Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.

The objective of this study was to estimate the components of variance and genetic parameters of test-day milk yield in first lactation Girolando cows, using a random regression model. A total of 126,892 test-day milk yield (TDMY) records of 15,351 first-parity Holstein, Gyr, and Girolando breed cows were used, obtained from the Associação Brasileira dos Criadores de Girolando. To estimate the components of (co) variance, the additive genetic functions and permanent environmental covariance were estimated by random regression in three functions: Wilmink, Legendre Polynomials (third order) and Linear spline Polynomials (three knots). The Legendre polynomial function showed better fit quality. The genetic and permanent environment variances for TDMY ranged from 2.67 to 5.14 and from 9.31 to 12.04, respectively. Heritability estimates gradually increased from the beginning (0.13) to mid-lactation (0.19). The genetic correlations between the days of the control ranged from 0.37 to 1.00. The correlations of permanent environment followed the same trend as genetic correlations. The use of Legendre polynomials via random regression model can be considered as a good tool for estimating genetic parameters for test-day milk yield records.

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Bibliographic Details
Main Authors: SANTOS, E. P. B., FELTES, G. L., NEGRI, R., COBUCI, J. A., SILVA, M. V. G. B.
Other Authors: Pós-graduando, Universidade Estadual de Santa Cruz; Pós-graduando, Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL.
Format: Artigo de periódico biblioteca
Language:Ingles
English
Published: 2021-08-12
Subjects:Correlação genética, Função de Wilmink, Herdabilidade, Polinômios de Legendre, Polinômios splines lineares, Gado Leiteiro, Bovino, Variação Genética, Parâmetro Genético,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1133497
http://dx.doi.org/10.1590/1678-4162-12071
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spelling dig-alice-doc-11334972021-08-12T15:01:20Z Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model. SANTOS, E. P. B. FELTES, G. L. NEGRI, R. COBUCI, J. A. SILVA, M. V. G. B. Pós-graduando, Universidade Estadual de Santa Cruz; Pós-graduando, Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL. Correlação genética Função de Wilmink Herdabilidade Polinômios de Legendre Polinômios splines lineares Gado Leiteiro Bovino Variação Genética Parâmetro Genético The objective of this study was to estimate the components of variance and genetic parameters of test-day milk yield in first lactation Girolando cows, using a random regression model. A total of 126,892 test-day milk yield (TDMY) records of 15,351 first-parity Holstein, Gyr, and Girolando breed cows were used, obtained from the Associação Brasileira dos Criadores de Girolando. To estimate the components of (co) variance, the additive genetic functions and permanent environmental covariance were estimated by random regression in three functions: Wilmink, Legendre Polynomials (third order) and Linear spline Polynomials (three knots). The Legendre polynomial function showed better fit quality. The genetic and permanent environment variances for TDMY ranged from 2.67 to 5.14 and from 9.31 to 12.04, respectively. Heritability estimates gradually increased from the beginning (0.13) to mid-lactation (0.19). The genetic correlations between the days of the control ranged from 0.37 to 1.00. The correlations of permanent environment followed the same trend as genetic correlations. The use of Legendre polynomials via random regression model can be considered as a good tool for estimating genetic parameters for test-day milk yield records. 2021-08-12T15:01:11Z 2021-08-12T15:01:11Z 2021-08-12 2021 Artigo de periódico Arquivo Brasileiro de Medicina Veterinária e Zootecnia, v. 73, n. 1, p. 18-24, 2021. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1133497 http://dx.doi.org/10.1590/1678-4162-12071 Ingles en openAccess
institution EMBRAPA
collection DSpace
country Brasil
countrycode BR
component Bibliográfico
access En linea
databasecode dig-alice
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language Ingles
English
topic Correlação genética
Função de Wilmink
Herdabilidade
Polinômios de Legendre
Polinômios splines lineares
Gado Leiteiro
Bovino
Variação Genética
Parâmetro Genético
Correlação genética
Função de Wilmink
Herdabilidade
Polinômios de Legendre
Polinômios splines lineares
Gado Leiteiro
Bovino
Variação Genética
Parâmetro Genético
spellingShingle Correlação genética
Função de Wilmink
Herdabilidade
Polinômios de Legendre
Polinômios splines lineares
Gado Leiteiro
Bovino
Variação Genética
Parâmetro Genético
Correlação genética
Função de Wilmink
Herdabilidade
Polinômios de Legendre
Polinômios splines lineares
Gado Leiteiro
Bovino
Variação Genética
Parâmetro Genético
SANTOS, E. P. B.
FELTES, G. L.
NEGRI, R.
COBUCI, J. A.
SILVA, M. V. G. B.
Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.
description The objective of this study was to estimate the components of variance and genetic parameters of test-day milk yield in first lactation Girolando cows, using a random regression model. A total of 126,892 test-day milk yield (TDMY) records of 15,351 first-parity Holstein, Gyr, and Girolando breed cows were used, obtained from the Associação Brasileira dos Criadores de Girolando. To estimate the components of (co) variance, the additive genetic functions and permanent environmental covariance were estimated by random regression in three functions: Wilmink, Legendre Polynomials (third order) and Linear spline Polynomials (three knots). The Legendre polynomial function showed better fit quality. The genetic and permanent environment variances for TDMY ranged from 2.67 to 5.14 and from 9.31 to 12.04, respectively. Heritability estimates gradually increased from the beginning (0.13) to mid-lactation (0.19). The genetic correlations between the days of the control ranged from 0.37 to 1.00. The correlations of permanent environment followed the same trend as genetic correlations. The use of Legendre polynomials via random regression model can be considered as a good tool for estimating genetic parameters for test-day milk yield records.
author2 Pós-graduando, Universidade Estadual de Santa Cruz; Pós-graduando, Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL.
author_facet Pós-graduando, Universidade Estadual de Santa Cruz; Pós-graduando, Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; Universidade Federal do Rio Grande do Sul; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL.
SANTOS, E. P. B.
FELTES, G. L.
NEGRI, R.
COBUCI, J. A.
SILVA, M. V. G. B.
format Artigo de periódico
topic_facet Correlação genética
Função de Wilmink
Herdabilidade
Polinômios de Legendre
Polinômios splines lineares
Gado Leiteiro
Bovino
Variação Genética
Parâmetro Genético
author SANTOS, E. P. B.
FELTES, G. L.
NEGRI, R.
COBUCI, J. A.
SILVA, M. V. G. B.
author_sort SANTOS, E. P. B.
title Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.
title_short Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.
title_full Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.
title_fullStr Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.
title_full_unstemmed Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model.
title_sort estimation of genetic parameters for test-day milk yield in girolando cows using a random regression model.
publishDate 2021-08-12
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1133497
http://dx.doi.org/10.1590/1678-4162-12071
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