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Provedor de dados:  Ciência Rural
País:  Brazil
Título:  Genetic analysis of residual feed intake adjusted for fat and carcass and performance traits in a Nellore herd
Autores:  Moraes,Giovanna Faria de
Abreu,Luiza Rodrigues Alves
Ferreira,Isabel Cristina
Pereira,Idalmo Garcia
Data:  2017-01-01
Ano:  2017
Palavras-chave:  Back fat thickness
Feed efficiency
Genetic correlation
Heritability
Resumo:  ABSTRACT: The study of the genetic evaluation of residual feed intake adjusted for fat (RFIFat) is important for the appropriate use of feed efficiency in selection programs. The objective was to analyze the influence of selection for RFIF at on carcass and performance traits by estimating various genetic parameters. Data were analyzed from five tests of feed efficiency, which were conducted with 677 Nellore males. Genetic evaluation was performed by Bayesian inference using an animal model via single- and two-trait analyses. Variables analyzed were dry matter intake, average daily gain, RFIFat, rib eye area, back fat thickness, rump fat thickness, marbling score, and subcutaneous fat thickness. The posterior mean distributions estimated at each analysis were used to estimate heritability of the traits and to perform various correlations. The studied traits showed high heritability estimates, and they should respond well to selection. The RFIFat presented a phenotypic correlation with carcass traits (which was next to zero), and there was also a negative genetic correlation. Additive genetic variability for RFIFat showed that selection for this trait can promote genetic gains in future generations, resulting in animals that are efficient in terms of nutrient use, and according to the genetic and phenotypic correlations, with no significant negative changes to carcass traits.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000200651
Editor:  Universidade Federal de Santa Maria
Relação:  10.1590/0103-8478cr20151505
Formato:  text/html
Fonte:  Ciência Rural v.47 n.2 2017
Direitos:  info:eu-repo/semantics/openAccess
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