CLUSTERS DE ROBUSTEZ COMO CRITÉRIO DE SELEÇÃO NO MELHORAMENTO GENÉTICO PARA MITIGAÇÃO DE IMPACTOS DAS MUDANÇAS CLIMÁTICAS

Mudanças climáticas são previstas para as próximas décadas e, consequentemente, seus impactos na pecuária bovina, sendo a seleção nos rebanhos uma maneira de amenizá-los. Este trabalho teve como objetivo desenvolver um sistema de seleção baseado nos parâmetros genéticos gerados por modelos de norma de reação adaptativa em bovinos da raça Nelore. Foram utilizados dados genealógicos e de crescimento fornecidos pela Associação Brasileira de Criadores de Bovinos. Definiu-se um gradiente ambiental baseado em valores médios de grupos contemporâneos padronizados. Para a predição de coeficientes das normas de reação adaptativas utilizou-se a regressão aleatória com polinômios cúbicos para pesos aos 450 dias com análise de sexos separados. Foram calculados os valores genéticos dos diferentes indivíduos em função de um gradiente ambiental utilizando o software BLUPF90. Os indivíduos foram classificados considerando coeficientes que gerassem normas com valores genéticos elevados e com menor variação ao longo do gradiente ambiental. Compensou-se, então, a elevação do valor genético e a sua robustez, criando clusters de robustez (CRs) com base na comparação direta entre os coeficientes. Os resultados da classificação mostraram que a seleção de indivíduos das classes de maior robustez devem gerar progênies com menor sensibilidade ambiental, visto que os coeficientes são componentes genéticos aditivos. Conclui-se que a seleção por clusters de robustez é uma forma de amenizar os impactos produzidos nos sistemas de produção por alterações nos ambientes de criação.

Genetic association of productive and reproductive traits with stayability in Nellore cattle: analysis using Bayesian models

We evaluated the genetic association of growth traits [weight adjusted to 205 days of age (W205), 365 days of age (W365), and 550 days of age (W550); weight gain between 205 days of age and 365 days of age (WG1) and between 365 days of age and 550 days of age (WG2)] and reproductive traits [age at first calving (AFC); first calving interval (FCI)] with stayability in the herd (STAY), using Bayesian inference in linear and threshold models. We defined STAY as the probability of a cow calving three or more times before the age of 76 months, given that she had calved at least once. We assigned binary codes (0, failure; 1, success) to each female. We used a sire model for analysis and formed different contemporary groups for the investigated traits. We analyzed the results by applying a two-trait sire model that included STAY (threshold trait) and linear traits (W205, W365, W550, WG1, WG2, AFC, and FCI). We used Gibbs sampling to estimate variance components and heritabilities. In all the analyses, we found that the mean heritability estimates for STAY were of moderate magnitude (0.20-0.25). The mean heritabilities for W205, W365, W550, WG1, WG2, AFC, and FCI were 0.20, 0.23, 0.39, 0.08, 0.14, 0.12, and 0.11, respectively. We observed wide variation in the posterior distributions of genetic correlations; however, with the exception of those obtained for the reproductive traits, the mean estimates were of low magnitude. Selection for WG2 can results in favorable correlated response in STAY.

Genetic evaluation of milk yield in Alpine goats for the first four lactations using random regression models

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.