285 resultados para fixed effects model.
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The objective of this study was to evaluate the effect of genotype by environment interaction (GEI) on the weight of Tabapuã cattle at 240 (W240), 365 (W365) and 450 (W450) days of age. In total, 35,732 records of 8,458 Tabapuã animalswhich were born in the state of Bahia, Brazil, from 1975 to 2001, from 167 sires and 3,707 dams, were used. Two birth seasons were tested as for the environment effect: the dry (D) and rainy (R) ones. The covariance components were obtainedby a multiple-trait analysis using Bayesian inference, in which each trait was considered as being different in each season. Covariance components were estimated by software gibbs2f90. As for W240, the model was comprised of contemporary groups and cow age (in classes) as fixed effects; animal and maternal genetic additive, maternal permanent environmental and residual were considered as random effects. Concerning W365 and W450, the model included only the contemporary aged cow groups as fixed effects and the genetic additive and residual effects of the animal as the random ones. The GEI was assessed considering the genetic correlation, in which values below 0.80 indicated the presence of GEI. Regarding W365 and W450, the GEI was found in both seasons. As for post-weaning weight (W240), the effect of such interaction was not observed. ©2012 Sociedade Brasileira de Zootecnia.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Aiming to establish selection criteria for the Brahman cattle in Brazil, the objective of this paper was to estimate genetic and environmental parameters for birth weight (BW), gestation length (GL) and scrotal circumference at 365 (SC365), 455 (SC455) and 550 (SC 550) days of age, and relative efficiency of indirect versus direct selection for these traits. Data were obtained from 15 851 animals belonging to 16 herds in six states, enrolled in a genetic breeding program. (Co)variance and heritability coefficients and genetic and environmental correlations between traits were estimated by restricted maximum likelihood (REML) under a multi trait animal model. The model included as fixed effects the contemporary group and the age of cow at calving as a covariate (linear and quadratic), and as random the direct genetic, the permanent environmental and residual effects. For BW and GL it was also considered the maternal genetic effect as random. Estimates of direct heritabilities were 0.36, 0.29, 0.55, 0.43 and 0.40 for BW, GL, SC365, SC455 and SC550, respectively. Genetic correlations between BW and GL, GL and SC365, GL and SC455, GL and SC550, SC365 and SC455, SC365 and SC550 and SC455 and SC550, were respectively 0.06, 0.13, 0.20, 0.13, 0.96, 0.98 and 0.99. The heritabilities estimates for all traits indicated these show enough additive genetic variability to respond favorably to selection. For sexual precocity, the best option would be SC365, due to the high value of heritability and to indirect selection at this age being more efficient than direct selection for PE455.
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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, 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. © FUNPEC-RP.
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The objectives of this study were to estimate genetic parameters involving yearling weight (Ps), carcass weight (Pc), hip height (Ag) and the scores of conformation (C), precocity (P) and musculature (M) and carcass yield (Rd) and finishing score (Ac) in Nellore cattle in order to define criteria for selection in this breed. The data of the 20 732 animals were obtained from Agrope-cuária Jacarezinho, SP. Data were analyzed by restricted maximum likelihood using animal model multi-trait analysis, which included fixed effects of contemporary groups (animals born at the same month and slaughtered on the same day) and the covariate age at slaughter (linear) for carcass traits, and contemporary groups (animals of the same farm, age, sex and management group at weaning and yearling) and yearling age (linear) for growth and as random, the additive effects and residual effects. Estimates ranged from 0.13 (Ac and Rd) to 0.36 (Ag) for heritability and from -0.59 ± 0.62 (Rd with Ac) to 0.71 ± 0.17 (Pc with C) for genetic correlations. Selection for Pc, C, P, M, Ag or Ps may be efficient because their heritability estimates are of magnitude moderate. Selection for Ps and C can favor heavier Pc, considering their positive and high genetic correlation.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Genética e Melhoramento Animal - FCAV
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Pós-graduação em Genética e Melhoramento Animal - FCAV
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Genética e Melhoramento Animal - FCAV
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Pós-graduação em Zootecnia - FCAV