Genetic analysis of feet and legs in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Parâmetros genéticos para características de desempenho e reprodutivas de aves poedeiras por inferência bayesiana

Pós-graduação em Genética e Melhoramento Animal - FCAV

Associação genética de características de qualidade de carne e precocidade sexual em animais Nelore (Bos indicus)

Pós-graduação em Genética e Melhoramento Animal - FCAV

Genetic associations between scrotal circumference and female reproductive traits in Nelore cattle

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

Genetic analysis of the temperament of Nellore cattle using linear and threshold models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genetic relationship among reproductive traits in Nellore cattle

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

A non-homogeneous poisson model with spatial anisotropy applied to ozone data from Mexico City

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimativas de parâmetros genéticos para características morfométricas em cavalos Quarto de Milha de Corrida

With highlighted sprint ability, the racing line is important segment within the Quarter Horses breed, with huge impact on agribusiness. Theseanimals have noted morphological differences when compared to other lines within the breed, especially for larger body size proportions.The objective of this study was to estimate genetic parameters forbody measurements traitsof the racing line of the Quarter Horses breed via Bayesian inference. Here,289 animals of both sexes, registered at brazilian association of breeders (ABQM), were used. The results showed high coefficient of heritability for body length (0.74) and back-loin lenght(0.61). The heritability coefficients for height at withersand croup length were moderate (0.44 and 0.47, respectively). High genetic correlation for body length and croup length and for body length and back-loins lengthwas also observed(0.80 and 0.76, respectively). Taking into account the estimates of heritability and genetic correlations between body measurement traits, the body length and height at withers traits proved to be appropriate to provide future researches that investigate the genetic correlation between body measurements and racing performance.

Estimativas de parâemtros genéticos para características morfométricas em cavalos Quarto de Milha de corrida

With highlighted sprint ability, the racing line is important segment within the Quarter Horses breed, with huge impact on agribusiness. Theseanimals have noted morphological differences when compared to other lines within the breed, especially for larger body size proportions.The objective of this study was to estimate genetic parameters forbody measurements traitsof the racing line of the Quarter Horses breed via Bayesian inference. Here,289 animals of both sexes, registered at brazilian association of breeders (ABQM), were used. The results showed high coefficient of heritability for body length (0.74) and back-loin lenght(0.61). The heritability coefficients for height at withersand croup length were moderate (0.44 and 0.47, respectively). High genetic correlation for body length and croup length and for body length and back-loins lengthwas also observed(0.80 and 0.76, respectively). Taking into account the estimates of heritability and genetic correlations between body measurement traits, the body length and height at withers traits proved to be appropriate to provide future researches that investigate the genetic correlation between body measurements and racing performance. Keywords: Heritability, Correlation, Length, Heigth.

Modelos lineares generalizados bayesianos para dados longitudinais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.

Application of dendrogeomorphology on the study of soil sediment deposition in the stems of Guarea guidonea trees in a disturbed riparian forest in Goias state, Brazil

The sediments resulting of natural or anthropic erosion are deposited on the soil surface and around the trunks of trees occurring in riparian forests. For assessment of the erosion, tree-rings of roots and stems were analyzed. Guarea guidonea trees from a riparian forest affected by the sedimentation of soil erosion from pastures and soybean fields in state of Goias were selected. Wood samples were extracted through a non-destructive method at three heights from trunks of trees located in three positions (top, middle and bottom) of a riparian slope. The evaluation revealed a deposition of a thick sediment layer up to 34 cm around the base of tree trunks during the past 24 years. The inter-correlations between the tree-rings widths present in wood samples at the base and at 50 and 100 cm from Guarea guidonea tree trunks presented low, medium and high values. These values resulted from the low tree-rings distinctiveness in the wood; the absence of some rings as well as the eccentricity of the pith. The analyses of dendrogeomorphology allowed the determination of the date of seed germination and tree growth and inference on the periods of sediment deposition in the trunk of the trees.

A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

Mayaro Virus Infection in Amazonia: A Multimodel Inference Approach to Risk Factor Assessment

Background: Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data - particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment. Methodology/Principal Findings: A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (beta +/- SE) on which to base inference. Residence area (beta(Village) = 2.93 +/- 0.41; beta(Upland) = -0.56 +/- 0.33, beta(Riverbanks) = -2.37 +/- 0.55) and bednet use (beta = -0.95 +/- 0.28) were the most important factors, followed by crop-plot ownership (beta = 0.39 +/- 0.22) and regular use of a closed toilet/latrine (beta = 0.19 +/- 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. Conclusions/Significance: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.

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.