Strategies for the identification of precocity in zebu beef cattle based on mixed nonlinear models and multivariate approach.

The use of mixed nonlinear models reduces the residual variance by including random effects, thereby improving the estimates in growth curves. Therefore, we tested distinct mixed nonlinear models (Richards, Brody, Gompertz, Logistic, and Von Bertalanffy) to model the growth curves of Zebu cattle herds raised on pasture in Brazil. In addition, we evaluated the diversity among breeds using hierarchical cluster multivariate analysis (full linkage) based on asymptotic weight (A), maturity rate (K), absolute growth rate (AGR), and absolute maturity rate (AMR) adjusted to 205, 365, 550, and 730 days of age. Body weight data from 311,834 males and females of Guzerat, Nellore, Tabapuã, and Polled Nellore breeds provided by the Brazilian Association of Zebu Breeders were used. The Brody model considering breed-sex fixed and animal random effects was the most suitable to describe the growth in the four breeds. The Guzerat and Tabapuã males showed increased precocity (higher K values) when compared to polled Nellore and Nellore males, which were characterized by higher A and AMR values. Females were more precocious than males (high K and low A values), particularly within Tabapuã and Guzerat breeds, respectively. Regardless of sex, the highest AGR values were observed from weaning up to 2 years of age in Tabapuã and Guzerat breeds. The cluster analyses revealed two groups: (1) Polled Nellore and Nellore males with high A, AGR_205, AGR_365, AGR_550, and AGR_730 values, represented by large adult animals, and (2) males and females of Guzerat and Tabapuã, characterized as animals of increased precocity. A subgroup encompassing males of Guzerat and Tabapuã was also observed, with intermediate values ​​for all parameters. This information is useful to help breeders and producers in strategies for feeding management and defining the most precocious beef cattle breed to increase the economic gains in pasture-based raising systems.