Impact of Integrated Farming System on Employment Generation: Analyzing Respondent Profile in the Konkan Region of Maharashtra, India

An integrated farming system is a biologically integrated system that integrates natural resources into farming activities through a regulation mechanism to achieve maximum replacement of off-farm inputs, secures sustainable production of high-quality food and other products through ecologically preferred technologies, sustains farm income, eliminates or reduces sources of current agricultural pollution and sustains the environment. This method not only ensures a high level of production while saving money on fertilizer but it also ensures maximum compatibility and organic matter replenishment through the successful recycling of organic residues and wastes generated through the integration of diverse land-based industries. Furthermore, for resource-poor farmers moderate increases in land productivity are no longer sufficient. As a result, competent resource management including optimal resource allocation is critical to reducing the risk of land sustainability. The Government of India's Ministry of Agriculture and Farmers' Welfare has placed a strong emphasis on the Integrated Farming System (IFS) as part of its ambition to double farmers' income by 2022. However, in our country, the planning and implementation of many enterprises in an integrated farming system lack a scientific and systemic approach. Furthermore, a thorough understanding of the component's interactions and interconnections would increase food security. The impact of an integrated farming system on doubling farmers' income was the primary goal of the current study. The study was carried out in the districts of Palghar, Raigad, Sindhudurg, and Ratnagiri in Maharashtra's Konkan area. Using multi-stage sampling approaches, 200 respondents in total were chosen. The “Ex-Post-Facto” research design was used for conducting the study. The data were collected through the personal interview. The data collected were processed and statistically analyzed by using statistical techniques like frequency, percentage, mean, standard deviation and chi-square test. Among the thirteen selected independent variables namely age, farming experience, major occupation, annual income, cropping pattern, livestock possession, information-seeking behavior, economic motivation, irrigation status and risk orientation were shown significant associations with the impact of integrated farming system while education, land holding and productivity level shows highly significant association with impact of integrated farming system in term of change in employment generation.