Efficiency of Artificial Insemination Using Frozen Semen in Black Bengal and Ganjam Goats Under Field Conditions

A study aimed to determine the efficiency of artificial insemination (AI) in upgrading the local goats under field conditions was undertaken in Bihar and Odisha. From 2727 AI conducted between 2019 and 2024 in five Cattle Development Centres (CDCs), data of 2691 AI were used for the evaluation of fertility traits (conception rate and litter size). A logistic regression model was used to assess the effects of sire breed, technician skill and month of insemination. The overall conception rate was 41.54% with a litter size of 1.54. The breed of sire had significant (P<0.01) influence on conception rate, 30% higher odds of conception with Black Bengal semen as compared to Ganjam semen (OR: 0.70). AI technician skill, as represented by CDC, also had significant (P<0.01) effect, with 31% variation in conception rate across centres (OR: 0.94-1.31). The month of insemination influenced conception rate (P<0.05), with lower values during the June to December (OR: 0.46-0.69). Litter size varied significantly (P<0.01) among AI centres from 1.25 to 1.94, with higher values in Bihar centres. The findings highlighted the important role of sire selection, AI technician skill and month of insemination in optimising AI success.