Diversity And Local Uses Of Woody Vegetation In Mined Arid And Semi Arid Lands Of Kimwarer, Kerio Valley, Kenya.

ABSTRACT

Despite Ethiopia possessing the highest number of livestock in Africa, its benefit to the country and smallholder farmers is small. This is to a large extent attributed to the dominance of low producing local cattle breeds. Though the government introduced Artificial Insemination (AI) technology to improve this condition, the adoption rate by smallholder farmers is still low. The main objective of this study was, therefore, to examine the adoption of AI technology by smallholder dairy farmers in Lemu-Bilbilo district, Ethiopia. The specific objectives were to characterize adopters and non-adopters of AI, to determine factors affecting adoption of AI and to determine the extent of adoption and factors affecting the extent of adoption. Purposive selection of the area and random sampling procedures were employed to select a sample of 196 smallholder dairy farmers. Data was collected using interview schedule via semi-structured questionnaires. The data was analyzed using Statistical Package for Social Sciences and STATA. Adopter and non-adopter farmers were significantly different with respect to education level, off-farm income, membership in dairy cooperatives, extension contacts, experience with crossbreeds, feeding concentrates to cows, access to credit, income from milk products sales and distance from AI station. The double-hurdle model was used for econometric analysis whereby the two stages were run separately as Probit and truncated regression, respectively. Contacts with extension agents, access to credit, income from milk sales, feeding concentrate to cows and family size influenced the probability of adoption without affecting the extent of adoption. While membership in dairy cooperatives and off-farm income positively affected the probability and extent of AI adoption, distance from AI station and access to crossbred bull services influenced both variables negatively. A further walking distance of one hour to the AI station was associated with 27% and 14.4% reduction in the probability and extent of adoption, respectively. Membership in dairy cooperatives and off-farm income can be instrumental in AI adoption due to milk market guarantee and the strengthening of financial capacity from off-farm income. Farmers located at farther distances from AI station and those with access to crossbred bulls preferred to use bulls than AI. Access to AI should be improved by expanding AI stations throughout the district along with training more AI technicians. Awareness creation especially on the difference between using AI and bull service must be done. Deploying adequate number of extension workers, educating farmers in farmers' training centres and field day visits can be the way forward. Dairy cooperatives and microfinance institutions must be established and strengthened. Ways of milk marketing at farm-gate should be designed, infrastructural development (especially road) should be considered.