Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Melo, Cláudio; Packer, Irineu Umberto; Costa, C. N.; Machado, Paulo Fernando

doi:10.1017/s1751731107685036

Cited by 12 publications

(14 citation statements)

References 27 publications

(53 reference statements)

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“…According to AIC and BIC, the Ali and Schaeffer function was better than the Wilmink function. Similar results have been reported by Brotherstone et al (2000), Melo et al (2007), and Costa et al (2008).…”

Section: Resultssupporting

confidence: 91%

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Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Bignardi

Faro²,

Torres³

et al. 2011

Genet. Mol. Res.

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ABSTRACT. We analyzed 152,145 test-day records from 7317 first lactations of Holstein cows recorded from 1995 to 2003. Our objective was to model variations in test-day milk yield during the first lactation of Holstein cows by random regression model (RRM), using various functions in order to obtain adequate and parsimonious models for the estimation of genetic parameters. Test-day milk yields were grouped into weekly classes of days in milk, ranging from 1 to 44 weeks. The contemporary groups were defined as herd-test-day. The analyses were performed using a single-trait RRM, including the direct additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. The mean trend of milk yield was modeled with a fourth-order orthogonal Legendre polynomial. The additive genetic and permanent environmental covariance functions were estimated by random regression on two parametric functions, Ali and Schaeffer and Wilmink, and on B-spline functions of days in milk. The covariance components and the genetic parameters were estimated by the restricted maximum likelihood method. Results from RRM parametric and B-spline functions were compared to RRM on Legendre polynomials and with a multi-trait analysis, using the same data set. Heritability estimates presented similar trends during mid-lactation (13 to 31 weeks) and between week 37 and the end of lactation, for all RRM. Heritabilities obtained by multi-trait analysis were of a lower magnitude than those estimated by RRM. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. RRM using B-spline and Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data.

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Section: Resultssupporting

confidence: 91%

“…B-spline and Wilmink showed similar estimates. Several studies in Holstein cattle using RRM reported similar trend for TD heritability estimates as obtained in this study, Olori et al (1999) and Kettunen et al (2000), and in Brazil by Cobuci et al (2005), Araújo et al (2006), Melo et al (2007) and Dorneles et al (2009).…”

Section: Resultssupporting

confidence: 87%

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Bignardi

Faro²,

Torres³

et al. 2011

Genet. Mol. Res.

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“…Brotherstone et al (2000), ao empregar as funções paramétricas AS e W, para a raça Holandesa, observaram estimativas negativas entre o primeiro controle e os controles a partir dos 42 dias de lactação. Resultados semelhantes foram relatados por Rekaya et al (1999), López-Romero & Carabaño (2003 e Melo et al (2007) para a raça Holandesa, por Kettunen et al (2000) para a raça Ayrshire, e por Costa et al (2005) para a raça Gir. Meyer (1999) relatou que o ajuste dos modelos de regressão aleatória, nas extremidades da curva, é deficiente, provavelmente em razão do menor número de observações e da variação amostral na partição da variância total, o que pode levar à obtenção de estimativas erradas dos parâmetros genéticos.…”

Section: Resultsunclassified

“…Segundo El Faro & Albuquerque (2003), desconsiderar a heterogeneidade de variância residual nos estudos que utilizam MRA pode acarretar partição incorreta da variação total. Assim, a utilização de variância residual constante dentro de -mas heterogênea entre -classes de período de lactação tem sido estudada (El Faro & Albuquerque, 2003;Costa et al, 2005;Melo et al, 2007;Costa et al, 2008;Herrera et al, 2008).…”

Section: Introductionunclassified

Funções de covariância para produção de leite no dia do controle em bovinos Gir leiteiro

Pereira

Lopes

Verneque

et al. 2010

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi estimar funções de covariância para a produção de leite no dia do controle (PLDC). Foram analisados 27 mil registros de PLDC de 3.362 primeiras lactações de vacas da raça Gir leiteira, paridas entre 1990 e 2007. As PLDC foram agrupadas em vinte classes quinzenais, analisadas por modelos de regressão aleatória, cujos efeitos aleatórios, genético-aditivo e de ambiente permanente foram modelados pelas funções de Wilmink (W) ou Ali & Schaeffer (AS). A modelagem da variância residual (VR) foi ajustada por meio de 1, 4, 6 ou 10 classes. As estimativas de herdabilidade para a PLDC variaram de 0,12 a 0,32, para a função AS, e de 0,09 a 0,33, para a função W, e foram maiores ao início da lactação. As correlações genéticas entre as PLDC decresceram de valores próximos à unidade, entre controles adjacentes, para valores negativos entre as PLDC da primeira e duas últimas quinzenas da lactação. O modelo que empregou a função AS com quatro classes de VR é uma opção parcimoniosa para o ajuste das PLDC de vacas Gir leiteira no Brasil.Termos para indexação: bovinos de leite, função paramétrica, inferência bayesiana, parâmetros genéticos. Covariance functions for test-day milk yield in Gir cattleAbstract -The objective of this work was to estimate covariance functions for test-day milk yield (TDMY). Twenty-seven thousand TDMY records of 3,362 first lactations of Gir cows calving between 1990 and 2007 were analyzed. The TDMY data were grouped in 20 biweekly classes, analyzed by random regression models, whose random, additive-genetic and permanent environment effects were fitted by Wilmink's (W) or Ali & Schaeffer's (AS) functions. The residual variance (VR) modelling was fitted by 1, 4, 6, or 10 classes. The heritability estimates for TDMY varied from 0.12 to 0.32 for the AS function, and from 0.09 to 0.33 for W function, and were larger in the begining of the lactation period. The genetic correlations decreased from near unity, among adjacent TDMY values, to negative values between the first and the two last quarters of lactation. The model using the AS function with four VR classes, is a parsimonious option for the TDMY fitting of Gir cows in Brazil.

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“…Among the parametric functions used in RRMs to study test-day milk yield (TMDY), the exponential function of Wilmink and the logarithmic one of Ali and Schaeffer are more prominent (López-Romero and Carabaño, 2003;de Melo et al, 2007;Herrera et al, 2008;Pereira et al, 2010). Modifications of the Wilmink function have been proposed with the intention of improving the adjustment of curves to the data.…”

Section: Introductionmentioning

confidence: 99%

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Santos

Peixoto²,

Aspilcueta-Borquis³

et al. 2013

Genet. Mol. Res.

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ABSTRACT. Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, 3, 6, or 10 classes. The models gave similar hereditability estimates, ranging from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data.

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Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Cited by 12 publications

References 27 publications

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Funções de covariância para produção de leite no dia do controle em bovinos Gir leiteiro

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

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