradation (P. K. Joshi et al., 2004). The success of the policy for crop diversification requires crop identification of suitable regionally-specific diversification alternatives, the creation of physical and institutional infrastructure facilities, and implementation of appropriate intervention strategies (Takashi Kurosaki, 2003).

The present study attempts to assess the cropping pattern change at the household level, in the Kulgam district of Jammu and Kashmir. This region has witnessed high level diversification of food crops, especially paddy to high-value cash crops like apple. Kulgam which was once used to known for its contribution in the rice production in the State and so called as the rice bowl of Kashmir is now among the least producers of rice (A. N. Raina, 2002). The share of paddy production of the district in the national income of the State has revealed a decreasing trend. Farmers feel that sticking only to the water-intensive crops like paddy in times of water-scarcity may possibly prove non-beneficial and they are willingly shifting the cultivation of cash crops like apple, almond and walnuts (J&K Govt. Report, 2012).

The inclination towards such type of diversification could be due to the result of climatic changes, as the farmers find it increasingly difficult to irrigate their rice fields. Recently, the farmers have shown not as much of interest in paddy cultivation as the paddy production has declined, because of the least profitability in cultivation of paddy, when compared to the cultivation of non-food crops like apple (Malik& Nusrat, 2013).

The returns from paddy cultivation are not increasing in proportion to the cost involved in the farming. According to Malik and Nusrat (2013), horticulture is a possible alternative for exploration in the State as paddy production shows a declining trend over the years, thereby decreasing the level of employment opportunities in the region. Farmers, particularly the poor who own very small holdings, are bound to shift from agriculture to

STATEMENT OF THE PROBLEM

Volume - 6 | Issue - 6 | December - 2016


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rain-fed horticultural farming. The area has good climatic zones for growing temperate, sub-tropical and tropical fruits throughout the year. These fruits not only form the supplement diet of the local people, but also form an important item of export to other parts of India.

1.To examine the status and nature of changing cropping pattern in the study area.2.To assess the variables influencing the production of paddy and apple in the region over the last seven years.

The study has made use of Von Thunen’s Location Theory to understand the changing cropping pattern in the study area. According to Von, the farmer does adapt his land use to site conditions, climate, land forms, and soils. He reflects the impact of the relative location of the particular farm and the suitable market on the changing cropping pattern in the particular area. Von says that the intensity of production of a particular crop decline with the distance from the market and the type of land use will vary with the distance from the market. He states that if environmental variables are held constant, then the farm product that attains the maximum profit will outbid all other products which are rival in the competition for the particular location. The location and cultivation of crops, according to him, is determined by three factors: one is the market prices, the second one being transport costs, and the third one is the yield per hectare. He illustrates that the transport cost changes with the bulk and the perishability of the crop. According to him, the crop with the maximum locational rent for the unit of land will always be grown, since, it gives the highest returns and all farmers will try to maximize their profit.

The perishable crops, according to this model, would be produced in the belts having the infrastructural facilities like access to roads and market. The more distant belts would specialize in the crops which find their market in the locality. Producers on farmland with better access to the central market must use that land intensively to produce high enough revenues to afford to be located there. This results in high person-hour inputs per unit area of land for central farms, thereby requiring large hired-labor forces. Von suggests that the producers on farmland with better access to the central market must utilize the land intensively to harvest large revenues, which in turn will result in high person-hour inputs per unit area of land for central farms.

Both primary and secondary data were used for this research and the primary data were collected through pre-tested interview schedule from the selected 272 sample respondents. The primary datawere obtained from the survey samples by adopting stratified random sampling method to choose the households from the selected villages, with the help of an interview schedule by implementing three-stage sampling procedure as follows:(i)Selection of all ten horticultural blocks of district Kulgam. (Manzgam, Waripora, D.K. Marg, Kulgam, Arreh, Kadder, Qazigund, Devsar, Qaimoh and Yaripora)(ii)Selection of thirty four highly apple populated orchardist villages from all ten blocks on the basis of the number of villages in the respective blocks.(iii)Selection of total of 272 sample respondents ofthe total thirty-four villages, eight sample respondents from each village.

The secondary data was obtained by usingDistrict Statistical Hand Book, prepared and released by the District Statistics & Evaluation Office Kulgam for the year 2014-15 and supported by theJ&K Development Report of Planning Commission, 2012.

