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Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model

This study was carried out to estimate (co)variance components and genetic parameters for live weight of Nellore cattle from Performance Test of Young Bulls using random regression models. Data of weights and ages of 925 weaned males was used. The animal model included the fixed effect of contempora...

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Autores principales: Lopes, Fernando Brito, Magnabosco, Cláudio Ulhôa, Paulini, Fernanda, da Silva, Marcelo Corrêa, Miyagi, Eliane Sayuri, Lôbo, Raysildo Barbosa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing AG 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3579416/
https://www.ncbi.nlm.nih.gov/pubmed/23449556
http://dx.doi.org/10.1186/2193-1801-1-49
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author Lopes, Fernando Brito
Magnabosco, Cláudio Ulhôa
Paulini, Fernanda
da Silva, Marcelo Corrêa
Miyagi, Eliane Sayuri
Lôbo, Raysildo Barbosa
author_facet Lopes, Fernando Brito
Magnabosco, Cláudio Ulhôa
Paulini, Fernanda
da Silva, Marcelo Corrêa
Miyagi, Eliane Sayuri
Lôbo, Raysildo Barbosa
author_sort Lopes, Fernando Brito
collection PubMed
description This study was carried out to estimate (co)variance components and genetic parameters for live weight of Nellore cattle from Performance Test of Young Bulls using random regression models. Data of weights and ages of 925 weaned males was used. The animal model included the fixed effect of contemporary group, age of the animal at weighing as a covariate and as random effects it was considered the effect of additive genetic and permanent environment of the animal. The residue was modeled considering four classes of variances. The models were compared based on the Bayesian information criteria of Akaike and Schwartz. The model polynomial of fourth and sixth order for the direct additive genetic effects and permanent environment of the animal, respectively was the most appropriate to describe the changes in the variances of the weights during the period in which the animals participating in the performance test young bulls. Heritability estimates showed moderate magnitudes and indicated that direct selection will promote improvement of selection criteria adopted. Furthermore, due to high positive correlation between the estimated weights, it was suggested selecting the best animals before at 365 days of age, because it is the period in which the animals have a higher growth rate and thus you can select animals heavier and less delayed.
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spelling pubmed-35794162013-02-26 Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model Lopes, Fernando Brito Magnabosco, Cláudio Ulhôa Paulini, Fernanda da Silva, Marcelo Corrêa Miyagi, Eliane Sayuri Lôbo, Raysildo Barbosa Springerplus Research This study was carried out to estimate (co)variance components and genetic parameters for live weight of Nellore cattle from Performance Test of Young Bulls using random regression models. Data of weights and ages of 925 weaned males was used. The animal model included the fixed effect of contemporary group, age of the animal at weighing as a covariate and as random effects it was considered the effect of additive genetic and permanent environment of the animal. The residue was modeled considering four classes of variances. The models were compared based on the Bayesian information criteria of Akaike and Schwartz. The model polynomial of fourth and sixth order for the direct additive genetic effects and permanent environment of the animal, respectively was the most appropriate to describe the changes in the variances of the weights during the period in which the animals participating in the performance test young bulls. Heritability estimates showed moderate magnitudes and indicated that direct selection will promote improvement of selection criteria adopted. Furthermore, due to high positive correlation between the estimated weights, it was suggested selecting the best animals before at 365 days of age, because it is the period in which the animals have a higher growth rate and thus you can select animals heavier and less delayed. Springer International Publishing AG 2012-11-20 /pmc/articles/PMC3579416/ /pubmed/23449556 http://dx.doi.org/10.1186/2193-1801-1-49 Text en © Lopes et al.; licensee Springer. 2012 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Lopes, Fernando Brito
Magnabosco, Cláudio Ulhôa
Paulini, Fernanda
da Silva, Marcelo Corrêa
Miyagi, Eliane Sayuri
Lôbo, Raysildo Barbosa
Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
title Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
title_full Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
title_fullStr Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
title_full_unstemmed Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
title_short Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
title_sort analysis of longitudinal data of nellore cattle from performance test at pasture using random regression model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3579416/
https://www.ncbi.nlm.nih.gov/pubmed/23449556
http://dx.doi.org/10.1186/2193-1801-1-49
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