Claudio Napolis Costa

Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model

Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.

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

Data comprising 263,390 test-day (TD) records of 32,448 first parity cows calving in 467 herds between 1991 and 2001 from the Brazilian Holstein Association were used to estimate genetic and permanent environmental variance components in a random regression animal model using Legendre polynomials (LP) of order three to five by REML. Residual variance was assumed to be constant in all or in some classes of lactation periods for each LP. Estimates of genetic and permanent environmental variances did not show any trend due to the increase in the LP order. Residual variance decreased as the order of LP increased when it was assumed constant, and it was highest at the beginning of lactation and relatively constant in mid lactation when assumed to vary between classes. The range for the estimates of heritability (0.27 - 0.42) was similar for all models and was higher in mid lactation. There were only slight differences between the models in both genetic and permanent environmental correlations. Genetic correlations decreased for near unity between adjacent days to values as low as 0.24 between early and late lactation. A five parameter LP to model both genetic and permanent environmental effects and assuming a homogeneous residual variance would be a parsimonious option to fit TD yields of Holstein cows in Brazil.

Parâmetros genéticos para as produções de leite no dia do controle e da primeira lactação de vacas da raça Holandesa

Covariance components for test day records and lactation milk yield using 263.390 records of 32.448 first lactation Holstein cows, were estimated using animal models by REML. Besides the lactation model, two alternative repeatability models (RM) were analyzed. Lactation model included fixed effects of herd-year-season and age of cow with linear and quadratic terms, and random effects of animal and error. The first model for test-day yield (RMF) included the same effects, but fixed effect of contemporary group, defined as herd-year-month of test. Alternatively another model for test-day yield (RMF) used a logarithmic polynomial sub-model for the shape of the lactation curve. Heritability for lactation yield (0.27) was smaller than those estimated by RMF and RMS, 0.30 and 0.43, respectively. Heritability estimates for univariate (0.22-0.36) and bivariate models (0.23-0.33) for test day milk yields were found to be smallest during early and late lactation. Heritability estimate for lactation milk yield when estimated by univariate model (0.27) was smaller than estimates obtained by bivariate models (0.27-0.30). Genetic correlations were higher between consecutive test days than between test days in the beginning and end of lactation. Larger heritability estimates for test day models and large genetic correlations between test day and lactation yield (0.86-0.99) indicate a potential use of test day records in genetic evaluations.

Análises da Persistência na Lactação de Vacas da Raça Holandesa, Usando Produção no Dia do Controle e Modelo de Regressão Aleatória 1

A total of 87,045 milk yield records of 11,023 first-parity Holstein cows was utilized, obtained from 1997 to 2001 from different herds of 10 Minas Gerais locations. Six types of persistency measures in lactation were evaluated using milk yield breeding values, obtained by means of Random Regression Model - RRM. The Wilmink function was used to describe the random and fixed effects by RRM. Heritability estimates and genetic correlations for various persistency measures in lactation were dependent on the definition of persistency. The heritability estimates for persistency in lactation ranged from 0.11 to 0.27 and the genetic variations among persistency measures in lactation and milk yield up to d 305 ranged from -0.31 to 0.55, showing that persistency in lactation is a trait of moderate heritability showing little correlation with milk yield up to d 305. The selection of animals for persistency in lactation aiming to alter the lactation curve may be effective.

Parâmetros genéticos para a produção de leite de controles individuais de vacas da raça Gir estimados com modelos de repetibilidade e regressão aleatória

