Milk yield persistency in Brazilian Gyr cattle based on a random regression model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Genetic parameters for production traits of dairy Gyr (Bos indicus) x Holstein cattle estimated with a random regression model

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

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

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)

Estimation of genetic parameters for partial egg production periods by means of random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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)

NEAR-RESONANT SCATTERING FROM NONSYMMETRIC DIMERS - APPLICATIONS TO SUBSTITUTED POLYANILINES

In this work we show that, beyond the prediction of the random dimer model [Wu and Phillips, Phys. Rev. Lett. 66, 1366 (1991)], it is possible to have near resonant scattering from nonsymmetric dimers. It is shown by direct density of states calculations as well as by a procedure similar to the random dimer model that protonated chains of alkyl-substituted polyanilines support extended electronic states at the Fermi energy when a disordered distribution of symmetric or asymmetric bipolarons is present. An extension of the random dimer model to include resonant scattering by nonsymmetric dimers is proposed.

Modeling metabolizable energy utilization in broiler breeder pullets

The objective of this study was to determine models for ME requirements for broiler breeder pullets using the factorial method. The influence of the temperature on maintenance ME requirements was determined by experiments conducted in three environmental rooms with temperature kept constant at 15, 22, and 30°C, using the comparative slaughter technique. The energy requirements for weight gain were determined based on the body energy content and efficiency of energy utilization for weight gain. Two ME requirement models for each age were developed using the coefficients for maintenance and weight gain. The models for 3 to 8 wk were ME = W 0.75 (186.52 - 1.94T) + 2.47WG, and ME = W 0.75 (174 - 1.88T) + 2.83WG; for 9 to 14 wk, ME = W 0.75 (186.52 - 1.94T) + 2.69WG, and ME = W 0.75 (174 - 1.88T) + 2.50WG; and 15 to 20 wk, ME = W 0.75 (186.52 - 1.94T) + 2.76WG, and ME = W 0.75 (174 - 1.88T) + 3.24WG. In these equations, W is BW (kg), T is temperature (°C), and WG is daily weight gain (g). These models were compared to the breeder's recommendations in a feeding trial from 5 to 20 wk of age. Models 1 and 2 provided energy intakes that promoted BW smaller than the breeder's recommendation. However, all breeder pullets had weights above the standard recommendation. Model 2 gave the smallest ME intake and BW close to the standard recommendation and provided the best prediction of ME requirements.

Modeling energy utilization and growth parameter description for broiler chickens

Two experiments were conducted to develop and evaluate a model to estimate ME requirements and determine Gompertz growth parameters for broilers. The first experiment was conducted to determine maintenance energy requirements and the efficiencies of energy utilization for fat and protein deposition. Maintenance ME (ME m) requirements were estimated to be 157.8, 112.1, and 127.2 kcal of ME/kg 0.75 per day for broilers at 13, 23, and 32°C, respectively. Environmental temperature (T) had a quadratic effect on maintenance requirements (ME m = 307.87 - 15.63T + 0.3105T 2; r 2= 0.93). Energy requirements for fat and protein deposition were estimated to be 13.52 and 12.59 kcal of ME/g, respectively. Based on these coefficients, a model was developed to calculate daily ME requirements: ME = BW 0.75 (307.87 - 15.63T + 0.3105 T 2) + 13.52 G f + 12.59 G p. This model considers live BW, the effects of environmental temperature, and fractional fat (G f) and protein (G p) deposition. The second experiment was carried out to estimate the growth parameters of Ross broilers and to collect data to evaluate the ME requirement model proposed. Live BW, empty feather-free carcass, weight of the feathers, and carcass chemical compositions were analyzed until 16 wk of age. Parameters of Gompertz curves for each component were estimated. Males had higher growth potential and higher capacity to deposit nutrients than females, except for fat deposition. Data of BW and body composition collected in this experiment were fitted into the energy model proposed herein and the equations described by Emmans (1989) and Chwalibog (1991). The daily ME requirements estimated by the model determined in this study were closer to the ME intake observed in this trial compared with other models. ©2005 Poultry Science Association, Inc.

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.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.