The cropping pattern means the identification of the most efficient crops of a region which fit the intensity of cropping. The changing cropping pattern simply infers a transformation in the area under varied set of crops. Cropping patterns is the extent to which the arable land under different agricultural activities can be put

OBJECTIVES

THEORETICAL PERSPECTIVE

METHODOLOGY

STATUS AND NATURE OF CROPPING PATTERN AT THE DISTRICT LEVEL



3


to use (Singh and Dhillon, 2005). Increasing the area under high value crop is expected to increase total return from the farm. The cropping pattern change is of great interest to the agricultural economists for its notable impact on agricultural output (Ranade, 1980). Everywhere, the major influencing factor behind the changes in the cropping pattern is found to be the size of the land owned by the farmer. Small farms dominate agricultural economy of India, and so is the case of Jammu and Kashmir. Small farmers are largely poor and depend upon their farms for their sustenance (Kadapatti & Bagalkoti, 2014). In general, the farmers have a tendency to stick to a stable cropping pattern under any given agro-climatic region unless they are dictated by the price factors in adjusting acreage allocation (Murthyunjaya and Kumar, 1989). Climate is also found to be the most significant environmental variable affecting the production of crops (R. K. Aggarwal).

Source: Computed.

So it can be seen from the above table, that the highest share of land holdings (94.43 percent) are marginal, with 5.01 percent small, 0.53 percent semi-medium, 0.03 percent medium and large holdings come for zero percent. And still the more important thing is that the marginal farmers being the highest group share just 81.30 percent of the total land area, with small farmers sharing 14.87 percent, semi-medium farmers sharing 3.46 percent and the medium farmers sharing 0.37 percent of the total.

Hence, the small farmers do have the option for the production of such crops which can uplift them from the severe poorness. Thus, they choose to cultivate the commercial crops in preference of food crops. The area under food crops has not been increasing in proportion to the area under fruits has been increased over the past few decades. Paddy is a highly labour-intensive crop, and rice cultivation is a major source of employment in the state. On the other hand, the labor requirements of cash crops (such as apple) are marginal. The shift in cropping pattern away from rice towards cash crops does have important implications for employment and also for the income distribution between the owner-cultivators and agricultural labourers.

Source: Computed.

From the above table it is clearly seen that the area under paddy cultivation has increased very little and it does not compulsory infer that the paddy land is not losing its area in cost for apple cultivation. Because from

Table No.1 {Land Holdings according to different size /classes (2010-11)}

Table No. 2 {Area under Crops (Hectares)}



Size- Class Land Holding Size

Number %age Share Area (Hectares) %age Share Marginal 63007 94.43 21327 81.30

Small 3340 5.01 3901.25 14.87 Semi-Medium 356 0.53 908.95 3.46

Medium 21 0.03 97.09 0.37 Large 0.00 0.00 0.00 0.00

All Classes 66724 100.00 26234.29 10.00

Year Paddy CAGR Maize CAGR Pulses CAGR Fruits CAGR Vegetables CAGR

2007-08 17961 100.00 4928 100.00 1047 100.00 5770 100.00 1009 100.00

2008-09 18291 101.84 4507 91.46 1170 111.48 5693 98.67 1059 104.50

2009-10 19537 108.77 3034 61.57 1133 108.21 5645 97.83 1109 109.91

2010-11 18121 100.89 3761 76.32 829 79.18 5347 92.69 1092 108.23

2011-12 16729 93.14 3275 66.46 1166 111.37 8532 147.87 1097 108.72

2012-13 16812 93.60 3827 77.66 1167 111.46 8900 154.25 1097 108.72

2013-14 16748 93.25 3061 62.57 1125 107.45 8747 151.59 1021 101.19

4


the Table No. 3, it is visible that the area not available for cultivation and area of other uncultivated land has been decreasing to a greater extent. Such type of land is being made available for cultivating paddy and the land already under the cultivation of paddy is losing its area for the cash crops, especially apple.

Source: Computed.

The region has different lands based on altitude (highlands, midlands, lowlands), but the cultivation of apple has become a fashion, instead of suiting the land quality. Area under fruits has gone up and it appears that the apple orchardists are increasing at the expense of paddy land. Horticultural crops, that tolerate low moisture conditions, especially in time summer months, such as apple, cherry, pear, almond, walnut and apricot are grown in the high altitude lands, where there is the shortage of irrigation water. While as the food crops like maize and rice are the most important crops easily grown in mid altitude lands, because of the abundant water in the soil throughout the year. And regarding the lowlands, the feature of sandy-to- sandy-loam soil makes it possible to cultivate root crops like radishes, beets, carrots, turnips, onion, potatoes and leafy vegetables, like lettuce, cabbage, spinach, cauliflower, broccoli, etc.

Horticulture sector plays a significant role in enhancing the economic profile of the people of the State and can be a promising sector, if the principle of the scientific program of horticulture development is adopted by the government. It implicates gratification that the State is enriched with rich green assets (horticultural crops) and henceforth offers an enormous outline for exploiting these assets at a broad and business scale. The J&K State in general and the Kulgam district in particular is witnessing a tremendous growth of horticultural crops, especially the growth of area and production of apple.

Source: Computed.

