Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians

ABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand ei...

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Main Authors: Mariana de Almeida Dornelles, Paulo Roberto Nogara Rorato, Luis Telo Lavadinho da Gama, Fernanda Cristina Breda, Carlos Bondan, Dionéia Magda Everling, Vanessa Tomazetti Michelotti, Giovani Luis Feltes
Format: Article
Language:English
Published: Universidade Federal de Santa Maria 2016-09-01
Series:Ciência Rural
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000901649&lng=en&tlng=en
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spelling doaj-9c1c8425e7f540899e3d3745fecfd1632020-11-24T22:30:05ZengUniversidade Federal de Santa MariaCiência Rural1678-45962016-09-014691649165510.1590/0103-8478cr20150473S0103-84782016000901649Random regression models using different functions to estimate genetic parameters for milk production in Holstein FriesiansMariana de Almeida DornellesPaulo Roberto Nogara RoratoLuis Telo Lavadinho da GamaFernanda Cristina BredaCarlos BondanDionéia Magda EverlingVanessa Tomazetti MichelottiGiovani Luis FeltesABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand eight hundred and eighty biweekly records of test-day milk production were used. The models included the fixed effects of group of contemporaries and cow age at calving as covariable. Statistical criteria indicated that the WF.33_HE2, LEG.33_HE2, and LEG.55_HE4 functions best described the changes in the variances that occur throughout lactation. Heritability estimates using WF.33_HE2 and LEG.33_HE2 models were similar, ranging from 0.31 to 0.50. The LEG.55_HE4 model diverged from these models, with higher estimates at the beginning of lactation and lower estimates after the 16th fortnight. The LEG55_HE4, among the three better models indicated by the index, is the one with highest number of parameters (14 vs 34) and resulted in lower estimation of residual variance at the beginning and at the end of lactation, but overestimated heritability in the first fortnight and presented a greater difficulty to model genetic and permanent environment correlations among controls. Random regression models that used the Wilmink and Legendre polynomials functions with two residual variance classes appropriately described the genetic variation during lactation of Holstein Friesians reared in Rio Grande do Sul.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000901649&lng=en&tlng=enfunção de Ali & Schaefferclasses de variância residualcurva de lactaçãopolinômios de Legendrefunção de Wilmink
collection DOAJ
language English
format Article
sources DOAJ
author Mariana de Almeida Dornelles
Paulo Roberto Nogara Rorato
Luis Telo Lavadinho da Gama
Fernanda Cristina Breda
Carlos Bondan
Dionéia Magda Everling
Vanessa Tomazetti Michelotti
Giovani Luis Feltes
spellingShingle Mariana de Almeida Dornelles
Paulo Roberto Nogara Rorato
Luis Telo Lavadinho da Gama
Fernanda Cristina Breda
Carlos Bondan
Dionéia Magda Everling
Vanessa Tomazetti Michelotti
Giovani Luis Feltes
Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
Ciência Rural
função de Ali & Schaeffer
classes de variância residual
curva de lactação
polinômios de Legendre
função de Wilmink
author_facet Mariana de Almeida Dornelles
Paulo Roberto Nogara Rorato
Luis Telo Lavadinho da Gama
Fernanda Cristina Breda
Carlos Bondan
Dionéia Magda Everling
Vanessa Tomazetti Michelotti
Giovani Luis Feltes
author_sort Mariana de Almeida Dornelles
title Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
title_short Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
title_full Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
title_fullStr Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
title_full_unstemmed Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
title_sort random regression models using different functions to estimate genetic parameters for milk production in holstein friesians
publisher Universidade Federal de Santa Maria
series Ciência Rural
issn 1678-4596
publishDate 2016-09-01
description ABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand eight hundred and eighty biweekly records of test-day milk production were used. The models included the fixed effects of group of contemporaries and cow age at calving as covariable. Statistical criteria indicated that the WF.33_HE2, LEG.33_HE2, and LEG.55_HE4 functions best described the changes in the variances that occur throughout lactation. Heritability estimates using WF.33_HE2 and LEG.33_HE2 models were similar, ranging from 0.31 to 0.50. The LEG.55_HE4 model diverged from these models, with higher estimates at the beginning of lactation and lower estimates after the 16th fortnight. The LEG55_HE4, among the three better models indicated by the index, is the one with highest number of parameters (14 vs 34) and resulted in lower estimation of residual variance at the beginning and at the end of lactation, but overestimated heritability in the first fortnight and presented a greater difficulty to model genetic and permanent environment correlations among controls. Random regression models that used the Wilmink and Legendre polynomials functions with two residual variance classes appropriately described the genetic variation during lactation of Holstein Friesians reared in Rio Grande do Sul.
topic função de Ali & Schaeffer
classes de variância residual
curva de lactação
polinômios de Legendre
função de Wilmink
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000901649&lng=en&tlng=en
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