Data/hora: 04/06/2024 05:43:32

Provedor de dados: 	86	
País: 	Brazil	
Título: 	Use of regularized quantile regression to predict the genetic merit of pigs for asymmetric carcass traits	
Autores: 	Santos,Patricia Mendes dos; Nascimento,Ana Carolina Campana; Nascimento,Moysés; Silva,Fabyano Fonseca e; Azevedo,Camila Ferreira; Mota,Rodrigo Reis; Guimarães,Simone Eliza Facioni; Lopes,Paulo Sávio.	
Data: 	2018-09-01	
Ano: 	2018	
Palavras-chave: 	Sus scrofa; Blasso; Shrinkage.	
Resumo: 	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.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2018000901011	
Editor: 	Embrapa Secretaria de Pesquisa e Desenvolvimento

Pesquisa Agropecuária Brasileira	
Relação: 	10.1590/s0100-204x2018000900004	
Formato: 	text/html	
Fonte: 	Pesquisa Agropecuária Brasileira  v.53 n.9 2018	
Fonte: 	info:eu-repo/semantics/openAccess