Table No. 3 {Land Utilization Pattern (Area in Hectares)}

Table No. 4{Area and Production of Fruit Crops in Kulgam District}



Year Area Under Forests

Reporting Area

Area not Available for Cultivation

Other Uncultivated

Land

Fallow Land

Net Area Sown

2007-08 190 47642 8894 7667 184 30707

2008-09 190 47642 8894 7667 208 30683

2009-10 190 47642 7491 7040 2149 30772

2010-11 190 47642 7112 6418 4903 29019

2011-12 190 47642 5491 6040 5242 30679

2012-13 190 47642 5475 6372 4926 30679

2013-14 190 47642 5475 6372 4925 30680

Area under Fruit-Crops. (Hectares)

Year Fresh Fruit CAGR Dry Fruit CAGR Total CAGR

2007-08 6560 100.00 157 100.00 6717 100.00

2008-09 14364 218.96 6085 3875.80 20449 304.44

2009-10 16236 113.03 6099 100.23 22335 109.22

2010-11 17178 105.80 6132 100.54 23310 104.37

2011-12 17446 101.56 6132 100.00 23578 101.15

2012-13 18405 105.50 6147 100.24 24552 104.13

2013-14 19092 103.73 6162 100.24 25254 102.86

Production under Fruit Crops. (Metric Tons)

Year Fresh Fruit CAGR Dry Fruit CAGR Total CAGR

2007-08 65895 100.00 2812 100.00 68707 100.00

2008-09 124510 188.95 8466 301.07 132976 193.54

2009-10 120156 96.50 20619 243.55 140775 105.86

2010-11 129408 107.70 21404 103.81 150812 107.13

2011-12 122122 94.37 21340 99.70 143462 95.13

2012-13 131090 107.34 19034 89.19 150124 104.64

2013-14 156689 119.53 24424 128.32 181113 120.64

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The above table depicts the area and production of fresh and dry fruits. It can be easily comprehended by the above table, both the area and production of the crops has increased over the years, especially in the year 2008-09. The area under the fresh fruits has been increasing steadily over the years, but in case of the dry fruits, the area under them has not increased to a greater extent. Similarly, for the case of production, fresh fruit production has been rising over the years, but the production of dry fruits has risen up to 2009-10 and later on decreased up to 2012-13. Now the keen interest is on the trend of productivity of both types of crops, which will depict the actual situation among both the crops, occurred over the years. The below table (Table No.5) portrays the productivity of dry fruits and fresh fruits in the district, over the years:

Source: Computed.

The table shows that the productivity of both types of crops is not showing a promising trend. The productivity of fresh fruits, as well as of dry fruits has declined over the years. However, the cultivation of cash crops (fruits) is considered as a better option than cultivating the food crops like paddy. Paddy land is getting changed into horticultural land, as the farmers find it to be more remunerative as compared to the cultivation of paddy.

Cross-tabulation was done to check the percentage aggregates of all the sample respondents, that’s how the demographic variables have impacted the production of the paddy cultivated by them. Within a single variable, the change of the different groups was observed. Chi-Square test has been used to find out the association between the dependent variable,i.e., the production pattern in case of paddy cultivation over the last seven years (whether increased, or decreased, or did not change) and the various independent variables (characteristics of the household head) such as age, gender, educational qualification, occupation, family type, family size and land owned.

Table No. 5 {Productivity of Fruit Crops in Kulgam District (Metric Tonnes/ Hectare}

Variables Influencing the Production of Paddy in the Study Area.



Year Fresh Fruit Dry Fruit Total

2007-08 10.04 17.91 10.23

2008-09 8.67 1.39 6.50

2009-10 7.40 3.38 6.30

2010-11 7.53 3.49 6.47

2011-12 7.00 3.48 6.08

2012-13 7.12 3.10 6.11

2013-14 8.21 3.96 7.17

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Annexure - 1{Association between the Demographic Variables & Paddy Productionin the Last Seven Years}



Variables Paddy Cultivation Over The Last Seven Year s Total

Increased Decreased Did not change

Age (21 to 40) 20

(41.7) 12

(25.0) 16

(33.3) 48

(100.0)

Age (41 to 60) 78

(45.3) 32

(18.6) 62

(36.0) 172

(100.0)

Age (Above 60) 20

(38.5) 8

(15.4) 24

(46.2) 52

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0)

Chi square (3.10) Df (4) P-value (0.54)

Gender (Male) 110

(45.1) 50

(20.5) 84

(34.4) 244

(100.0)

Gender (Female) 8

(28.6) 2

(7.1) 18

(64.3) 28

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0) Chi square (9.89) Df (2) P-value (0.001)

Education (Illiterate) 40

(50.0) 14

(17.5) 26

(32.5) 80

(100.0)

Education (Middle) 34

(33.3) 18

(17.6) 50

(49.0) 102

(100.0)

Education (HSC) 22

(61.1) 4

(11.1) 10

(27.8) 36

(100.0)

Education (Graduation) 10

(45.5) 6

(27.3) 6

(27.3) 22

(100.0)

Education (PG/Other) 12

(37.5) 10

(31.3) 10

(31.3) 32

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0)


Occupation (Agriculture) 42

(35.6) 22

(18.6) 54

(45.8) 118

(100.0)

