The body weight is one of the mainly traits evaluated in sheep selection and it provides a more accurate measure of carcass yield, and can be measured in the same animal at different ages. In addition, as well as traits related to the production, the selection should also include resistance and resilience to endoparasites traits, because sheep have a greater susceptibility to infections caused by endoparasites, which considerably limits the performance and economic efficiency of these animals. The aims of this study were: (1) compare structures to mold the residual variance in random regression models; (2) evaluate the influence of this modeling in the estimation of genetic parameters in order to determine the most appropriate model to study the growth curve and resistance to worms; (3) use cluster analysis to explore the genetic profile of the animals for meat production, resistance and resilience to endoparasites, in order to identify superior animals and use them as sires and dams of Santa Ines sheep. To perform the analysis, it will be used a data set with records from 2,531 from 771 sheep Santa Ines. The traits analyzed will be: body weight (BW), fecal egg counting per gram (FEC) and packed cell volume (PCV). The analysis of the estimates of the variance components will be carried out using a single trait random regression model by the restricted maximum likelihood method in order to determine the best model to study the growth curve and resistance to worms. Based on breeding values of the additives studied traits, cluster analysis by the hierarchical and non-hierarchical methods will be performed, in order to characterize the groups that will be subject to selection.
News published in Agência FAPESP Newsletter about the scholarship: