Effect of bull sire selection strategies on competitiveness of dairy AI studs

Abstract

Artificial insemination (AI) studs need to have competitive breeding programs to stay in business. One way to be competitive is to use only the few top ranking bulls as sires of the next cohort of young bulls. This maximises average genetic merit of young bulls and increases the chance of producing outstanding bulls on progeny testing. Competitiveness of an AI stud with intense bull sire selection compared with a conventional stud was evaluated stochastically, by simulating the expected numbers of sons in the top ranking list. Utility theory and the probability of having no young bulls in the top ranks were used to consider risk. The maximum average number of bulls in the top ranks was achieved with use of the best bull sire and the number declined steadily as additional bull sires were used. Risk for the stud from using few bull sires was not high. Size of the stud had little effect on the results. With five competitors instead of two, risk was even less important because extra genetic merit has a higher utility when there is more competition for a limited market. Lower accuracy of bull sire selection (on sib records or on pedigree) was useful only if genetic trend was high. There is a conflict between the need for individual studs to be competitive by selecting few bull sires, and the long term need of the breed to retain genetic variation.