Occupation (Business) 44

(53.7) 10

(12.2) 28

(34.1) 82

(100.0)

Occupation (Government Service) 32

(44.4) 20

(27.8) 20

(27.8) 72

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0)


Family Type (Nuclear Family) 86

(44.3)

42

(21.6)

66

(34.0)

194

(100.0)

Family Type (Joint Family) 32

(41.0) 10

(12.8) 36

(46.2) 78

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0) Chi square (4.59) Df (2) P-value (0.10)

Family Size (Below 5) 62

(39.7) 38

(24.4) 56

(35.9) 156

(100.0)

Family Size (6-10) 38

(50.0) 10

(13.2) 28

(36.8) 76

(100.0)

Family Size (Above 10) 18

(45.0) 4

(10.0) 18

(45.0) 40

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0)


Land Owned (Below 2 Kanals) 4

(40.0) 2

(20.0) 4

(40.0) 10

(100.0)

Land Owned (3-4 Kanals) 22

(44.0) 4

(8.0) 24

(48.0) 50

(100.0)


(40.7) 32

(29.6) 32

(29.6) 108

(100.0)


(47.8) 14

(15.2) 34

(37.0) 92

(100.0)

Land Owned (Above 16 Kanals) 4

(33.3) 0 8

(66.7) 12

(100.0)

Total 118

(43.4) 52

(19.1) 102

(37.5) 272

(100.0)

7


In the age group of 21 to 40, the highest share of 20 sample respondents (41.7 percent) shows an increase and the least share of 12 sample respondents (25.0 percent) shows a decrease in the paddy production over the last seven years. Similarly, in the age group of 41 to 60, the highest share of 78 sample respondents (45.3 percent) shows an increase and the least share of 32 sample respondents (18.6 percent) shows a decrease in the paddy production over the last seven years. But, in the age group with respondents having age above 60 years, the highest share of 24 sample respondents (46.2 percent) depicted no change and the least share of 8 sample respondents (15.4 percent) shows a decrease in the paddy production over the last seven years. The result reveals that the calculated chi-square value (3.10) at 4 degrees of freedom is > 0.05. Therefore, it can be concluded that there is no association between the attribute (age) and the production pattern in case of paddy cultivation over the last seven years.

In the case of gender, among the males, the highest share of 110 sample respondents (45.1 percent) shows an increase and the least share of 50 sample respondents (20.5 percent) shows a decrease in the paddy production over the last seven years. And among the females the highest share of 18 sample respondents (64.3 percent) depicted no change and the least share of 2 sample respondents (7.1 percent) shows a decrease in the paddy production over the last seven years. The result reveals that the calculated chi-square value (9.89) at 4 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (gender) and the production pattern in case of paddy cultivation over the last seven years.

In the case of educational qualification, considering illiterates, the highest share of 40 sample respondents (50.0 percent) shows an increase and the least share of 14 sample respondents (17.5 percent) shows a decrease in the paddy production over the last seven years. Among the respondents who have studied up to middle, the highest share of 50 sample respondents (49.0 percent) depicted no change and the least share of 18 sample respondents (17.6 percent) shows a decrease in the paddy production over the last seven years. Among the respondents, who have studied HSC, the highest share of 22 sample respondents (61.1 percent) shows an increase and the least share of 4 sample respondents (11.1 percent) shows a decrease in the paddy production over the last seven years. But, the respondents who have studied up to graduation, the highest share of 10 sample respondents (45.5 percent) shows an increase, a share of 6 sample respondents (27.3 percent) shows a decrease and a share of 6 sample respondents (27.3 percent) shows no change in the paddy production over the last seven years. And finally among the sample respondents who have studied PG or above, the highest share of 12 sample respondents (37.5 percent) shows an increase, a share of 10 sample respondents (31.3 percent) shows a decrease and a share of 10 sample respondents (31.3 percent) shows no change in the paddy production over the last seven years. The result reveals that the calculated chi-square value (16.72) at 8 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (educational qualification) and the production pattern in case of paddy cultivation over the last seven years.

In the case of occupational structure, among the respondents practicing agriculture, the highest share of 54 sample respondents (45.8 percent) depicted no change and the least share of 22 sample respondents (18.6 percent) shows a decrease in the paddy production over the last seven years. But, among the respondents having business as their main income generating source, the highest share of 44 sample respondents (53.7 percent) shows an increase and the least share of 10 sample respondents (12.2 percent) shows a decrease in the paddy production over the last seven years. Similarly, among the respondents who are in government service, the highest share of 32 sample respondents (44.4 percent) shows an increase, a share of 20 sample respondents (27.8 percent) shows a decrease and a share of 20 sample respondents (27.8 percent) shows no change in the paddy production over the last seven years.The result reveals that the calculated chi-square value (12.76) at 4 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (occupation) and the production pattern in case of paddy cultivation over the last seven years.

