ABSTRACT The objectives of this work were to estimate the genetic parameters for the traits longevity (LG) and accumulated milk yield at 305 days (MY305) using a bitrait animal model and the single-step GBLUP method and estimate the genetic gain for LG through direct and indirect selection for MY305. We used 4,057 records of first lactations of Murrah dairy buffaloes, collected between 1987 and 2020, belonging to six Brazilian herds located in the states Ceará, Rio Grande do Norte, and São Paulo and 960 animals genotyped using the 90K Axiom Buffalo Genotyping (Thermo Fisher Scientific, Santa Clara, CA) to estimate the genetic parameters. The heritability estimate was 0.25 for MY305 and 0.13 for LG. The genetic gain for LG was 0.13 months under direct selection, and 0.14 months under indirect selection, which results in a relative selection efficiency of 11% under selection for MY305 compared with the direct selection. The genetic correlation between the two traits was 0.77, indicating that animals with genetic potential for high MY305 tend to live longer. The genetic trends for MY305 and LG were 0.22 kg/year and 5.20 days/year, respectively, indicating a positive response, which reaffirms its relationship with the high genetic correlation between the two traits.

ABSTRACT The objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattle.

The objective of this study was to estimate (co)variance components for weight at 550 days, average daily gain and an index with both traits, and to compare alternatives for evaluation and ranking of Nellore young bulls in pasture performance tests. The heritability estimates were 0.73, 0.31 and 0.44 for weight at 550 days, average daily gain and index, respectively. Animals were ranked according to their predicted breeding values or the phenotypic deviations in relation to the mean of the test. Although the correlations between breeding values and phenotypic deviations were high, there were differences in the number of animals selected in common when the selection criteria were the predicted breeding values or the phenotypic deviations. Mixed models are more appropriate than the least squares method and should be utilized in the evaluation of young bulls in performance tests.