Data/hora: 21/06/2024 22:43:08

Biblioteca(s): 	Embrapa Florestas.	
Data corrente: 	19/12/2014	
Data da última atualização: 	19/12/2014	
Autoria: 	AZEVEDO, C. F.; SILVA, F. F.; RESENDE, M. D. V. de; LOPES, M. S.; DUIJVESTEINJN, N.; GUIMARÃES, S. E. F.; LOPES, P. S.; KELLY, M. J.; VIANA, J. M. S.; KNOL, E. F.	
Afiliação: 	C. F. AZEVEDO, UFV; F. F. SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; M. S. LOPES, TOPGS Research Center IPG; N. DUIJVESTEINJN, TOPGS Research Center IPG; S. E. F. GUIMARÃES, UFV; P. S. LOPES, UFV; M. J. KELLY, Queensland Alliance for Agriculture & Food Innovation; J. M. S. VIANA, UFV; E. F. KNOL, TOPGS Research Center IPG.	
Título: 	Supervised independent component analysis as an alternative method for genomic selection in pigs.	
Ano de publicação: 	2014	
Fonte/Imprenta: 	Journal of Animal Breeding and Genetics, v. 131, p. 452-461, 2014.	
Idioma: 	Inglês	
Conteúdo: 	The objective of this work was to evaluate the efficiency of the supervised independent component regression (SICR) method for the estimation of genomic values and the SNP marker effects for boar taint and carcass traits in pigs. The methods were evaluated via the agreement between the predicted genetic values and the corrected phenotypes observed by cross-validation. These values were also compared with other methods generally used for the same purposes, such as RR-BLUP, SPCR, SPLS, ICR, PCR and PLS. The SICR method was found to have the most accurate prediction values.	
Palavras-Chave: 	Melhoramento genético.	
Thesagro: 	Porco.	
Categoria do assunto: 	--	
Registro original: 	Embrapa Florestas (CNPF)	
Exemplares: 	CNPF - (53131-1) - UPC - AP - DD -  -  -  - DIS