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Title: | Essays on the Adoption and Impact of Climate Smart Agriculture Practices: Insights from Rural Farmers of Odisha |
Authors: | Tanti, Purna Chandra |
Supervisors: | Jena, Pradyot Ranjan |
Keywords: | Climate Smart Agriculture;Agricultural Extension;Perception to Climate Change;Access to energy |
Issue Date: | 2023 |
Publisher: | National Institute Of Technology Karnataka Surathkal |
Abstract: | Climate change endangers rural livelihoods by negatively impacting agricultural production through reduced crop yields, harvest loss, and increasing production costs. Odisha agriculture depends on rainfall and remains vulnerable to rising temperatures and uncertain precipitation. Climate-smart agricultural (CSA) practices have been advanced as a possible solution to adopt and mitigate climate change issues. This study addresses three objectives correlated with adopting Climate Smart Agriculture practices. The first objective is to evaluate the factors determining agricultural machinery. It examines the effect of agricultural machinery adoption on net agricultural income, household income, and household consumption adoption among rural farmers in India. The study draws on India Human Development Survey (IHDS) data of 10,000 households spread over 28 states of India to derive the extent of mechanization for each state in India. Concerning the multivariate probit model, climate change events and shocks induce farmers to adopt farm mechanization. The other significant drivers of agricultural mechanization include access to institutional credit, availability of extension services, and landholding size. ESR model revealed that adopting machineries has increased net agricultural income by 31%, household income by 19%, and food consumption by 5%. Given these demonstrable positive effects of mechanization in agriculture Administering a structured questionnaire survey among the 494 rural farming households of an eastern Indian state, namely Odisha, the first objective explores the key determinants of CSA adoption. The investigation will focus on one coastal district and two inland districts. In order to adapt to these weather anomalies, the respondents have implemented various CSA practices, including rescheduling planting, crop rotation, crop diversification, soil conservation, drought-resistant seeds, and agroforestry. This study uses a multivariate probit model to investigate the primary factors that influence the decision to implement CSA practices. According to the findings, perceptions of climate change, availability of extension services, and electricity for irrigation are the most important factors in adopting CSA practices. The sub-objective of this section focuses on the gender aspects of the adoption of CSA practices. The FGDs were undertaken in ten study area villages to understand the gender dimension of CSA adoption in the study area. iThe third objective is to examine the impacts of CSA practices on the productivity and income of the farmers. The current study is based on the cross-sectional household survey data collected from three climate-vulnerable districts in the semi-arid regions of Odisha, namely, Balangir, Kendrapara and Mayurbhanj. The impact of CSA practices' adoption on income and productivity was analyzed using propensity score matching (PSM) and two stage least square method(2SLS). Two instruments were used to remove self-selection bias and endogeneity, i.e., distance to extension and percentage of multiple adapters in a village. Both models show the positive and significant impact of adoption on the productivity and income of the farmers. There are few policy ramifications of these findings. Adopting CSA practices requires the farmer's involvement and communication with other farmers. Effective farmer-to-farmer extension programmes enhance adoption, productivity, and income. If we want to see more widespread adoption of CSA methods, we must see more frequent extension interaction and a more conveniently located extension office. |
URI: | http://idr.nitk.ac.in/jspui/handle/123456789/18006 |
Appears in Collections: | 1. Ph.D Theses |
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