Phenotypic relationship of female sexual precocity with production and reproduction traits in beef cattle using multivariate statistical techniques

Abstract

Multivariate statistical techniques were used to characterise the differences between precocious and non-precocious Nellore females regarding the phenotypic expression of various reproductive and productive traits. Information of 13,105 females was used in a correspondence analysis to describe the relationship of heifer early pregnancy and the categorical variables (stayability and visual scores). Moreover, principal component and factor analyses were used to investigate the relationship between early pregnancy and the continuous variables. These statistical techniques allow synthesising the information of a large set of random and correlated traits in a reduced set of uncorrelated latent variables generated as linear combinations of the original dataset. In this study, principal component and factor analyses indicated that sexually precocious females present higher weight gain from weaning to yearling, backfat thickness, longevity, and cumulative productivity than non-precocious females. In the correspondence analysis, precocious females were associated with score 4, which is between the intermediate and the extremely high expression, of conformation, muscling, finishing precocity and size, and with value 1 (favourable) of stayability. All these findings indicate that the use of precocious females could benefit the overall performance of a herd since they present higher growth rate, better product quality and higher lifetime productivity than non-precocious cows.Highlights Multivariate statistical techniques were used to investigate the relationship pattern of complex traits in Nellore cattle. The anticipation of heifer reproductive life was favourably associated with cumulative productivity and longevity in beef cattle. Using precocious females could benefit all production phases of a herd.

Keywords

• principal component analysis
• factor analysis
• correspondence analysis
• nellore beef cattle