Birth seasons based on a climatic index for statistical model fitting of live weight of bovine cattle in Mexico

Abstract

The objective of this study was to compare the effects of a methodology for the climatic season classification that traditionally had been used as birth season (BS) in statistical assessments. This methodology bases in an aridity index (AI) to classify BS using meteorological historic information. Using a 7,460-pedigree animals dataset were fitted two statistical models for birth and weaning weights of Charolais cattle. Genetic models included the fixed effect of contemporary groups (CG= herd, sex, year and BS) and dam age as a covariate (linear and quadratic). Same models compared with a traditional season classification for BS. When variance component and expected progeny differences (EPD) were predicted with their accuracies, models were statistically different accordingly to the likelihood ratio test (P<0.01). An improvement and reduction in CG conformation (25 \%) were observed for those models including IA based BS. The main effect in assessed models was the ranking changes in EPD from both traits. This classification method of birth season can improve the model fitting in animal production based in extensive systems.