Data comprising 8,183 test day records of 1,273 first lactations of Gyr cows from herds supervised by ABCZ were used to estimate variance components and genetic parameters for milk yield using repeatability and random regression animal models by REML. Genetic modelling of logarithmic (FAS), exponential (FW) curves was compared to orthogonal Legendre polynomials (LP) of order 3 to 5. Residual variance was assumed to be constant in all (ME=1) or some periods of lactation (ME=4). Lactation milk yield in 305-d was also adjusted by an animal model. Genetic variance, heritability and repeatability for test day milk yields estimated by a repeatability animal model were 1.74 kg2, 0.27, and 0.76, respectively. Genetic variance and heritability estimates for lactation milk yield were respectively 121,094.6 and 0.22. Heritability estimates from FAS and FW, respectively, decreased from 0,59 and 0.74 at the beginning of lactation to 0.20 at the end of the period. Except for a fifth-order LP with ME=1, heritability estimates decreased from around 0,70 at early lactation to 0,30 at the end of lactation. Residual variance estimates were slightly smaller for logarithimic than for exponential curves both for homogeneous and heterogeneous variance assumptions. Estimates of residual variance in all stages of lactation decreased as the order of LP increased and depended on the assumption about ME. Estimates of genetic and permanent environment variances did not show any trend due to the increase in the order of LP. Genetic correlation estimates between TD were largest for LP and larger for FW than for FAS. Except for FAS, a similar pattern in genetic correlation estimates was observed for all curves decreasing from values close to unity between adjacent TD at early lactation to negative values for TD in the beginning and the end of lactation. The Legendre polynomial of order five and the FAS under ME4 best fitted the data. There is a potential for using random regression to model animal genetic and permanent environmental effects using test day information of Gyr cows.

Heterogeneidade de variância e avaliação genética de bovinos da raça Holandesa no Brasil

Dados de 109.200 lactacoes foram utilizados para verificar o efeito da heterogeneidade de variância sobre a avaliacao genetica de vacas e touros da raca Holandesa criados no Brasil. A producao total de leite ajustada para idade adulta foi usada para classificar os rebanhos em tres classes de desvio-padrao fenotipico: baixo ( 1625 kg). Dados das primeiras lactacoes foram analisados considerando a producao total de leite ajustada para idade adulta (TOTAJU) e producao total de leite ajustada para idade adulta e para 305 dias de lactacao (TAJU305). As producoes de leite medias e os componentes de variância genetica, residual e fenotipica aumentaram com o aumento do desvio-padrao da classe. Para as classes de baixo e medio, baixo e alto e medio e alto desvios-padrao, as correlacoes geneticas foram 0,97; 0,89; e 0,91 para TOTAJU e 0,97; 0,92; e 0,96 para TAJU305, respectivamente. As correlacoes entre os valores geneticos para as classes de baixo, medio e alto desvios-padrao obtidos nas analises conjuntas (considerando como diferentes a expressao da caracteristica nas tres classes) e os obtidos na analise geral (todas as classes como unica caracteristica) foram proximas a unidade. Entretanto, os reprodutores apresentaram maiores valores geneticos em rebanhos das classes de alto desvio-padrao. Na avaliacao genetica, e importante considerar a variabilidade entre rebanhos, pois, sob selecao, as classes mais variaveis contribuiram com a maior parte dos animais, e a avaliacao genetica do animal poderia ser funcao nao apenas do seu potencial genetico, mas tambem do ambiente no qual suas progenies expressaram a caracteristica.

Uso de modelos de regressão aleatória para descrever a variação genética da produção de leite na raça Holandesa

Data comprising 68,523 test day milk yield of 8,536 cows of the Holstein breed, calving from 1996 to 2001, were used to compare random regression models, for estimating variance components. Test day records (TD) were analyzed as multiple traits, considering each TD as a different trait. The test day records were analyzed as longitudinal traits by different random regression models regarding the function used to describe the trajectory of the lactation curve of the animals. The Wilminks exponential function, the Ali and Schaeffer logarithmic function and the Legendre orthogonal polynomials of second and fourth order were used. The comparisons among the models were based on the following criteria: estimates of variance components of the multiple-trait model and random regressions models, values of residual variance and values of the logarithms of the likelihood functions. The heritability estimates obtained using the multiple-trait model varied from 0.110 to 0.244, for the random regression models the values ranged from 0.127 to 0.301, being the largest estimates observed in the models with larger number of parameters. The random regression models which used the Legendre polynomials was the model which better described the genetic variation of the milk yield.