In the case of family type, among the nuclear type household families, the highest share of 86 sample respondents (44.3 percent) shows an increase and the least share of 42 sample respondents (21.6 percent) shows a decrease in the paddy production over the last seven years. And among the joint family type



8


households, the highest share of 36 sample respondents (46.2 percent) shows no change and the least share of 10 sample respondents (12.8 percent) shows a decrease in the paddy production over the last seven years. The result reveals that the calculated chi-square value (4.59) at 2 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (family type) and the production pattern in case of paddy cultivation over the last seven years.

In the case of family size, in the group of households having family size below 5, the highest share of 62 sample respondents (39.7 percent) shows an increase and the least share of 38 sample respondents (24.4 percent) shows a decrease in the paddy production over the last seven years. Similarly, among the households in the group of 6-10 the highest share of 38 sample respondents (50.0 percent) shows an increase and the least share of 10 sample respondents (13.2 percent) shows a decrease in the paddy production over the last seven years. And, among the households having the family size of above 10, 18 sample respondents (45.0 percent) shows an increase, 18 sample respondents (45.0 percent) depicted no change and the least share of 4 sample respondents (10.0 percent) shows a decrease in the paddy production over the last seven years.The result reveals that the calculated chi-square value (7.376) at 4 degrees of freedom is > 0.05. Therefore, it can be concluded that there is no association between the attribute (family size) and the production pattern in case of paddy cultivation over the last seven years.

In case of land owned, considering the group of households having land size below 2 Kanals, 4 sample respondents (40.0 percent) shows an increase, a share of 4 sample respondents (40.0 percent) depicted no change and the least share of 2 sample respondents (20.0 percent) depicted a decrease in the paddy production over the last seven years. Among the respondents who have been having the land size of 3 to 4 Kanals, the highest share of 24 sample respondents (48.0 percent) depicted no change and the least share of 4 sample respondents (8.0 percent) shows a decrease in the paddy production over the last seven years. Among the respondents, who have land size of 5 to 8 Kanals, the highest share of 44 sample respondents (40.7 percent) shows an increase, a share of 32 sample respondents (29.6 percent) shows a decrease and the least share of 32 sample respondents (29.6 percent) shows no change in the paddy production over the last seven years. Among the respondents who have land size of 9 to 16 Kanals, the highest share of 44 sample respondents (47.8 percent) shows an increase and the least share of 14 sample respondents (15.2 percent) shows a decrease in the paddy production over the last seven years. And among the sample respondents who have land size of above 16 Kanals, the highest share of 8 sample respondents (66.7 percent) shows a decrease, and the rest of the 4 sample respondents (33.3 percent) shows a decrease in the paddy production over the last seven years. The result reveals that the calculated chi-square value (19.40) at 8 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (land owned) and the production pattern in case of paddy cultivation over the last seven years.

Cross-tabulation was done to check the percentage aggregates of all the sample respondents, that’s how the demographic variables have impacted the production of the apple cultivated by them. Chi-Square test has been used to find out the association between the production pattern in case of apple cultivation over the last seven years and the various characteristics of the household head such as age, gender, educational qualification, occupation, family type, family size and land owned.

In the age group of 21 to 40, the highest share of 28 sample respondents (58.3 percent) shows an increase and the least share of 8 sample respondents (16.7 percent) shows a decrease in the apple production over the last seven years. Among the respondents of the age group of 41 to 60, the highest share of 108 sample respondents (62.8 percent) shows an increase, a share of 32 sample respondents (18.6 percent) shows a decrease and a share of 32 sample respondents (18.6 percent) shows no change in the apple production over the last seven years. And among the respondents having age above 60 years, the highest share of 42 sample respondents (80.0 percent) depicted no change and the least share of 4 sample respondents (7.7 percent) shows no change in the apple production over the last seven years. The result reveals that the calculated chi-square value (8.08) at 4 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an

Variables Influencing the Production of Apple in the Study Area.



9


association between the attribute (age) and the production pattern in case of apple cultivation over the last seven years.

In the case of gender, among the males, the highest share of 160 sample respondents (65.6 percent) shows an increase and the least share of 38 sample respondents (15.6 percent) shows a decrease in the apple production over the last seven years. And among the females the highest share of 18 sample respondents (64.3 percent) also shows an increase and the least share of 2 sample respondents (7.7 percent) shows no change in the apple production over the last seven years. The result reveals that the calculated chi-square value (4.46) at 4 degrees of freedom is > 0.05. Therefore, it can be concluded that there is no association between the attribute (gender) and the production pattern in case of apple cultivation over the last seven years.

