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Int.J.Curr.Microbiol.App.Sci (2018) 7(7): 1160-1166 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 07 (2018) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2018.707.140 Income and Employment Generation under Optimum Combination of Different Enterprises in Sugarcane Based Farming System for Small Category of Farms in District Meerut of Uttar Pradesh, India Subhash Kumar Jawla1*, Babu Singh1, Teshu Kumar2 and Rahul Katiyar1 1 Chandra Shekhar Azad Universities of Agriculture and Technology, Kanpur - 208001, Uttar Pradesh, India 2 Lovely professional University, Jalandhar, Punjab, India *Corresponding author ABSTRACT Keywords Farming system, Optimization, LP model, Livestock, Land allocation, Employment generation. Article Info Accepted: 08 June 2018 Available Online: 10 July 2018 The present study was conducted during the year 2013-14 in District Meerut of Uttar Pradesh to know the possibilities of optimum combination of different enterprises for the enhancement of the farms income and employment of small category of farms household’s. Multistages tratified random sampling design was used to collect the primary data from; a sample of 32 respondents was selected on the basis of probability proportion to size of holdings. A linear programming (LP) model was used to find out the optimal farm plan for optimum land allocation for maximization of net returns and to generate employment from, small category of farms. In the study area, Small farms linear programming model resulted that increase in return which was 33.72 per cent higher than the existing farm plan and labour man days 69.59 per cent higher compare to the existing farm plan. Introduction Agriculture continues to be the backbone of Indian economy. It may be noted that Indian agriculture is the home of small and marginal farmers (80%) The structural reforms and stabilization policies introduced in India in 1991 initially focused on industry, tax reforms, foreign trade and investment, banking and capital markets. The economic reforms did not include any specific package specifically designed for agriculture. We have problems of poverty, unemployment, inequalities in access to health and education and poor performance of agriculture sector. One of the excluded sector during the reform period was agriculture which showed low growth and experienced more farmers’ suicides. There are serious concerns on the performance of agriculture sector in the country. Especially for small and marginal farmers who constitute more than 80 Per cent of the farming community. The crop and cropping system based research needs to be 1160 Int.J.Curr.Microbiol.App.Sci (2018) 7(7): 1160-1166 conducted in a holistic manner for the generating suitable management of available resources in an optimum manner by small farmer. Compared to many other crops grown, sugarcane is a highly versatile plant which is successfully grown as a cash crop under a wide range of conditions in Meerut. Soil texture varying from light sands to heavy clay and under pH ranging from 4 to 7, and it also shows remarkable resistance to drought. Therefore the farming systems approach is a valuable tool for addressing the problems of sustainable economic growth for farming communities in India. Farming System is a complex inter-related matrix of soil, plants, animals, implements, power, labour, capital and other inputs controlled in parts by farming families and influenced to varying degrees by political, economic, institutional and social forces that operate at many levels. Agriculture production and livestock production are intrinsically linked, one be dependent on the other, and both crucial for overall food security. The role of small farms in development and poverty reduction is well recognized (Lipton, 2006). The global experience of growth and poverty reduction shows that GDP growth originating in agriculture is at least twice as effective in reducing poverty as GDP growth originating outside agriculture (WDR, 2008). Small holdings play important role in raising agricultural development and poverty reduction. The objective of this paper is to examine the role and challenges of small holding agriculture in achieving agricultural growth, food security and livelihoods in India. Small holdings also face new challenges on integration of value chains, liberalization and globalization effects, market volatility and other risks and vulnerability, adaptation of climate change etc. (Thapa and Gaiha, 2011). One of the paradoxes of the Indian economy is that the decline in the share of agricultural workers in total workers has been slower than the decline in the share of agriculture in the GDP. Thus, the small holding character of Indian agriculture is much more prominent today than even before. The average size of holdings in India declined from 2.3 ha. in 1970-71 to 1.33 ha. in 2000-01. Materials and Methods District Meerut was purposively selected for present investigation. Being homogeneous of all the Blocks, two blocks were selected