Abstract:
Artificial insemination is a biotechnology used to improve genetics in dairy cows and other farm animals. A cross-sectional study was conducted to assess the efficiency of artificial insemination services, evaluate semen quality, and identify constraints in selected districts of the Central Gondar zone, north-west Ethiopia, from February 2024 to July 2024. Semi-structured questionnaires were administered to 373 artificial insemination beneficiaries using systematic random sampling methods, while 18 Artificial insemination technicians and 34 animal health and production professionals were selected using purposive sampling methods. Additionally, 31 straws of semen were examined for individual progressive motility, viability, and morphological defects. Field practices of AITs, as well as conditions for semen handling and storage, were also observed. The data was analyzed using STATA software (version 17) and summarized using descriptive statics and a chi-square test. The results showed that out of the 373 AI users, 220 (58.9%) received AI services regularly, while 153 (41.1%) experienced interruptions due to various reasons. Of the AI users, 197 (52.8%) were not satisfied with the overall AI services. The major challenges identified were repeat breeding, failure of cycling, lack of semen and liquid nitrogen, shortages of feed, reproductive diseases, insufficient training and incentives for AI technicians, poor semen quality, improper semen storage conditions, limited availability of technicians, and the distance from AI service centers. The overall mean (±SE) individual progressive motility, viability, and normal sperm cell percentage for frozen bull sperm were 48% (±4), 47% (±4.86), and 71% (±6), respectively. Motility was significantly (p<0.05) affected by districts, bull ID, breed, batch number, and storage day length. Sperm viability was also significantly (p<0.05) affected by districts, bull ID, breed, and batch number. Similarly, normal sperm cell percentage was significantly (p<0.05) affected by districts and Bull ID. During the study period, the average conception rate was observed to be 45.5%. In conclusion, the efficiency of AI services in the study areas was found to be limited. Improvements could be made by enhancing the capacity of AI technicians, ensuring a consistent supply of AI materials, improving semen handling and storage practices, and addressing dairy health issues.