Annexure –2{Association between the Demographic Variables &Apple Production in the Last Seven Years}



A ge A pple Cultivation O ver The Last Seven Y ears T otal

Increased D ecreased Did not change

A ge (21 to 40) 28

(58.3) 8

(16 .7 ) 1 2

(25.0 ) 4 8

(100 .0 )

A ge (41 to 60) 1 08

(62.8) 32

(18 .6 ) 3 2

(18.6 ) 1 72

(100 .0 )

A ge (Abov e 60 ) 42

(80.8) 6

(11 .5 ) 4

(7.7) 5 2

(100 .0 )

Total 1 78

(65.4) 46

(16 .9 ) 4 8

(17.6 ) 2 72

(100 .0 )

C hi sq uare (8.08 ) Df (4) P-val ue (0 .01)

Gender (Ma le) 1 60 (65.6) 38 (15.6) 4 6 (18.9) 2 44

(100 .0 )

Gender (Fema le) 18 (64 .3 ) 8 (28 .6 ) 2 (7 .1 ) 2 8

(100 .0 )

Total 1 78

(65.4) 46

(16 .9 ) 4 8

(17.6 ) 2 72

(100 .0 )


Educatio n (Illitera te) 50

(62.5) 20

(25 .0 ) 1 0

(12.5 ) 8 0

(100 .0 )

Educatio n (M iddle) 70

(68.6) 14

(13 .7 ) 1 8

(17.6 ) 1 02

(100 .0 )

Educatio n (HSC) 20

(55.6) 6

(16 .7 ) 1 0

(27.8 ) 3 6

(100 .0 )

Educatio n (Graduatio n) 16

(72.7) 2

(9.1) 4

(18.2 ) 2 2

(100 .0 )

Educatio n (PG/Other) 22

(68.8) 4

(12 .5 ) 6

(18.8 ) 3 2

(100 .0 )

Total 1 78

(65.4) 46

(16 .9 ) 4 8

(17.6 ) 2 72

(100 .0 )


Occupa tio n (Ag riculture) 82 (69 .5 ) 22 (18.6) 1 4 (11.9) 1 18

(100 .0 )

Occupa tio n (B us iness) 50 (61 .0 ) 14 (17.1) 1 8 (22.0) 8 2

(100 .0 ) Occupa tio n (G overnment

Service)

46 (63 .9 ) 10 (13.9) 1 6 (22.2) 7 2

(100 .0 )

Total 1 78

(65.4)

46

(16 .9 )

4 8

(17.6 )

2 72

(100 .0 ) C hi sq uare (5.12 ) Df (4) P-val ue (0 .27)

F ami ly Ty pe (Nuclea r

F ami ly)

1 16 (59.8) 38 (19.6) 4 0 (20.6) 1 94

(100 .0 ) F ami ly Ty pe (Joint

F ami ly)

62 (79 .5 ) 8 (10 .3 ) 8 (10.3 ) 7 8

(100 .0 )

Total 1 78

(65.4)

46

(16 .9 )

4 8

(17.6 )

2 72

(100 .0 ) C hi sq uare (9.54 ) Df (2) P-value (0 .0 01)

F ami ly Si ze (Below 5) 96 (61 .5 ) 32 (20.5) 2 8 (17.9) 1 56

(100 .0 )

F ami ly Si ze (6-10) 50 (65 .8 ) 8 (10 .5 ) 1 8 (23.7) 7 6

(100 .0 )

F ami ly Si ze (Abo ve 1 0) 32 (80 .0 ) 6 (15 .0 ) 2 (5 .0 ) 4 0

(100 .0 )

Total 1 78

(65.4)

46

(16 .9 )

4 8

(17.6 )

2 72

(100 .0 ) C hi sq uare (9.97 ) Df (4) P-val ue (0 .01)

La nd Owned (Belo w 2 K ana ls)

6 (60.0) 2 (20 .0 ) 2 (20.0 ) 1 0 (100 .0 )

La nd Owned (3 -4 K ana ls) 26 (52 .0 ) 10 (20.0) 1 4 (28.0) 5 0

(100 .0 )

La nd Owned (5 -8 K ana ls) 72 (66 .7 ) 22 (20.4) 1 4 (13.0) 1 08

(100 .0 )

La nd Owned (9 -16 K ana ls)

64 (69 .6 ) 10 (10.9) 1 8 (19.6) 9 2 (100 .0 )

La nd Owned (Above 16

K ana ls)

10 (83 .3 ) 2 (16 .7 ) 0 1 2

(100 .0 )

Total 1 78

(65.4)

46

(16 .9 )

4 8

(17.6 )

2 72

(100 .0 ) Chi square (12.0 8) Df (8) P-val ue (0 .14)

10


In the case of educational qualification, considering illiterates, the highest share of 50 sample respondents (62.5 percent) shows an increase and the least share of 10 sample respondents (12.5 percent) shows no change in the apple production over the last seven years. And among the respondents who have studied up to middle, the highest share of 70 sample respondents (68.6 percent) shows an increase and the least share of 14 sample respondents (13.7 percent) shows a decrease in the apple production over the last seven years. Similarly among the respondents, who have studied HSC, the highest share of 20 sample respondents (55.6 percent) shows an increase and the least share of 6 sample respondents (16.7 percent) shows a decrease in the apple production over the last seven years. Likewise, among the respondents who have studied up to graduation, the highest share of 16 sample respondents (72.7 percent) shows an increase and the least share of 2 sample respondents (9.1 percent) shows a decrease in the apple production over the last seven years. And also among the sample respondents who have studied PG or above, the highest share of 22 sample respondents (68.8 percent) shows an increase and the least share of 4 sample respondents (12.5 percent) shows a decrease in the apple production over the last seven years. The result reveals that the calculated chi-square value (9.22) at 8 degrees of freedom is > 0.05. Therefore, it can be concluded that there is no association between the attribute (education) and the production pattern in case of apple cultivation over the last seven years.

