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Provedor de dados:  Ciência Rural
País:  Brazil
Título:  Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians
Autores:  Dornelles,Mariana de Almeida
Rorato,Paulo Roberto Nogara
Gama,Luis Telo Lavadinho da
Breda,Fernanda Cristina
Bondan,Carlos
Everling,Dionéia Magda
Michelotti,Vanessa Tomazetti
Feltes,Giovani Luis
Data:  2016-09-01
Ano:  2016
Palavras-chave:  Ali and Schaeffer function
Classes of residual variance
Lactation curve
Legendre polynomials
Wilmink function
Resumo:  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.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000901649
Editor:  Universidade Federal de Santa Maria
Relação:  10.1590/0103-8478cr20150473
Formato:  text/html
Fonte:  Ciência Rural v.46 n.9 2016
Direitos:  info:eu-repo/semantics/openAccess
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