FACTORS AFFECTING ADOPTION OF FARM MECHANIZATION IN RICE FARMING IN SOME SELECTED AREAS OF BANGLADESH

Abstract

Rice is cultivated all the year round in Bangladesh. The sustainable growth of the agricultural sector critically depends on the adoption of improved, scale-appropriate and ecofriendly technologies which includes using scale-appropriate new agricultural machinery. The specific objective of the systemic study was to assess the socioeconomic

profile of the rice farmers, to identify the factors affecting the adoption of farm mechanization for rice cultivation and to identify the constrains of adopting farm mechanization. A structured questionnaire was used for data collection from adopters and non-adopters of farm mechanization from the rice cultivators of several villages of Homna and Meghna upazila in Cumilla district. To understand the factors affecting farm mechanization, econometric models like logistic regression technique was used. Results from the study shows that majority of individuals were between the ages of 50 and 59 which is 33 percent of the population, among the population the bulk of farmers in each upazila have a 1-5 years of education who are 60 percent of the respondents. About 31 percent of the respondents got training where 69 percent didn’t and altogether 23 percent of the respondents had membership of different social and agricultural groups. A significant number (60 percent) of respondents had a medium experience level in case of adopter category. in case of non-adopter category 63.34 percent of respondents had a high experience level. On an average, about 48 percent of the respondents recieved extension contact when 52 percent did not. About 67 percent of the respondents had allowed women members in rice field from when 33 percent were not. Among the variables taken for estimating the adoption of farm mechanization, the most affecting and significant factors were education, farmer’s training and field visit by the extension workers. Poor buying capacity and lack of training act as major constraints which can be solved by proper financing and training programs.