randomly i.e. Hastinapur and Sardhana. Three villages were selected randomly from each block. List of all the farmers of the selected villages was prepared according to their land holding size. A sample of 32 respondent having area upto 1-2 hectare were selected on the basis of probability proportional to their total numbers. Required primary data on crops, livestock and other allied enterprises was collected by personnel interviewed method and secondary data was also collected from various published sources. CACP cost concept and Linear programming is a systematic and accurate method of determining mathematically the optimum combination of enterprises or inputs so as to maximize the income or minimize the cost within the limits of available resources. Programming approach of the following form was used use to optimize the return from Sugarcane Based Farming System. Objective function –I (Maximization of income) n Maximize Z = Σ CjXj j=1 Where, Z = Net returns (income) variable cost in rupees Cj= Net return over variable costs per unit of 1161 Int.J.Curr.Microbiol.App.Sci (2018) 7(7): 1160-1166 j-th activity in rupees Xj = The level of j-th activity, respectively in both the season. The working capital availability was Rs. 49264 and Rs. 47658 respectively in kharif and rabi season. The sugarcane production is important crop for attaining maximum return by the marginal farms in the study area which was included as minimum area constraint and value was 0.45 ha. number limit on livestock unit was imposed for determining the potential of increasing income and employment. Subject to constraints N Σ aijxij j=1 ≤ bi Non-negative decision variable Resource utilization pattern for small farms Xij ≥ 0 Where: aij= amount of i-th resource required for the jth activity, bi = total available quantity of i-th resources. i = 1, 2, 3,……………………..m, resources) j = 1, 2, 3, …………………….n, activities) The farmer must decide how many hectares that should be allocated to each activity. So the decisions are: X1 = hectares allocated for paddy production. X2 = hectares allocated for Jawar production. X3 = hectares allocated for sugarcane production. X4 = hectares allocated for wheat production. X5 = hectares allocated for potato production. X6 = hectares allocated for mustard production. X7 = hectares allocated for oat production. X8 = number allocated for buffalo rearing. X9 = number allocated for cow rearing. Results and Discussion Optimum farm plan for small farms The linear programming formulation for small farms was presented in the in the Table 1, average land holding size and labour availability of small farm household in the study area was 1.44 hectare and 360 man-days The linear programming formulation was solved by using computer based MICRO SOFTWARE and results of existing and optimum resource allocation plan of small farms is presented in Table 2. In existing plan area under paddy, jowar, sugarcane, wheat, potato, mustard and oat were 0.35, 0.30, 1.02, 0.52, 0.42, 0.27 and 0.11 hectare respectively whereas all the area in optimum farm plan covered fewer than three crops viz., sugarcane, potato and oat with 0.45, 0.99 and 0.99 hectare respectively and other crops were not feasible in selected area due to their minor importance in returns. Similarly buffalo and cow were in number of 1.58 and 1.36 respectively in the existing farm plan but due to greater importance of buffalo in planning, it appears 9.24 in numbers in to optimum farm plan. Further linear programming resulted into a net return of ₹429103.94 in optimum farm plan as compared to ₹ 320906.10 in existing farm plan. There is an absolute improvement in net return which was 33.72 per cent higher than the existing farm plan. The land was fully utilized in optimum farm plan, whereas, requirement of labor man-days was 69.59 per cent higher in optimum farm plan than the existing farm plan. Analysis indicates that optimal farm plan seems more feasible because it create more opportunity for employment to the small farm families in the study area. 1162 Int.J.Curr.Microbiol.App.Sci (2018) 7(7): 1160-1166 Table.1 Matrix of linear programming model for small farms Crop Paddy (0.30) Jawar (0.21) Sugarcane (0.59) Wheat (0.35) Potato (0.24) Mustard (0.13) Oat (0.05) Cow* (1.1) KH L X7 Buffalo * (1.3) X8 Variable X1 X2 X3 X4 X5 X6 Kharif Land (ha) 1 1 1 - - Rabi Land (ha) - - 1 1 Kahrif Laboure (man-days) Rabi Laboure (man-days) Kahrif working capital (Rs.) Rabi working capital (Rs.) Minimum area (ha) 96 38 80 - - X9 X1 0 - - - - 1 1 1 - - - - - - 30 25 -1 - - 70 45 78 31 28 23 - -1 - - ≤ 360 32346 16421 30080 - - - 31317 26047 - - -1 - ≤ 49264 - - 27904 27579 63007 18028 30610 25083 - - - - ≤ 47658 - - - - - - - - - -1 ≥ 0.45 Net Return (Rs.) 60366 40608 113326 55082 75670 45556 - - - - 32 18328 38315 37599 R H L X1 1 KB RB X12 X13 Paddy (0.30) ≤ 1.23 27588 ≤ 1.23 ≤ 360 Table.2 Land allocation, income and employment generation under optimum combination of different enterprises in sugarcane based farming of small farms Variables Crop Land Allocation Labour Net