Genetic parameters for test day milk yield of first lactation Holstein cows estimated by random regression using Legendre polynomials

Costa, C. N.; Melo, Cláudio; Packer, Irineu Umberto; Freitas, Ary Ferreira de; Teixeira, Nilson Milagres; Cobuci, Jaime Araújo

doi:10.1590/s1516-35982008000400003

Cited by 49 publications

(63 citation statements)

References 21 publications

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“…Considering the Holstein breed in Brazil, heritability estimates for the test-day milk yield, adjusted with the Legendre polynomials, Wilmink, Ali & Schaeffer under RRM range from .11 to .31 (Cobuci et al, 2004;Cobuci et al, 2006;Araújo et al, 2006;Costa et al, 2008;Biassus, Cobuci, & Costa, 2011). These results are in agreement with heritability results observed in studies with Holsteins from other countries, ranging from 0.08 to 0.23 (Hahammi et al, 2008;Silvestre, Petim-Batista, & Colaço, 2006;Strabel & Misztal, 1999).…”

Section: Introductionsupporting

confidence: 79%

“…The residual variance was assumed to be constant throughout the lactation and independent between milk records (Costa et al, 2008;Biassus, Cobuci, & Costa, 2011). The different functions adopted, characterizing the different sub-models of random regression, have been adjusted in bz, az and pz in order to model the fixed and random animal effects and animal environmental permanent, respectively.…”

Section: Genetic Analysesmentioning

confidence: 99%

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Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

Azevedo¹,

Gonçalves²,

Souza³

et al. 2018

JAS

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Random regression models (RRM) differ in terms of the functions used to describe the shape of lactation curves. The aim was to compare random regression models under different functions to describe the lactation curves from Holstein cows in herds of the state of Minas Gerais. A database of 28,118 production records was analyzed using the test-day records of 4,230 first parity cows from five herds. The Wilmink, Ali & Schaeffer and Legendre polynomial (orders 4, 5 and 6) functions were adjusted in RRM to model the mean production trend (fixed) and genetic and permanent environmental (random) effects. The residual variances were assumed to be constant throughout lactation. Analyses were performed using the AIREMLF90 program. Except for the model with the polynomial function of order 5, all models converged. The Wilmink function showed lower values for criteria based on the -2log (L), AIC and BIC. The model with the Legendre polynomial of order 6 showed lower residual variance. Heritability estimates were similar between functions, ranging from 0.07 to 0.18 and were higher from 215 days of lactation. From 155 days of lactation, genetic and permanent environmental correlations between successive controls are of high magnitude. The Wilmink function is the most suitable for the study of milk yields from primiparous Holstein cows. The selection of animals is possible from 155 days of lactation on. Permanent environmental effects have greater influence on the milk production at the end of lactation of primiparous cows and should be considered since they are important and may be cumulative throughout lactation.

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Section: Introductionsupporting

confidence: 79%

Section: Genetic Analysesmentioning

confidence: 99%

Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

Azevedo¹,

Gonçalves²,

Souza³

et al. 2018

JAS

View full text Add to dashboard Cite

show abstract

“…Traits in younger ages also differ from each other, especially at the lowest ages (for instance, the correlation between growth traits at 2 and 4 weeks is 0.70). In other studies, it has been shown that the genetic control of weight at initial ages is different from that observed at later ages (Fischer et al, 2004b;Wilson et al, 2005;Szwaczkowski et al, 2007;Costa et al, 2008;El Faro et al, 2008;Oliveira et al, 2010). The genetic correlations of BW measured between 14 and 24 weeks estimated with the multivariate method were 0.89 and 0.97 in US and UK turkey populations, respectively (Kranis et al, 2006).…”

Section: Correlationsmentioning

confidence: 87%

Estimates of the genetic parameters of turkey body weight using random regression analysis

Rafat

Namavar

Shodja

et al. 2011

Animal

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Random regression (RR) analysis has been recommended to estimate the genetic parameters of longitudinal data. The objective of this study was to evaluate the growth of turkeys using RR models. Data were collected from 957 turkeys and included 15 478 individual body weight recorded during the first week of life and between weeks 2 and 32 by 2-week intervals. To take into account the repeated measurements of weight for each animal, a specific overall growth curve was modelled using a cubic smoothing spline. Animal deviation to this curve was also modelled using an RR function. All data were analysed with the ASReml package. The results showed an increase in heritability estimates over the trajectory and peaked at 0.60 around 20 to 32 weeks of age. Genetic correlations showed that turkeys could be selected at earlier time points, at 12 weeks of age, in order to increase the growth rate. In general, genetic correlation estimates were higher among adjacent ages, decreasing markedly with the increase of distance between ages. Negative genetic correlations were observed between ages.

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“…Segundo Melo (2003), tendo em vista que há indicações de que a herdabilidade para a característica produção de leite no dia do controle é maior que a da produção de leite ajustada para 305 dias, a adoção da herdabilidade, como critério de seleção, promoveria progresso genético mais rápido. No Brasil, Freitas (2003), Melo (2003), Costa et al (2005) Costa et al (2008) relataram que, embora a variância residual para a produção de leite seja heterogênea entre determinados estágios de lactação, a adoção de variância residual homogênea (constante ao longo do período de lactação) pelos modelos é uma opção parcimoniosa para ajuste das produções no dia do controle de vacas da raça Holandesa no Brasil.…”

Section: Introductionunclassified

Estimação de parâmetros genéticos para produção de leite de vacas da raça Holandesa via regressão aleatória

Dorneles

Cobuci

Rorato

et al. 2009

Arq. Bras. Med. Vet. Zootec.

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RESUMOForam utilizados 21.702 registros de produção de leite no dia do controle de 2.429 vacas primíparas da raça Holandesa, filhas de 233 touros, coletados em 33 rebanhos do Estado do Rio Grande do Sul, para estimar parâmetros genéticos para produção de leite no dia do controle. O modelo de regressão aleatória ajustado aos controles leiteiros entre o sexto e o 305º dia de lactação incluiu o efeito de rebanho-ano-mês do controle, idade da vaca no parto e os parâmetros do polinômio de Legendre de ordem quatro, para modelar a curva média da produção de leite da população e parâmetros do mesmo polinômio, para modelar os efeitos aleatórios genético-aditivo e de ambiente permanente. As variâncias genéticas e de ambiente permanente para produção de leite no dia do controle variaram, respectivamente, de 2,38 a 3,14 e de 7,55 a 10,35. As estimativas de herdabilidade aumentaram gradativamente do início (0,14) para o final do período de lactação (0,20), indicando ser uma característica de moderada herdabilidade. As correlações genéticas entre as produções de leite de diferentes estágios leiteiros variaram de 0,33 a 0,99 e foram maiores entre os controles adjacentes. As correlações de ambiente permanente seguiram a mesma tendência das correlações genéticas. O modelo de regressão aleatória com polinômio de Legendre de ordem quatro pode ser considerado como uma boa ferramenta para estimação de parâmetros genéticos para a produção de leite ao longo da lactação.

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Genetic parameters for test day milk yield of first lactation Holstein cows estimated by random regression using Legendre polynomials

Cited by 49 publications

References 21 publications

Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

Estimates of the genetic parameters of turkey body weight using random regression analysis

Estimação de parâmetros genéticos para produção de leite de vacas da raça Holandesa via regressão aleatória

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