Success rate of artificial insemination, reproductive performance and economic impact of failure of first service insemination: a retrospective study

Abstract

Abstract Background A retrospective cohort study using a 10 year artificial insemination (AI) and cow reproductive performance data was conducted to study the success rate of AI; associations between effectiveness of AI and breed, AI season and, number of service per conception, and economic impact of failure of FSC in Dessie town, Dessie zuria and Kutaber districts. A total of 3480 dairy cows’ AI and reproductive performance records which were performed between 2003 and 2013 in the three selected districts of South Wollo were used. The economic losses and costs for cows that failed to conceive at their first AI associated with the larger number of days open were estimated. Result The prevalence of conception has a statistically significant difference between breeds of cows (P = 0.019). The non-return rate for first service was 58.54%. The median days to first service (DFS), inter-service interval (ISI) and gestation length (GL) were 126, 30 and 278 days respectively. Whereas, the mean + SD days open, calving interval (CI), number of inseminations (NOI) and number of services per conception (NSPC) were 147.2 ± 60.26, 424.5 ± 60.55, 1.14 ± 0.38 and 1.15 ± 0.39 respectively. Based on AI season there was a significant difference in conception between winter and spring (P = 0.021). There is a 45.04 days extension in the mean calving to conception interval in cows that did not conceive at their first AI but conceived by 2nd and 3rd AI than in cows that did conceive at their first AI. A total of 21,665.3 ETB extra costs was spent on reproductive treatment and other management for cows that failed to conceive at their first AI but conceived by second and third service. In cows that did not conceive totally the owner losses on average 473.7 ETB per cow per day extra costs until the cows will be culled. Conclusion Therefore to increase the conception rate and decrease the economic loss the owners of the dairy cows should supervise the cows regularly and should be trained on how to identify cows on estrous, the AI technicians should be trained to conduct the AI service accurately.