Determinants of vulnerable group of Madhya Pradesh developing climate change strategies for Sustainable Agriculture practices: Discrete Analysis using Logit Model

Jay Anand
Karthick Radhakrishnan
Naitik Sharma
Noor Hasan
Binu Mathew
Ashwini Upadhyay

Abstract

The present study has focused to analysed determinants at field level climate resilient practices adopted by the vulnerable community in Madhya Pradesh. The model used data of a cross-sectional survey of 681 farm beneficiaries who have benefited under the Sustainable Livelihood for Adaptation and Climate Change (SLACC) project. The SLACC project was carried out in two districts of Madhya Pradesh (Central-India). The 13 logit models were performed which impacts the decision making of the farmers to enhance the exiting farming practice at the field level. Independent variables used for this study are socio-economic variable, credit accessibility, farmland holding, gender etc. which attracts farmers towards sustainable practices. The major finding of this exercises shows a positive relationship between the adoption of ‘line sowing’ of rice and ‘SRI’ (System of Rice Intensification), and the number of years of farming experience The credit accessibility results are positive significant where farmers have to adopt major farm activities like deep ploughing, seed replacement, zero tillage etc. combat the climate change vagaries. More interestingly, organic manure has been adopted by the vulnerable groups higher than the others where results are also validated from the ground level information. The promotions of above interventions require more focus policy driven steps to bifurcate different vulnerable groups under a cluster approach for effective credit diffusion to address Climate Resilient Practices.

How to Cite
Jay Anand, Karthick Radhakrishnan, Naitik Sharma, Noor Hasan, Binu Mathew, & Ashwini Upadhyay. (2019). Determinants of vulnerable group of Madhya Pradesh developing climate change strategies for Sustainable Agriculture practices: Discrete Analysis using Logit Model. Journal of Innovative Agriculture, 6(2), 1-13. https://doi.org/10.37446/jinagri/6.2.2019.1-13