Principal component analysis of breeding values for growth, reproductive and visual score traits of Nellore cattle

Abstract The objective of this study was to estimate genetic parameters for 7 traits of Nellore, to verify how the estimate breeding values (EBVs) of the traits are distributed in different Brazilian states, and to suggest a selection index by state/sex.Heritability (h2) and EBVs were estimated by single-trait analysis under animal model, using the AIREML method. In addition, relationships among animal EBVs for these traits were explored using principal component analysis (PCA). Direct h2 estimates ranging from 0.20 ± 0.06 to 0.51 ± 0.05 indicate that productive and morphological traits are all heritable to varying degrees. However, AFC presented low h2 estimate (0.05 ± 0.06). The first 2 principal componentspresented correlation above ± 0.60 with EBVs of all evaluated traits, retaining above 96% of the total breeding value variance.In state of Parana they are the best EBVs for growth traits (W550 and D400) in males and females. In general, Minas Gerais was highlighted for reproductive traits in males (EBVSC550), and females (EBVAFC). Selecting for the PC1 would identify animals with favorable breeding values for all studied traits.The PCA is a good alternative in the elaboration of selection indices in Nellore breeddefined for different sex and environments.