Article-27
Eco. Env. & Cons. 21 (December Suppl.) : 2015; pp. (S149-S151) Copyright@ EM International ISSN 0971–765X
Resource use efficiency in wheat production in Narmadapuram division R. Narvariya, A. Sharma, A. Patidar, J.S. Raghuvanshi and D. Narvariya Department of Agricultural Economics and Farm Management, Rajmata Vijayaraje Krishi Vishwa Vidyalaya, Gwalior 407011, Madhya Pradesh, India (Received 11 May, 2015; accepted 10 July, 2015)
ABSTRACT This study was designed to measure resource use efficiency in wheat production of Narmadapuram division of central narmada vally region of Madhyapradesh state. In present investigation we use the double log type Cobb-Douglas type of production function. The sample of 216 Wheat farmers were selected from which input-output data collected based on 2012-13 rabi cropping season. Functional analysis of wheat crop revealed that Seed rate, fertilizers and manures, plant protection, irrigation facilities ,Human Labour,and Machine Labour, manure and fertilizers and, had the elasticity of 0.425**, 0.318**,-0.027*, 0.024, 0.415** and 0.251** respectively and was statistically significant. The value of MVP in respect of human labour (3.9), Machine labour (5.6), Seed rate (2.7), and fertilizers and manures (9.4) ,were more than unity level and the MVP value of irrigation facilities (0.4) and plant protection (0.1) were found to be less than unity level.
Key words: Wheat, Profitability, Resource use efficiency, Marginal value of product
Wheat (Triticum aestivum) is a staple food for more than 50%nof the world population. Wheat (Triticum species) is a crop of global significance. It is grown in diversified environments. It is a staple food of millions of people. Approximately one-sixth of the total arable land in the world is cultivated with wheat. Whereas paddy is mainly cultivated in Asia, wheat is grown in all the continents of the world. It supplies about 20 per cent of the food calories for the world’s growing population. Global wheat production touched 622.2 million tones in 2007-08. India is the second largest producer of wheat after China. Wheat has a distinct place among the food grain crops. Carbohydrate and protein are two main constituents of wheat. On an average wheat contains 1112% protein. Wheat is grown mainly in two seasons in the world viz., winter and spring. Considering the quality wheat has been divided into two categories *Corresponding author’s email :
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(1) soft wheat, (2) hard wheat. Triticum aestivum (bread wheat) is known as soft wheat and Triticum durum is known as hard wheat. In India mainly three species of Triticum mainly aestivum, durum and dicoccum are cultivated (Fig. 1) in which area is approximately 95, 4 and 1 per cent, respectively. Triticum aestivum is cultivated in all the regions of the country while durum is cultivated in Punjab and Central India and dicoccum in Karnataka. Wheat is the major crop grown in the state of Madhya Pradesh covering 4901.4 thousand ha. And production is 12703.2 thousand tones. Hoshangabad division is one of the important wheat growing divisions of Madhya Pradesh. It cover 488.4 thousand ha and the production of 2056.3 thousand qtl (year 2012). In Narmadapuram division, Hoshangabad and Harda are the selected districts. The present investigation aims to ex-amine cost and returns analy-
S150 sis of principle crop of Narmadapuram division In view of above investi-gation entitled “Resource Use Efficiency in Wheat Produc-tion of Narmadapuram Division” was undertaken with following objective. To estimate the Resource use efficiency in Wheat production.
Materials and Methods The present study was carried out In Narmadapuram division of of Madhyapradesh, where Wheat is the com-monly grown as rabi season crop by the farmers Narmadapuram division comprises of two districts namely, Hoshangabad and Harda. The data of 216 cultivators were collected and compiled for the year 2012-13.
