Caracterização da diversidade genética de Stryphnodendron adstringens (Mart.) Coville por marcador molecular AFLP e transferência de microssatélites

Pós-graduação em Agronomia (Horticultura) - FCA

Genes de efeito principal e locos de características quantitativas (QTL) em suínos

Pós-graduação em Zootecnia - FMVZ

A meta-analysis of the feed intake and growth performance of broiler chickens challenged by bacteria

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

Monitoramento de processos multivariados autocorrelacionados

Technological advances and the availability of computational resources have been facilitating the collection and processing of data. Thus, the natural tendency of the monitoring processes is the simultaneous control of various quality characteristics. In automated processes, observations are generally autocorrelated. Studies with univariate graph for processes have shown that the autocorrelation reduces the ability of this signal changes in the process. In this paper, we study the multivariate autocorrelated processes. Through simulations are obtained properties of graphs, monitoring the mean vector, the properties of graphs VMAX, in monitoring the covariance matrix, and the properties of graphs MCMAX, the simultaneous monitoring of mean vector and covariance matrix. Conclude that increasing the autocorrelation and the number of variables being monitored, reduces the power of the graphics in signal of a special cause

Genome-wide association study of reproduction traits in Nelore cattle, including additional phenotypic information from non-genotyped animals

Pós-graduação em Genética e Melhoramento Animal - FCAV

Análise de pedigree e estimativas de parâmetros genéticos para características reprodutivas em bovinos da raça Brahman

Pós-graduação em Ciência e Tecnologia Animal - FEIS

Metodologia de atribuição dos escores visuais e estudo de associação genômica para os escores de conformação, precocidade e musculosidade em bovinos Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Non-synonymous mutations mapped to chromosome X associated with andrological and growth traits in beef cattle

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

Attribute charts for monitoring the mean vector of bivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Efeito da utilização de diferentes critérios de controle de qualidade dos genótipos em estudos de associação e seleção genômica ampla

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

Estudo de associação entre polimorfismos de base única com características de eficiência de conversão, consumo e desempenho em bovinos da raça Nelore

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelos lineares generalizados mistos e equações de estimação generalizadas para dados binário aplicados em anestesiologia veterinária

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Seleção e associação genômica para precocidade sexual em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Spatial statistical models that use flow and stream distance

We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions.

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken. (C) 2012 Elsevier B.V. All rights reserved.