Use of regularized quantile regression to predict the genetic merit of pigs for asymmetric carcass traits

Authors

  • Patricia Mendes dos Santos Universidade Federal de Viçosa, Departamento de Estatística, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.
  • Ana Carolina Campana Nascimento Universidade Federal de Viçosa, Departamento de Estatística, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.
  • Moysés Nascimento Universidade Federal de Viçosa, Departamento de Estatística, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.
  • Fabyano Fonseca e Silva Universidade Federal de Viçosa, Departamento de Zootecnia, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.
  • Camila Ferreira Azevedo Universidade Federal de Viçosa, Departamento de Estatística, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.
  • Rodrigo Reis Mota Université de Liège, Gembloux Agro-Bio Tech, Passage des Déportés 2, B5030 Gembloux, Belgium.
  • Simone Eliza Facioni Guimarães Universidade Federal de Viçosa, Departamento de Zootecnia, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.
  • Paulo Sávio Lopes Universidade Federal de Viçosa, Departamento de Zootecnia, Avenida P.H. Rolfs, s/no, CEP 36570-000 Viçosa, MG.

DOI:

https://doi.org/10.1590/S1678-3921.pab2018.v53.25763

Keywords:

Sus scrofa, Blasso, shrinkage

Abstract

The objective of this work was to evaluate the use of regularized quantile regression (RQR) to predict the genetic merit of pigs for asymmetric carcass traits, compared with the Bayesian lasso (Blasso) method. The genetic data of the traits carcass yield, bacon thickness, and backfat thickness from a F2 population composed of 345 individuals, generated by crossing animals from the Piau breed with those of a commercial breed, were used. RQR was evaluated considering different quantiles (τ = 0.05 to 0.95). The RQR model used to estimate the genetic merit showed accuracies higher than or equal to those obtained by Blasso, for all studies traits. There was an increase of 6.7 and 20.0% in accuracy when the quantiles 0.15 and 0.45 were considered in the evaluation of carcass yield and bacon thickness, respectively. The obtained results are indicative that the regularized quantile regression presents higher accuracy than the Bayesian lasso method for the prediction of the genetic merit of pigs for asymmetric carcass variables.

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Published

2018-11-07

How to Cite

Santos, P. M. dos, Nascimento, A. C. C., Nascimento, M., Silva, F. F. e, Azevedo, C. F., Mota, R. R., … Lopes, P. S. (2018). Use of regularized quantile regression to predict the genetic merit of pigs for asymmetric carcass traits. Pesquisa Agropecuaria Brasileira, 53(9), 1011–1017. https://doi.org/10.1590/S1678-3921.pab2018.v53.25763

Issue

v.53, n.9, set. 2018

Section

STATISTICS