Influences of progeny test programs on genetic evaluations of young sires

Our purpose was to examine differences among AI progeny test programs in their effectiveness in identifying elite young sires for milk and protein. Data were from 6238 Holstein sires in five animal model evaluations of the USDA from January 1995 to February 1997. Bulls were required to be < or = 8 yr of age and to have > or = 10 daughters in production at the time of the evaluation. Bulls in AI programs were placed in nine groups based on affiliation with major AI organizations; from these nine groups, bulls with daughters averaging < 150 DIM and bulls sampled in > 100 herds were placed in two separate groups. Bulls sampled in organizations with controller numbers > or = 30 and bulls that had no connection to a sampling organization formed two additional groups. We also classified bulls by sampling codes of the National Association of Animal Breeders. A model predicting daughter yield deviation included effects of organization or sampling code, parent average (free of progeny information), and the interaction of organization or sampling method and parent average. When all data were used, a common intercept for milk was appropriate for all sampling methods, but the slopes differed (R2 = 0.44). Neither a common intercept nor a common slope was appropriate for protein. When data were restricted to the nine major organizations, a common intercept and slope were appropriate for milk, and R2 decreased to 0.14. A common intercept and slope were found for protein, and R2 decreased to 0.15. We detected no important differences in response to pedigree selection among progeny-testing methods used by major organizations that provide semen, but a difference was detected among the sampling codes of the National Association of Animal Breeders.