Genetic parameters for milk production by using random regression models with different alternatives of fixed regression modeling

Records of test-day milk yields of the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters for milk yield by using two alternatives of definition of fixed regression of the random regression models (RRM). Legendre polynomials of fourth and fifth orders were used to model regression of fixed curve (defined based on averages of the populations or multiple sub-populations formed by grouping animals which calved at the same age and in the same season of the year) or random lactation curves (additive genetic and permanent enviroment). Akaike information criterion (AIC) and Bayesian information criterion (BIC) indicated that the models which used multiple regression of fixed lactation curves of lactation multiple regression model with fixed lactation curves had the best fit for the first lactation test-day milk yields and the models which used a single regression of fixed curve had the best fit for the second and third lactations. Heritability for milk yield during lactation estimates did not vary among models but ranged from 0.22 to 0.34, from 0.11 to 0.21, and from 0.10 to 0.20, respectively, in the first three lactations. Similarly to heridability estimates of genetic correlations did not vary among models. The use of single or multiple fixed regressions for fixed lactation curves by RRM does not influence the estimates of genetic parameters for test-day milk yield across lactations.

Genetic evaluation for persistency of lactation in Holstein cows using a random regression model

A model for analyzing test day records including both fixed and random coefficients was applied to the genetic evaluation of first lactation data for Holstein cows. Data comprising 87045 test-day milk yield records from calving between 1997 and 2001 from Holstein herds in 10 regions of the Brazilian state of Minas Gerais. Six persistency of lactation measures were evaluated using breeding values obtained by random regression analyses. The Wilmink function was used to model the additive genetic and permanent environmental effects. Residual variance was constant throughout lactation. Ranking for animals did not change among criteria for persistency measurements, but ranking changes were observed when the estimated breeding value (EBV) for persistency of lactation was contrasted with those estimated for 305-day milk yield (305MY). The rank correlation estimates for persistency of lactation and 305MY were practically the same for sire and cows, and ranged from -0.45 to 0.69. The EBVs for milk yield during lactation for sires producing daughters with superior 305MY indicate genetic differences between sires regarding their ability to transmit desirable persistency of lactation traits. This suggests that selection for total lactation milk yield does not identify sires or cows that are genetically superior in regard to persistency of lactation. Genetic evaluation for persistency of lactation is important for improving the efficiency of the milk production capacity of Holstein cows.

An investigation into heterogeneity of variance for milk and fat yields of Holstein cows in Brazilian herd environments

Heterogeneity of variance in Brazilian herd environments was studied using first-lactation 305-day mature equivalent (ME) milk and fat records of Holstein cows. Herds were divided into two categories, according to low or high herd-year phenotypic standard deviation for ME milk (HYSD). There were 330 sires with daughter records in both HYSD categories. Components of (co)variance, heritability, and genetic correlations for milk and fat yields were estimated using a sire model from bivariate analyses with a restricted maximum likelihood (REML) derivative-free algorithm. Sire and residual variances for milk yield in low HYSD herds were 79 and 57% of those obtained in high HYSD herd. For fat yield they were 67 and 60%, respectively. Heritabilities for milk and fat yields in low HYSD herds were larger (0.30 and 0.22) than in high HYSD herds (0.23 and 0.20). Genetic correlation between expression in low and high HYSD herds was 0.997 for milk yield and 0.985 for fat yield. Expected correlated response in low HYSD herds based on sires selected on half-sister information from high HYSD was 0.89 kg/kg for milk and 0.80 kg/kg for fat yield. Genetic evaluations in Brazil need to account for heterogeneity of variances to increase the accuracy of evaluations and the selection efficiency for milk and fat yields of Holstein cows. Selection response will be lower in low variance herds than in high variance herds because of reduced differences in daughter response and among breeding values of sires in low HYSD herds. Genetic investments in sire selection to improve production are more likely to be successful in high HYSD herds than in low HYSD Brazilian herds.