Eco. Env. & Cons. 21 (Dec. Suppl.) : 2015 b) Marginal Value Productivity (MVP) The estimated production function underlying cropproduction enables us to evaluate the efficiency of prevalent factor proportions. The MVP was computed by the multiplying the coefficients of the given resource with ratio of the geometric means of the output to the geometric mean of the given resource. For example, the MVP of Xi would be, from the above production function the M.V.P. of each resource was worked out. The marginal productivity of particular input “Xi” at geometric mean of input and output expressed in following equation. MPVXi = bi •i i
Pxi
Resource Use Efficiency In present investigation we use the fallowing CobbDouglas type of production function - Resource use efficiency .The production function commonly used for estimation of the resource use efficiency. In today’s world problems, both economical and social, re-source and the resource efficiency play a vital role. The in-vestors have been concerned with increasing productivity of resources by introduction of new ones that lie higher technol-ogies. By replacing the existing production function by new ones that lie higher in output, plane, it is hoped that, this in-vestment leads to production of more output from the same quantity of inputs, or to the same outputs from few inputs (there by releasing resource for other economic activities). The Cobb-Douglas production function was used for estimating the resources productivity of variable resources used in selected crop. The Cobb-Douglas type of Production Function was used and is usually defined as follows. Y = a X1 b1. X2 b2. X3 b3. X4 b4. X5b5. X6 b6. Where, Y = Dependent variable (gross income in Rs) a = Constant X = independent variable X1 = Value of seed in Rs X2 = value of fertilizer in Rs. X3 = value of human labour in Rs. X4 = value of plant protection measures in Rs. X5 = irrigation charge in Rs X6 = value of machine labour in Rs. b1 …….b6 = Regression coefficient of concern variable
Where, •i = gross value of output (Rs.) = Factor of production i bi = Regression coefficient of Xi Pxi = Price of Xi By comparing the respective input prices with their mar-ginal values, fanners can decide as to whether they should increase or decrease the level of use of that, particular input of products. (c) Returns to Scale The returns to scale can be easily estimated from this type of production function. Thus, Returns to Scale = a1+a2+…. +an = Σ ai =1, 2…….n Therefore, the summation of the powers of all the input variables provided us directly with a ready estimate of the returns to scale as also the degree of homogeneity of the production function. The returns to scale are deceasing, constant or increasing, Depending on whether a, is less than, equal to or greater than one.
Results and Discussion Without having the functional analysis and estimating the marginal value productivity (MVPs) the existing levels of inputs, one cannot come to the conclusion that whether the input is being overused or underused in production and also the contribution of different resources in the production of crop. For this purpose, as mention earlier, the Cobb-Douglas type of production function was fitted to the data
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and the estimates elasticity’s of different inputs are obtained at the same are presented in Table 1. Table 1. Coefficient of different resource use in Wheat Production No.
Input
1 2 3 4 5 6 7 8 9
Constant Seed rate Fertilizer and manure Plant protections measures Irrigation charges Human labour Machine labour R2 Returns to Scale
Coefficient 0.026 0.425 ** 0.318 ** -0.027* 0.024 0.415** 0.251** 0.965 1.408
ute to the extent of 96 per cent of the total variation in gross returns. Marginal Value Product (MVP) The result of production function analysis in terms of Marginal Value Product are presented in table 2
Conclusions 1.
2. 3.
It can be observed from the above Table 1 that seed rate, fertilizers and manures, plant protection, irrigation facilities, Human Labour, and Machine Labour, had the elasticity of 0.425 **, 0.318 **, -0.027*, 0.024, 0.415** and 0.251** respectively and were statistically significant. This means that one per cent increase in investment on these resources would contribute that percentage increase in wheat yield. The values of the elasticity’s of these variables reveal further scope for utilization of these inputs. The return to scale was more than unity (1.408) indicating increasing returns to scale. The coefficient of determination (R2) gives an idea about the proportion of the total variation in yield explained by the selected variables. For Wheat crop the value of R2 was 0.965 this has indicated that the selected variables contribTable 2. Marginal value product Sr. No.
Inputs
1 2 3 4 5 6
Seed rate Fertilizer and manure Plant protections measures Irrigation charges Human labour Machine labour
MVP 2.7 9.4 0.1 0.4 3.9 5.6
4.
The MVPs of the seed rate, fertilizer and manure, machine and human labour im-plies the profitable economic returns on investments on these resources. The economic efficiency of selected Wheat growers was 96 per cent. The average allocative efficiency of the selected Wheat growers was 90 percent. The study implied that the output of average farmers could be increased by adopting the allocation of resourc-es fallowed by the best practiced farmers.
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