Return Existing Optimum %∆ Existing Optimum %∆ Existing Optimum %∆ Paddy X1 0.35 0 -100 32.9 0 -100 21379.4 0 -100 Jowar X2 0.30 0 -100 11.40 0 -100 12301.5 0 -100 Sugarcane X3 1.02 0.45 -55.88 153.00 67.50 -55.88 115860.8 51115.05 -55.88 Wheat X4 0.52 0 -100 23.92 0 -100 28284.88 0 -100 Potato X5 0.42 0.99 135.71 32.34 29.70 135.71 32621.82 76894.29 135.71 Mustard X6 0.27 0 -100 8.37 0 -100 13171.41 0 -100 Oat Buffalo X7 X8 0.11 1.58 0.99 9.24 800.00 484.81 93.22 65.28 76.23 545.16 800.00 484.81 4117.74 57121.74 37059.66 334019.9 800.00 484.81 Cow X9 1.36 0 -100 3.3 0 -100 36046.8 0 -100 423.73 718.59 69.59 320906.1 429103.94* 33.72 Total %∆ - Percentage change over existing, 1163 Int.J.Curr.Microbiol.App.Sci (2018) 7(7): 1160-1166 (Appendix – I) Optimal value of the objective Function = 429103.95000 Activity Paddy Jowar Sugarcane Wheat Potato Mustard Oat Buffalo Cow Kharif Hired Labour Rabi Hired Labour Kharif Borrowing Rabi Borrowing Allocation Objective Contribution 0.00000 0.00000 0.45000 0.00000 0.99000 0.00000 0.99000 9.23906 0.00000 0.00000 -1.46519 275647.60000 305118.40000 61084.00000 41005.00000 113589.00000 54394.00000 77671.00000 48783.00000 37434.00000 36153.00000 26505.00000 -200.00000 -200.00000 -0.12000 -0.12000 0.00000 0.00000 51114.98000 0.00000 76894.35000 0.00000 37059.68000 334019.90000 0.00000 0.00000 293.03820 -33077.71000 -36614.21000 429103.94000 Objective Function Resources / Constraints Kharif land (ha.) Rabi land (ha.) Kharif labour(man day) Rabi labour (man days) Kahrif working capital (Rs.) Rabi working capital (Rs.) Minimum area (ha.) Type Slack 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 <= <= <= <= <= <= >= Utilization R.H.S. 1.44000 1.44000 360.00000 360.00000 49264.00000 47658.00000 0.45000 1.44000 1.44000 360.00000 360.00000 9264.00000 47658.00000 0.45000 Reduced Cost 25104.68000 2476.88300 0.00000 12872.08000 0.00000 14215.40000 0.00000 0.00000 2947.30900 -528.23500 0.00000 0.00000 0.00000 Shadow price 13765.35000 54635.04000 728.23500 200.00000 0.12000 0.12000 32448.48000 Sensitivity Analysis Activity Oat Sugarcane Potato Buffalo Rabi Hired Labour Kharif Borrowing Rabi Borrowing Resource/Constraint Kharif land (ha.) Rabi land (ha.) Kharif labour(man day) Rabi labour (man day) Kahrif working capital Rabi working capital Minimum area (ha.) Objective Incoming Variable Jowar Function 37434.0000 113589.0000 77671.0000 36153.0000 -200.0000 -0.1200 -0.1200 Incoming Variable Kharif land (ha.) Wheat Cow Mustard Jowar Mustard R.H.S. Outgoing Variable 1.4400 1.4400 360.0000 360.0000 49264.0000 47658.0000 0.4500 Lower Limit Rabi Hired Labour Potato Kharif Borrowing Rabi Hired Labour Oat 146037.5000 64798.9200 32525.5400 -509.0303 -0.5214 -0.4317 Kharif land (ha.) Rabi labour (man day Kahrif working capit Rabi working capital 50836.0500 0.0000 0.0000 0.0000 Lower Limit Outgoing Variable Upper Limit 1.3821 0.4500 85.0741 358.5348 -0.5400 1164 Upper Limit 34957.1200 Buffalo Rabi Hired Labour Rabi Hired Labour 11.2950 1.4590 361.7365 Kharif Borrowing Rabi Borrowing Rabi Hired Labour 324911.6000 352776.4000 0.4836 Int.J.Curr.Microbiol.App.Sci (2018) 7(7): 1160-1166 The adoption of improved technology had a much higher impact on increasing farm income. Similarly, the integrated crop and milk production showed a scope for generating employment on small categories of farms. Thus from the optimal plans for small categories of households, it could be inferred that there are significant potentials for income and employment generation in the study area. These could be achieved by making just a few adjustments in the existing farm plans, suggested by the developed optimal farm plans. Adoption of recommended technology even with restricted capital investment resulted in higher net farm income and better utilisation of human labour. With relaxation of capital constraint, more profitability could be generated with more opportunities for human labour employments. In conclusion, the central point of dispute revolves around the nature of the impact of new farming system on income generation among the farms. The change in cropping pattern, which is still in its transitional stage has lifted agriculture from decades of stagnation to a new threshold of growth and dynamism. The change in farming system has given rise to new hopes and aspiration to the farms regarding the future of agriculture. An empirical study has been done to know the actual impact of sugarcane based farming system on income and farm employment in Meerut district of Uttar Pradesh. In the small farms linear programming model included constraints were land ≤ 1.23 ha., labour ≤ 360 days, capital ≤ Rs. 111201, and minimum area ≤ 0.45 ha. In rabi and kharif season. In the further linear programming result for small farms rearing 9.24 buffalo in optimal plan compare to rearing 1.58 buffalo on existing plan that increase in returns which was 33.72 per cent higher than the existing farm plan and labour man days 69.59 per cent higher than the existing plan. 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