In the case of occupational structure, among the respondents practicing agriculture, the highest share of 82 sample respondents (69.5 percent) shows an increase and the least share of 14 sample respondents (11.9 percent) shows no change in the apple production over the last seven years. Among the respondents having business as their main income generating source, the highest share of 56 sample respondents (61.0 percent) shows an increase and the least share of 14 sample respondents (17.1 percent) shows a decrease in the apple production over the last seven years. Likewise, among the respondents who are in government service, the highest share of 46 sample respondents (63.9 percent) shows an increase and the least share of 10 sample respondents (13.9 percent) shows a decrease in the apple production over the last seven years. The result reveals that the calculated chi-square value (5.12) at 4 degrees of freedom is > 0.05. Therefore, it can be concluded that there is no association between the attribute (occupation) and the production pattern in case of apple cultivation over the last seven years.

In the case of family type, among the nuclear type household families, the highest share of 116 sample respondents (59.8 percent) shows an increase and the least share of 38 sample respondents (19.6 percent) shows a decrease in the apple production over the last seven years. Similarly, among the joint family type households, the highest share of 62 sample respondents (79.5 percent) also shows an increase and the least share of 8 sample respondents (10.3 percent) shows a decrease in the apple production over the last seven years. The result reveals that the calculated chi-square value (9.54) at 2 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (family type) and the production pattern in case of apple cultivation over the last seven years.

In the case of family size, in the group of households having family size below 5, the highest share of 96 sample respondents (61.5 percent) shows an increase and the least share of 28 sample respondents (17.9 percent) shows no change in the apple production over the last seven years. Among the households in the group of 6-10 the highest share of 50 sample respondents (65.8 percent) shows an increase and the least share of 8 sample respondents (10.5 percent) shows a decrease in the apple production over the last seven years. And, among the households having the family size of above 10, 32 sample respondents (80.0 percent) shows an increase and the least share of 2 sample respondents (5.0 percent) shows no change in the apple production over the last seven years. The result reveals that the calculated chi-square value (9.97) at 2 degrees of freedom is significant at 0.01 levels. Therefore, it can be concluded that there is an association between the attribute (family size) and the production pattern in case of apple cultivation over the last seven years.

In case of land owned, considering the group of households having land size below 2 Kanals, 6 sample respondents (60.0 percent) shows an increase, a share of 2 sample respondents (20.0 percent) shows a decrease and a share of 2 sample respondents (20.0 percent) shows no change in the apple production over the last seven years. Among the respondents who are having the land size of 3 to 4 Kanals, the highest share of 26 sample respondents (52.0 percent) shows an increase and the least share of 10 sample respondents (20.0 percent)



11


shows a decrease in the apple production over the last seven years. And among the respondents, who have land size of 5 to 8 Kanals, the highest share of 72 sample respondents (66.7 percent) shows an increase and the least share of 14 sample respondents (13.0 percent) shows no change in the apple production over the last seven years. Among the respondents who have land size of 9 to 16 Kanals, the highest share of 64 sample respondents (69.6 percent) shows an increase and the least share of 10 sample respondents (10.9 percent) shows a decrease in the apple production over the last seven years. And among the sample respondents who have land size of above 16 Kanals, the highest share of 10 sample respondents (83.3 percent) shows a decrease and the rest of the 2 sample respondents (16.7 percent) shows a decrease and no any respondent who shows a decrease in the apple production over the last seven years. The result reveals that the calculated chi-square value (12.08) at 8 degrees of freedom is > 0.05. Therefore, it can be concluded that there is no association between the attribute (land owned) and the production pattern in case of apple cultivation over the last seven years.

So from the overall discussion, it is clear that food crops, especially paddy is losing its area of cultivation to the cash crops because of their remunerative output against the food crops. The secondary data obtained from various sources after the evaluation also depicted the same story, which was supported by the primary the data, obtained from the sample respondents using the interview schedule. The variables which were found to be significant for the change in production of paddy, turned out to be insignificant in case of production of apple, and the variables which were found to be insignificant for the paddy production turned out to be significant in the case of apple production.

