Depicting latent variables considering different pig genetics and nutritional plans in crossbred pigs

• Main Author: Henriques, Renata Felisberto
• Publication Date: 2022
• Other Authors: Silva, Fabyano Fonseca e, Veroneze, Renata, Duarte, Marcio de Souza, Paiva, José Teodoro, Veloso, Rogério de Carvalho, Lopes, Paulo Sávio
• Format: Article
• Language: eng
• Source: LOCUS Repositório Institucional da UFV
• Download full: https://locus.ufv.br//handle/123456789/30227; https://doi.org/10.37496/rbz5120220021
• topic: carcass; factor analysis; factor analysis; multivariate; performance

We aimed to reduce the dimensionality of quantitative traits in pigs applying factor analysis. Quantitative variables were collected, and the factor analysis extracted five factors with biological meaning related to performance, carcass quality, carcass yield, meat quality, and initial pH. These factors were posteriorly used as dependent variable to evaluate the effects of genetic groups (Piau, Duroc, and Pietrain crossbreds), nutritional plans (low, medium and high lysine levels) and sex. An interaction effect between genetic group and sex was observed in performance, in which Duroc crossbred showed the greatest scores. The Pietrain genetic group showed greater values of carcass quality compared with Duroc and Piau, while Piau crossbred pigs had greater values for meat quality compared with Pietrain and Duroc. A greater carcass yield was observed in Pietrain crossbred compared with Duroc pigs. Pigs fed under low lysine level had the lowest performance values. Carcass yield was affected by nutritional plans, in which the medium lysine level showed the greatest values. Meat quality was improved by the nutritional plan with high lysine level compared with the low lysine level. Initial pH showed increased means when using nutritional plans with low and medium lysine levels in diet composition. With regard to sex effects, a greater carcass quality was found for gilts compared with barrows. The reduction of the data dimensionality allowed the joint evaluation of genetic group, nutritional plan, and sex based on new latent variables that represented the original dataset under easier framework based on factors’ biological interpretation