Assessment of the status of artificial insemination and its constraints in East Arsi Zone, Oromia Region, Ethiopia

Gedefa, T., Kebede, K., Yusuf, Y. and Gebreyohannes, G. 2025. Assessment of the status of artificial insemination and its constraints in East Arsi Zone, Oromia Region, Ethiopia. African Journal of Food, Agriculture, Nutrition and Development 25(2): 25946–25967.

Ethiopia's genetic enhancement efforts have included directly importing exotic cattle from other countries or introducing genes from an external source via artificial insemination (AI) to enhance the breed composition of local cattle. The study aimed to evaluate the status of artificial insemination and identify its constraints in the selected districts of East Arsi Zone, Oromia regional state. The data were collected from 301 farmers and 9 AI technicians (AIT) using semi-structured questionnaires. Five-year secondary data were used from the annual summary of the casebook to evaluate AI status. Data on AI status, satisfaction, breeding method, controlled mating and AI delivery were analyzed using Statistical Analysis Systems (SAS) chi- square procedures. Secondary data were analyzed using General Linear Model SAS methods. The ranking coefficient was analyzed using the R software Plackett–Luce model procedure. The study found that 43.52% of participants were dissatisfied with AI services, while 56.48% were satisfied. Furthermore, 72.43% of respondents indicated an increase in AI services, whereas 13.62% reported a decrease and 13.95% no change. The respondents' satisfaction with AI and AI status differed (P<0.05) among districts, but no difference (P>0.05) between the production systems. The secondary data revealed a gradual increase in AI delivery from 2018 to 2022. The average AI delivery was 2281.5±275.6 per year. While AI services did not differ (P > 0.05) across districts, there was a significant (P< 0.05) variation over time. About 55.48% of the districts' dairy producers used AI for breeding. Most respondents (61.79%) received AI from government administrations, while 36.21% received from government and private and only 1.99% obtained it from private suppliers. Breeding methods varied significantly across production systems (P<0.0001), but controlled mating and AI provision were non-significant. The farmers preferred neighbor bulls with estimated coefficients of 2.24 followed by their bulls (1.05) for breeding purposes. The respondents indicated that conception failure (0.72) and poor conception rates (0.56) were the biggest challenges for AI in the study areas. Transportation (2.89) was the main constraint in delivering AI services identified by AITs. Despite these challenges, there has been an increase in the use of AI in study areas over the past five years. Because AI is the only accessible technology for increasing dairy cow performance in the country, it is vital to address these challenges to increase AI utilization in the study regions. Focusing on semen quality is necessary to achieve a high conception rate per service. Supporting commercial AI businesses could improve farmers' access to services.