Now the question arises, that whether the shift in cropping pattern is a good move or not, it will be represented in the coming decades. Till now the farmers have not shown any disinterest or negative impact of the changing of cropping pattern. Rather, they are seen to be motivated by the move, as the cultivation of cash crops seems to be more beneficial for them, rather than the cultivation of food crops. Food crops can just sustain their food needs, rather the cash crops seems to be a good strategy to maximize the profits by exporting the produce to the rest of the country and the world.There is now the need of the intervention of the government to make it a good move, because the farmers are seen facing lot of problems while going from the food crops to the cash crops. The need of the infrastructural development is the need of the hour, and the government should try to make efforts for making the rice availability to the population, as the people of the area are having rice as the staple food for them. So the insecurity of food should be taken into consideration. Another problem faced in areas like Punjab, where the particularity in the cropping pattern had a great ecological damage, hence, under such circumstances, there is need to identify the varieties and regions suitable for production of quality fruits.

The building of virtuous governmental policies in the form of minimization of unit fixed costs of specialized machinery needed for apple cultivation, specialized crop culture skills, macro macro-market structure, processing infrastructure in the form of post-harvest management can turn the move into a great success, by enabling the crop to be cultivated on a large scale, and turning the traditional farm into a modern and commercial farm. The State can no doubt reap tremendous economic gains bydeveloping policies and strategies that focus on the development of the horticultural sector by making more effective use of knowledge to increase the overall productivity of the sector, leading to the prosperity of its economy and the welfare of its population. In so doing, the State will be able to improve its international competitiveness and join the ranks of countries that are making a successfultransition to the horticultural economy.

In the last, I will conclude by quoting the document of the World Bank, which was on the leveraging strengths and opportunities of Indian economy, that still India having the world’s largest agricultural research and extension system, but its efficiency and effectiveness has been increasingly called into question. The report goes on documenting the situation of the Indian economy as this, “A more regionally differentiated R&D strategy is needed for agriculture. The top-down, narrow, crop-focused approach to agricultural extension has also become outmoded and ineffective in meeting the needs of farmers. In the future, the public extension system must become more demand driven, with stronger synergies between public and private extension efforts” (World Bank, 2003).

CONCLUSION:



12


REFERENCES1.Aggarwal, R. K. (2013). Effect of rainfall on cropping pattern in mid Himalayan region. African Journal of Environmental Science and Technology, 7(7), 634-640.2.Farmer, B. (1986). Perspectives on the 'Green Revolution' in South Asia. Modern Asian Studies, 20(1), 175-199.3.Hazra, C. R. (2001). CROP DIVERSIFICATION IN INDIA. CROP DIVERSIFICATION IN THE ASIA-PACIFIC REGION, 32.4.Kadapatti, R. G., & Bagalkoti, S. T. (2014). Small Farms and Agricultural Productivity-A Macro Analysis. International Journal of Social Science Studies, 2(3), 123-135.5.Kurosaki, T. (2003). Specialization and Diversification in Agricultural Transformation: The Case of West Punjab, 1903-92. American Journal of Agricultural Economics, 372-386.6.Nadkarni, M. V., & Vedini, K. H. (1996). Accelerating commercialization of agriculture. Economic and Political Weekly, 22, a63-a73.7.O’Kelly, M., & Bryan, D. (1996). Agricultural Location Theory: Von Thiinen's Contribution to Economic Geography'. Progress in Human Geography, 20(4), 457-475.8.Ranade, C G (1980). ‘Impact of Cropping Pattern on Agricultural Production’, Indian Journal of Agricultural Economics, 35 (2), April-June. 9.Sengupta, S. (2008). The food chain in fertile India, growth outstrips agriculture. New York Times. http://www.nytimes.com/2008/06/22/business/22indiafood.html10.Sharma, H. R. (2005). Agricultural Development and Crop Diversification in Himachal Pradesh: Understanding the Patterns, Processes, Determinants and Lessons. Indian Journal of Agricultural Economics, 60(1).11.Singh, Alka (2014). Agricultural Production and Cropping Pattern Change in India South. Asian Journal of Multidisciplinary Studies, 2 (2).12.Singh, J. and Dhillon, S.S, 2005. Agricultural Geography. New Delhi: Tata McGraw Hill Publications.13.Vyas, V. S. (1996). Diversification in Agriculture: Concept, Rationale and Approaches. Indian Journal of Agricultural Economics, 51(4), 636.14.Raina, A. N. (2002). Geography of Jammu & Kashmir State. Radha Krishan Anand & Co., Pacca Danga, Jammu.15.A.H., Malik & Jan Nusrat (2013). Portrait of Agriculture in Jammu and Kashmir, Greater Kashmir, Issue 29 Jan. 2013.http://www.greaterkashmir.com/news/gk-magazine/portrait-of-agriculture-in-j-k/138683.html16.J&K Development Report of Planning Commission, 2012.



Mohd Asif ShahPh.D. Research Scholar, Department of Economics, Annamalai University, Annamalainagar , Tamil Nadu, India.

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