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.

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

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.

Bacille Calmette-Guérin/DNAhsp65 prime-boost is protective against diabetes in non-obese diabetic mice but not in the streptozotocin model of type 1 diabetes

Type I diabetes is a disease caused by autoimmune destruction of the beta cells in the pancreas that leads to a deficiency in insulin production. The aim of this study was to evaluate the prophylactic potential of a prime-boost strategy involving bacille Calmette-Guérin (BCG) and the pVAXhsp65 vaccine (BCG/DNAhsp65) in diabetes induced by streptozotocin (STZ) in C57BL/6 mice and also in spontaneous type 1 diabetes in non-obese diabetic (NOD) mice. BCG/DNAhsp65 vaccination in NOD mice determined weight gain, protection against hyperglycaemia, decreased islet inflammation, higher levels of cytokine production by the spleen and a reduced number of regulatory T cells in the spleen compared with non-immunized NOD mice. In the STZ model, however, there was no significant difference in the clinical parameters. Although this vaccination strategy did not protect mice in the STZ model, it was very effective in NOD mice. This is the first report demonstrating that a prime-boost strategy could be explored as an immunomodulatory procedure in autoimmune diseases. © 2013 British Society for Immunology.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

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.

Distribuição espacial e plano de amostragem sequencial para Euschistus heros (Fabricius, 1794) (Heteroptera: Pentatomidae) na cultura da soja convencional e transgênica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo da correlação entre propriedades não-ôhmicas, processos de relaxação dielétrica e microestrutura de cerâmicas policristalinas do tipo (Ca IND. 1/4 Cu IND. 3/4)TiO IND. 3

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento e avaliação de equipamentos e metodologia para determinação de parâmetros físicos do solo relacionados a dias trabalháveis com máquinas agrícolas

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Associações genéticas com o marcador alfa actina 1, e variabilidade genética de características de importância econômica de frangos de corte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo das tensões em próteses sobre implantes esplintadas: análise pelo método da fotoelasticidade

Pós-graduação em Odontologia - FOA

Genetic parameters for body weight in buffaloes (Bubalus bubalis) in Colombia using random regression models

The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32 +/- 0.05), decreasing thereafter until one year of age (0.18 +/- 0.04) and increased again, reaching 0.39 +/- 0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11 +/- 0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60 +/- 0.060) to high (0.99 +/- 0.001), maternal genetic correlations showed a similar range (0.41 +/- 0.401 and 0.99 +/- 0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning. (C) 2013 Elsevier B.V. All rights reserved.

Genetic Parameters for Milk Yield and Lactation Length of Crossbred Buffaloes from Brazil by Bayesian Inference

The objective of the study was to estimate heritability and repeatability for milk yield (MY) and lactation length (LL) in buffaloes using Bayesian inference. The Brazilian genetic improvement program of buffalo provided the data that included 628 females, from four herds, born between 1980 and 2003. In order to obtain the estimates of variance, univariate analyses were performed with the Gibbs sampler, using the MTGSAM software. The model for MY and LL included direct genetic additive and permanent environment as random effects, and contemporary groups, milking frequency and calving number as fixed effects. The convergence diagnosis was performed with the Geweke method using an algorithm implemented in R software through the package Bayesian Output Analysis. Average for milk yield and lactation length was 1,546.1 +/- 483.8 kg and 252.3 +/- 42.5 days, respectively. The heritability coefficients were 0.31 (mode), 0.35 (mean) and 0.34 (median) for MY and 0.11 (mode), 0.10 (mean) and 0.10 (median) for LL. The repeatability coefficient (mode) were 0.50 and 0.15 for MY and LL, respectively. Milk yield is the only trait with clear potential for genetic improvement by direct genetic selection. The repeatability for MY indicates that selection based on the first lactation could contribute for an improvement in this trait.

Flavor-changing neutral currents in the minimal 3-3-1 model revisited

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

N=1 super sinh-Gordon model in the half line: breather solutions

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

Search for the Higgs boson H-2(0) at LHC in 3-3-1 model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

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