Test-day model for milk yield of dairy buffaloes in colombia

The test-day model is the preferred method for genetic evaluations in dairy cattle. For this study, 28372 test-day records of 1220 lactations from 1997 to 2009 were used. The (co)variance components for milk in test-day were estimated using a Uni and multiple-traits repeated animal model with the Restricted Maximum Likelihood method (REML). The Contemporary Group (herd, year, and season of parity) and the age of parity (linear and quadratic) fixed effects, and the additive genetic, permanent environmental, and residual random effects were included in the model. The heritabilities ranged between 0.06 and 0.45 during lactation. The genetic correlations were greater than 0.93. In conclusion, the test-day model is appropriate for the genetic evaluation of dairy buffaloes in Colombia.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was 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. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameters for first lactation test-day milk flow in Holstein cows

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Test-day milk yield as a selection criterion for dairy buffaloes (Bubalus bubalis Artiodactyla, Bovidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameters for milk yield analyzed by test-day models in Murrah buffaloes in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Genetic parameters for test-day milk yield, 305-day milk yield, and lactation length in Guzerat cows

Milk production in tropical environments requires the use of crossbreeding systems including breeds well adapted to harsh conditions, but with lower productivities when compared to specialized breeds. Besides the genetic improvement for milk production, lactation lengths also need to be studied for most of these breeds. Accordingly, genetic parameters were estimated for 305-day cumulative milk yield (MY305), test-day milk yield (TDMY), and lactation length (LL) using information from the first lactations of 2816 Guzerat cows selected for milk production in 28 herds in Brazil. Contemporary groups were defined as herd, year and season of the test for TDMY, and as herd, year and season of calving for MY305 and LL. Variance components were estimated with the restricted maximum likelihood method under a multi-trait animal model. Heritabilities estimated for TDMY ranged from 0.16 to 0.24, and were 0.24 and 0.12 for MY305 and LL, respectively. Genetic correlations were high and positive, ranging from 0.51 to 0.99 among TDMY records, from 0.81 to 0.98 between each TDMY and MY305, and from 0.71 to 0.94 between each TDMY and LL. Genetic parameters obtained in this study indicated the possibility of using test-day records for the prediction of breeding values for milk yield in this population of the Guzerat breed. The use of TDMY as selection criteria would result in indirect gains in MY305 and LL. However, the highest response to selection for MY305 would be obtained by direct selection for this trait. © 2012 Elsevier B.V.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.