Abstract
The inclusion of genetic groups in sire evaluation has been widely used to represent genetic differences among animals not accounted for by the absence of parentage data. However, the definition of these groups is still arbitrary, and studies assessing the effects of genetic grouping strategies on the selection efficiency are rare. Therefore, the aim in this study was to compare genetic grouping strategies for animals with unknown parentage in prediction of breeding values (EBV). The total of 179,302 records of weaning weight (WW), 29,825 records of scrotal circumference (SC), and 70,302 records of muscling score (MUSC) from Montana Tropical animals, a Brazilian composite beef cattle population, were used. Genetic grouping strategies involving year of birth, sex of the unknown parent, birth farm, breed composition, and their combinations were evaluated. Estimated breeding values were predicted for each approach simulating a loss of genealogy data. Thereafter, these EBV were compared to those obtained in an analysis involving a real relationship matrix to estimate selection efficiency and correlations between EBV and animal rankings. The analysis model included the fixed effects of contemporary groups and class of the dam age at calving, the covariates of additive and nonadditive genetic effects, and age, and the additive genetic effect of animal as random effects. A second model also included the fixed effects of genetic group. The use of genetic groups resulted in means of selection efficiency and correlation of 70.4 to 97.1% and 0.51 to 0.94 for WW, 85.8 to 98.8% and 0.82 to 0.98 for SC, and 85.1 to 98.6% and 0.74 to 0.97 for MUSC, respectively. High selection efficiencies were observed for year of birth and breed composition strategies. The maximum absolute difference in annual genetic gain estimated through the use of complete genealogy and genetic groups were 0.38 kg for WW, 0.02 cm for SC, and 0.01 for MUSC, with lower differences obtained when year of birth was adopted as a genetic group criterion. Grouping strategy must consider selection decisions and the number of genetic groups formed, in the way that genetic groups represent the genetic differences in population and allow an adequate prediction of EBV.
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