No abstract

ABSTRACT. Random regression models have been used in evaluating test-day milk yield, providing accurate estimates of genetic values in animals. However, herd evaluation with only information from the first lactation may not be the best option from an economic perspective. Other factors should be taken into account, particularly other lactations. Our objective in this study was to analyze the genetic divergence between the first four lactations of Alpine goats. The RENPED software was used to perform descriptive statistics, check for errors in pedigree, recode the data, and for Pearson's and Spearman's correlations. The WOMBAT software was used to estimate the variance components and predict the breeding values. The CALC software was adopted to calculate the percentage of coincidence between the ranking of the animals and the animals kept in common at each lactation evaluation. The results show that selection using only the first lactation in small herds with a low degree of technology can be employed as a palliative measure, in view of the difficulty in evaluating all lactations. However, the selection of breeding goats and the production of catalogues should not be based only on the first lactation, because the results demonstrate inversions in the classification of the best breeders when other lactations are analyzed.

Body weight records of 231,416 Nellore females obtained from the Brazilian Association of Zebu Breeders were used to determine a linear combination between visual appraisal scores (body structure, precocity and muscling) using principal components analysis (PC), and to verify their genetic association with body weight at 12 months (BW) and age at first calving (AFC). The mixed linear model included the fixed effect of the contemporary group and the linear and quadratic effects of age at calving, random effects of genetic additive, maternal environment and temporary environment. Heritability estimates for BW, PC and AFC were 0.51, 0.30 and 0.17, respectively. Genetic additive correlations between BW and PC; BW and AFC, and PC and AFC were 0.48; -0.31 and -0.55; respectively. Spearman's correlations for the best-ranked bulls based on PC prediction were positive between BW and PC and negative among the other combinations. Heritability estimates and correlations indicate potential genetic gains for BW and CP with reduced AFC in cows. The use of PC allows positive responses on precocity and body weight development.