Factors Influencing Adoption of Artificial Insemination by Smallholder Livestock Farmers in Dryland Production Systems of Kenya

Abstract

Increasing human population in recent decades has mounted pressure on food supply including livestock products. Livestock is the main source of livelihood to the poor households in the drylands of sub-Saharan Africa (SSA) such as parts of Kenya. Therefore, increasing its productivity is necessary to improve the welfare of poor rural households in the arid and semi-arid lands (ASALs). One of the viable ways to improve livestock productivity is by embracing the utilization of artificial insemination (AI) services. However, empirical evidence on level of AI uptake in ASALs remains scanty. In order to address this knowledge gap, the current study assessed factors influencing the uptake and intensity of AI adoption by the smallholder livestock farmers in dryland production systems of Kenya. The study used primary survey data that was collected through structured questionnaires administered to 398 randomly selected smallholder livestock farmers. The double-hurdle model (comprising probit and truncated regressions) was applied to analyse factors influencing the adoption and intensity of use of AI technology by smallholder livestock farmers. The results showed that, the overall adoption rate was 13.3%, while it was 21% and 1.8% in Makueni and Kajiado Counties, respectively. The probit regression results indicated that, access to extension services, age of household head, education level of household head, contract farming and cattle farm size had positive influence while, household size, off-farm employment, access to information, group membership and distance from home to nearby open-air livestock markets had negative influence on AI adoption. The truncated regression results revealed that, distance from home to nearby AI centre, household size, and access to information positively influenced the extent of AI adoption. On the contrary, dishonesty of the service providers, education level of household head and distance to nearby livestock markets had negative effects on extent of AI adoption.

Based on the low adoption rate found in the study area and the significant variables, the study recommends application of information communication technology (ICT) such as the use of mobile messaging system to promote extension services, training and dissemination workshops to smallholder farmers, promotion of pastoral education in Kajiado and expansion of AI centres as policy options to encourage the adoption of AI technology in the drylands of Kenya. Key words: livestock farmers, drylands, artificial insemination.