Determinants of the Adoption of Sustainable Land Management Practices among Smallholder Farmersa in Jeldu District, West Shewa Zone, Oromia Region, Ethiopia.
Land degradation is a major cause of Ethiopia’s low and declining agricultural productivity, continuing food insecurity, and abject rural poverty. The productivity of agricultural economy, which is the backbone of the country’s economy, is being seriously eroded by unsustainable land management practices both in areas of food crops and in grazing. Low land productivity due to land degradation in form of soil erosion is one of the leading challenges to improving the performance of the smallholder farming system sector in Ethiopia. In this context, the adoption of Sustainable Land Management practices/ technologies is quite crucial to increase agricultural productivity, ensure food security and improve the livelihoods of smallholder farmers. Farmers recommend various SLM practices/technologies for sustainable implementation, but adoption of such agricultural land management practices/ technologies is still very low. There is no clear understanding of the problems encountered by farmers in the adoption of recommended SLM practices/ technologies. Therefore, the main purpose of this study was to assess the socio-economic, institutional, psychological and biophysical determinant factors that influence adoption of SLM practices/technologies among smallholder farmers in Jeldu district in West Shewa zone. Primary data were collected through household questionnaires surveys, focus group discussions, key informants interviews and personal observations while secondary data were collected from relevant local authority reports and records. A total of 224 households were interviewed. Both Descriptive statistics and binary logistic regression model were used to analyze the data. The computed independent T-test for the mean income difference was statistically highly significance between adopters and non-adopters, suggesting that adopters were in better-off position to improve their livelihood. From the 18 explanatory variables entered into the model, 14 variables were found to be st
