An Assessment of Net Returns from Rice Production Practiced through Conventional and System of Rice Intensification (SRI) Methods in the Light of Climate Change in Bhandara District of Maharashtra, India

Abstract

Indian farming witnessed surplus production of cereals along with other food commodities. The production of rice across the Indian subcontinent has a subsistent impact on achieving food security and attaining judicious socio-economic growth for the farming community. However, it also faces certain challenges and difficulties. The phenomenon of climate change has been creating a menace against the sustainable growth of food crops. Due to this, it has become necessary to assess the economic impact of farmers practicing rice crops in terms of net returns from rice. By applying ex post facto research design, this study aimed to estimate the inter and intra-level of interaction between sets of predicted variables, Net returns from rice (both conventional and SRI methods), and predictor variables (x1-x35) and to generate policy at the micro-level. To conduct the study, the State, District, Blocks, and Villages were selected using purposive sampling techniques. Two hundred (200) respondents were selected from two talukas of the Bhandara district of Maharashtra using a simple random sampling method. For the purpose of data analysis, following statistical tools were used: Coefficient of Correlation, Stepwise regression analysis and Path analysis. The correlation coefficients found that farmers having a higher level of education have been showcasing higher net returns from rice produced by conventional methods. Regression results implied that 35 causal variables together have contributed 32 percent and 83.8 percent of the variance in the consequent variable, net returns from rice (y) practiced by conventional and SRI methods respectively. The results of a path analysis revealed that the variable farm size has got the highest indirect individual effect on net returns from rice practiced by both the conventional and SRI methods.