UC Davis

Recent advancements in the reproductive management of dairy cattle highlight the integration of multiple disciplines, including physiology, management, nutrition, genetics, economics, veterinary herd health, and production medicine, to improve reproductive performance. Generation of timely and cost-effective pregnancies is a key economic driver in dairy herds, influencing milk yield, income over feed cost, and culling decisions. Artificial insemination (AI) accelerates genetic progress, controls venereal diseases, and ensures safety. Estrous cycle synchronization programs, particularly timed AI (TAI), have emerged as cost-effective solution to improve pregnancy rates and reducing estrus detection needs. Despite the development of numerous controlled breeding programs, a thorough understanding of estrous cycle physiology and follicular wave dynamics is essential. Different synchronization programs enhance insemination and pregnancy rates in dairy cows and heifers. Genetic selection for reproductive traits has improved breeding strategies by emphasizing both productive and reproductive traits. Improved understanding of hormonal influences, estrous synchronization, and genetic selection has significantly enhanced reproductive performance. The goals of this thesis are to: 1) review the literature on the current status of knowledge of factors impacting effective reproductive management strategies and hormonal manipulations in dairy cattle; 2) assess the impact of increasing the dose of GnRH at the beginning of a CIDR Synch to improve ovulation and pregnancy in dairy heifers, and 3) to compare key reproductive outcomes in two reproductive programs with variable estrus detection length followed by OvSynch and to assess their relationship with the fertility traits genomic prediction for daughter pregnancy rate (GDPR) and the genomic prediction for cow conception rate (GCCR) in lactating Holstein dairy cows.