Genotypic parameters for egg production in pure breed hens by using random regression model

ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.

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Main Authors: Ferreira,Priscila Becker, Rorato,Paulo Roberto Nogara, Breda,Fernanda Cristina, Michelotti,Vanessa Tomazetti, Rosa,Alexandre Pires, Macedo,André
Format: Digital revista
Language:English
Published: Universidade Federal de Santa Maria 2017
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000500652
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spelling oai:scielo:S0103-847820170005006522017-04-27Genotypic parameters for egg production in pure breed hens by using random regression modelFerreira,Priscila BeckerRorato,Paulo Roberto NogaraBreda,Fernanda CristinaMichelotti,Vanessa TomazettiRosa,Alexandre PiresMacedo,André Barred Plymouth Rock heritability laying rate White Plymouth Rock ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.info:eu-repo/semantics/openAccessUniversidade Federal de Santa MariaCiência Rural v.47 n.5 20172017-01-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000500652en10.1590/0103-8478cr20141631
institution SCIELO
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country Brasil
countrycode BR
component Revista
access En linea
databasecode rev-scielo-br
tag revista
region America del Sur
libraryname SciELO
language English
format Digital
author Ferreira,Priscila Becker
Rorato,Paulo Roberto Nogara
Breda,Fernanda Cristina
Michelotti,Vanessa Tomazetti
Rosa,Alexandre Pires
Macedo,André
spellingShingle Ferreira,Priscila Becker
Rorato,Paulo Roberto Nogara
Breda,Fernanda Cristina
Michelotti,Vanessa Tomazetti
Rosa,Alexandre Pires
Macedo,André
Genotypic parameters for egg production in pure breed hens by using random regression model
author_facet Ferreira,Priscila Becker
Rorato,Paulo Roberto Nogara
Breda,Fernanda Cristina
Michelotti,Vanessa Tomazetti
Rosa,Alexandre Pires
Macedo,André
author_sort Ferreira,Priscila Becker
title Genotypic parameters for egg production in pure breed hens by using random regression model
title_short Genotypic parameters for egg production in pure breed hens by using random regression model
title_full Genotypic parameters for egg production in pure breed hens by using random regression model
title_fullStr Genotypic parameters for egg production in pure breed hens by using random regression model
title_full_unstemmed Genotypic parameters for egg production in pure breed hens by using random regression model
title_sort genotypic parameters for egg production in pure breed hens by using random regression model
description ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.
publisher Universidade Federal de Santa Maria
publishDate 2017
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000500652
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