An Empirical Investigation of Farm Mechanisation Adoption in Betul District of Madhya Pradesh

This article aims to examine the extent of farm mechanisation and its determinants, with a particular emphasis on the Betul district of Madhya Pradesh. Betul is a tribal district of Madhya Pradesh. We used the stratified random sampling technique to conduct a survey of 150 farmers from the Chicholi tehsil in the Betul district, selecting 30 farmers from each of the five villages within the tehsil. We created a composite farm mechanisation index (CFMI) to assess the extent of farm mechanisation among the farmers. Subsequently, we conducted a regression analysis with the CFMI cut-off score as the dependent variable in order to identify its determinants. Additionally, we estimated a multinomial logistic regression model by classifying CFMI scores into low-, moderate- and high-mechanisation categories as dependent variables. The findings indicated that 40%, 42.67% and 17.33% of farmers were classified as farmers with low, moderate and high levels of mechanisation, respectively. The multiple regression results indicated that farm mechanisation scores are significantly influenced by factors such as the sex of the family head, caste category, higher education level and farm size. Farm mechanisation scores are negatively impacted by female family heads and Scheduled Caste and Scheduled Tribe classification categories. Farms managed by women are more likely to fall into the low farm mechanisation category, while those with higher education and larger farms are more likely to fall into the high farm mechanisation category. Consequently, special programmes can be developed by the authorities to educate and train female farmers and other marginal farmer communities to promote more sustainable and inclusive agricultural development.