Exploring Diff erent Model Structures for the Genetic Evaluation of Dairy Bull Fertility

Th e aim of study was to investigate diff erent models for the evaluation of dairy bulls for male fertility. A dataset containing single insemination records performed on Brown Swiss cows and heifers reared in Eastern Italian Alps was used. Th e outcome variable (successful/ unsuccessful) was analyzed as binary trait. In the fi rst step raw conception rate was computed for each service sire, as the mean of the outcome of all his insemination events. In the second step Bayesian threshold sire models were implemented via Gibbs sampling. Diff erent models increasing in complexity were fi tted, in order to obtain variance components and sire solution estimates. Results showed that genetic variance for direct eff ect(s) on conception rate is low (repeatability=0.014; heritability=0.009-0.073) and raw conception rate is poorly related to solutions from prediction models. If the service sire is a diagonal eff ect, rank correlations with raw conception rate are about 0.81-0.84, while those decrease to 0.74-0.78 if service sires are related by a relationship matrix, and is null (-0.01-0.06) if is the sire of the service sire to account for the direct genetic eff ect. Service sire fertility (sire of service sire effect) has been proven to be a diff erent trait to embryo survival (service sire eff ect) giving rank correlation of 0.11-0.24. In conclusion phenotypic and genetic diff erences in male fertility among the service sires exist, and should be monitored thought a reliable evaluation system.