Region-wise per hectare resource use structure and yield gap in castor and rapeseed-mustard in Banaskantha district

Introduction

In India, there are two major sources of Oilseeds i.e. Primary and Secondary. Primary sources are made combining the edible group [(Groundnut, Rapeseed (Toria, Mustard and Sarson), Soybean, Sunflower, Sesame, Safflower and Niger)] and non-edible group (Castor and Linseed). Similarly, secondary sources have been established combining edible group (Seasonal crops: Cottonneseed, Ricebran, Maize germ, Watermelon, Plantation crops: Coconut, Red-oilpalm, Tree borne oilseeds: Sal seed, Mahua, Mango-kernel, Cheura / Phulwara, Kokum, Dhupa, Simarouba) and non-edible group (Seasonal crops: Mesta seed, Tobacco seed, Plantation crops: Rubberseed, other Tree Borne Oilseeds: Neem, Karanj, Pilu or Khakan, Palash, Nahor, Undi, Pisa, Wild-apricot, Rattan-jyot, Maroti, Jojoba, etc). Castor crop cultivated in kharif season mainly in India but it is also cultivated in rabi season. Castor contains 35 to 58 per cent oil. Castor seeds are mostly used to make castor oil, which is utilized in lubricants, medicines, and the cosmetics industry. Rapeseed-mustard are major rabi oilseed crops of India. The oil content varies from 37 to 49 per cent. The seed and oil are used as condiment in the preparation of pickles, curries, vegetables, hair oils, medicines and manufacturing greases. Mustard oil, which is widely used for cooking in many parts of India; it is extracted from crushed mustard seeds.

Methodology

The crops were selected based on the highest triennium average area as per the year from 2016 to 2018. Anonymous (2022) [2] . Primary data were collected through the sample survey method. Two talukas were selected purposively for each crop from the Banaskantha district for the study, viz., for the castor crop, Bhabhar and Kankrej taluks were selected, and for the rapeseed-mustard crop, Tharad and Dhanera taluks were selected from the Banaskantha district. These talukas were selected based on their highest triennium average area occupied as per the year from 2019 to 2021. And the data of these talukas were collected from each district, Head Office of Agriculture Department. Four villages were selected randomly from each taluka, and from each village, ten farmers were randomly selected. Thus, a total of 160 farmers were selected randomly for the study.

Resource use costs and returns structure

The standard cost concepts such as Cost 'A', Cost 'B' and cost 'C' was used for estimation of costs and returns.

Functional analysis

The relationship between output and factors determining the output levels in oilseeds production was estimated by using the following Cobb-Douglas type of production function. As it gives specific scales of returns i.e., diminishing, increasing or constant. www.extensionjournal.com

The logarithmic form of the function, Log Y = Log a + b1 Log X1+b2 Log X2+……+ bn Log Xn + u Log e

Selection of input variables

While fitting the production function in respect of selected oilseed crop, following seven inputs were considered as important factors responsible for contributing to the production of these crops.

Where, Y = Output of main produce (q ha -1 ) a = Intercept. X1 = Human labour (man days ha -1 ) X2 = Bullock power (pairs days ha -1 ) X3 = Machine power (hr ha -1 ) X4 = Manure (q ha -1 ) X5 = Nitrogen (kg ha -1 ) X6 = Phosphorus (kg ha -1 ) X7 = Potassium (kg ha -1 ) U = Error term bi΄s = Regression coefficients of respective variables

Estimation of marginal value product

The marginal value products (MVP's) of the individual resource was estimated and compared with the marginal cost (MC). The MVP of resources was estimated by using the following formula,

Marginal value product (MVP) of X1 = b1 Py

Where, bi = Elasticity of production of i th input Y = Geometric mean of output X = Geometric mean of of i th input Py = Per unit price of output (₹) Based on Table 3, results revealed that the value of coefficient of R 2 was estimated as 0.85 at overall level. In case of castor human labour was significant at 5%, machine power was significant at 10% level and manure was significant at 1% level which indicated that there is scope to increase the use of these resources to increase the output. www.extensionjournal.com Other inputs like nitrogen was negatively significant at 10% level, phosphorus was negatively significant at 1% level indicates that these resources decrease the output with increase their input level. Marginal value product indicated that human labour, machine power and manure were higher than other resources. So, it indicates that profitability should be maximized by increasing these resources. According to Table 4, results indicated that the value of coefficient of R 2 was estimated 0.80 at overall level. Regarding rapeseed-mustard, human labour was significant at 10% level and machine power was significant at 1% level which showed the possibility to expand the utilization of these resources in order to increase the output. Other inputs were negatively non-significant which revealed that these resources decrease the output with increase in their input level. Marginal value product revealed that human labour and machine power were higher than other resources. Therefore, it implies that increasing these resources should maximize profitability. [3] . [5] .

Yield gap analysis

Yield gap analysis for castor and rapeseed-mustard in

Conclusion

The study found that the cost of cultivation was higher on www.extensionjournal.com small farms for castor and rapeseed-mustard in Banaskantha due to higher unit costs of raw materials. Marginal value product analysis highlighted that human labor, machine power, and manure were key drivers of profitability in castor, while human labor and machine power were critical for rapeseed-mustard. Yield gaps in both crops indicated lower farmer yields compared to research station and demonstration yields, primarily due to soil fertility differences, climatic variations, and agricultural practices in castor, and soil moisture, rainfall, sowing time, and pest issues in rapeseed-mustard. Improving resource use and addressing these constraints can enhance productivity and profitability.

References

1. Anonymous. Directorate of Oilseeds Development India. Available from: https://oilseeds.dac.gov.in/Introduction.aspx. Accessed on: 11 Jun 2023.
2. Prajapati PJ, Joshi NS, Patel ML, Parmar VS. Yield gap analysis through front line demonstration in castor. Int J Curr Microbiol Appl Sci. 2018;7(11): ISSN: 23197706.
3. Roy A, Sarkar S, Bera B. Estimation of cost of cultivation, profitability in different farm sizes as well as growth and instability of mustard in West Bengal. J Crop Weed. 2022;18(3):273-287.
4. Singh M, Poonia MK, Sharma KM, Goyal MC, Kumhar BL. Yield gap analysis of mustard crop: A case study of village Chomakot in Kota district. Chem Sci Rev Lett. 2017;6(22):671-675.