Genetic principal components for reproductive and productive traits in Holstein cows reared under tropical conditions.

The objective of this study was to compare the standard multi-trait model and five reduced-rank models fitted to the first principal components and genetic parameter estimates in order to determine the most appropriate method to model the covariance structure of reproductive and productive traits in Brazilian Holstein cows. Individual records of the following traits from 5217 cows were analyzed: 305-day milk yield (MY305), peak yield, milk yield per day of calving interval, days from calving to first estrus, days from calving to last service (CLS), calving interval (CI), and gestation length. Schwarz's Bayesian information criterion was used to compare the different models. The results indicated that four principal components were necessary to model the genetic (co)variance structure, reducing the number of parameters to be estimated. Analysis of genetic and phenotypic correlations showed that milk production-related traits were strongly correlated with each other (ranging from 0.74 to 0.99), while the correlation of these traits with the reproductive traits was weak (ranging from - 0.14 to 0.27). Heritability estimates for the traits ranged from 0.03 to 0.18. The reproductive traits CLS and CI and the production trait MY305 should be included as selection criteria in dairy cattle breeding programs because they are correlated with the first two principal components, retaining 91% of the genetic variability of the data.