Estimating Impact of Conventional and System of Rice Intensification (SRI) Methods of Rice Production Management on Sustainable Livelihood Generation in the Context of Climate Change in Maharashtra, India: A Factor Analysis
S.N. Panchabhai, Saumyesh Acharya, T. K. Mandal, Rahul Tayade
International Journal of Environment and Climate Change · pp. 673–681 · Published 23 Mar 2024
10.9734/ijecc/2024/v14i34075Abstract
The global agricultural community has been preparing to face the imminent threat posed by climate change as projections by scientific communities complement the fact that food production will be affected adversely in the near future. The Indian subcontinent has not been explicit about the effects of natural disasters like floods and cyclones caused due to climatic changes. The aberrant weather patterns along with the inconsistent output of monsoon create unprecedented challenges for the rice-dominated farming system to thrive. It directly impacts the livelihood of the farmers making them economically vulnerable. Thus, it has become necessary for the research community to explore different causal dimensions related to rice production and suggest remedies for the constantly changing agroecosystem. This study aimed to investigate different indicators of impact on sustainable livelihood generation through rice production management in light of climate change in both conventional as well as SRI methods of rice production. An ex post facto research design was adopted for conducting the study. Purposive sampling was used to select the state, district, and talukas keeping in view the backwardness and agricultural status of the area of the study. Using a simple random sampling method, two hundred (200) respondents were selected from two talukas of the Bhandara district of Maharashtra. In case of results found in conventional method of rice production, the variables, Water management, Farm size, Education, Irrigation index%, Selling% and Risk orientation have contributed 9.996 per cent of variance and clubbed into Factor 1. On the other hand, in the case of SRI method, Factor 1 has the following variables i.e., Farm size, Family income primary, Education, Primary occupation, Mass media exposure, Family education status and Sowing time which has contributed 9.54 per cent of variance and has been renamed as ‘Family capability’.
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