855 resultados para 280212 Neural Networks, Genetic Alogrithms and Fuzzy Logic
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The effect of competition is an important source of variation in breeding experiments. This study aimed to compare the selection of plants of open-pollinated families of Eucalyptus with and without the use of competition covariables. Genetic values were determined for each family and tree and for the traits height, diameter at breast height and timber volume in a randomized block design, resulting in the variance components, genetic parameters, selection gains, effective size and selection coincidence, with and without the use of covariables. Intergenotypic competition is an important factor of environmental variation. The use of competition covariables generally reduces the estimates of variance components and influences genetic gains in the studied traits. Intergenotypic competition biases the selection of open-pollinated eucalypt progenies, and can result in an erroneous choice of superior genotypes; the inclusion of covariables in the model reduces this influence.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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O objetivo deste trabalho foi a caracterização genética de quatro novas estirpes de Rhizobium e a avaliação de sua capacidade de fixação de N2 e nodulação, comparadas a estirpes comerciais e à população nativa de rizóbios de um Latossolo Vermelho. Dois experimentos foram conduzidos em blocos ao acaso, em casa de vegetação. No primeiro experimento, conduzido em tubetes com vermiculita, avaliaram-se a nodulação e a capacidade de fixação das novas estirpes, em comparação com as estirpes comerciais CIAT-899 e PRF-81 e com a população nativa do solo. Das colônias puras isoladas, extraiu-se o DNA genômico e realizou-se o seqüenciamento do espaço intergênico, para a caracterização genética das estirpes e da população nativa de rizóbios. O segundo experimento foi realizado em vasos com solo, para determinação da produtividade e da nodulação do feijoeiro, cultivar Pérola, com o uso das estirpes isoladamente ou em mistura com a PRF-81. A população nativa do solo foi identificada como Rhizobium sp. e se mostrou ineficiente na fixação de nitrogênio. Foram encontradas três espécies de Rhizobium entre as quatro novas estirpes. As estirpes LBMP-4BR e LBMP-12BR estão entre as que têm maior capacidade de nodulação e fixação de N2, e apresentam respostas diferenciadas quando misturadas à PRF-81.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Carcass and meat quality traits of thirty-six feedlot beef heifers from different genetic groups (GG) fed at two concentrate levels (CL) were evaluated using 12- Nellore (NE), 12 - 1/2Angus x 1/2Nellore (AN) and 12 - 1/2Simmental x 1/2Nellore (SN) animals. Six heifers of each GG were randomly assigned into one of two treatments: concentrate at 0.8% or 1.2% of body weight (BW). Heifers fed concentrate at 0.8% of BW had greater (P<0.05) dressing percentage. None of the proximate analysis components of the beef were affected (P>0.05) by either CL or GG. Heifers from the AN group had higher (P<0.05) carcass weights, 12th rib fat thickness and lower dressing percentage (P<0.05) compared to the other groups. NE heifers had greater WBSF values (P<0.05) than the other genetic groups. Data suggest that the concentrate level can be reduced without compromising meat quality traits. (C) 2011 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The objectives of the current study were to investigate the additive genetic associations between heifer pregnancy at 16 months of age (HP16) and age at first calving (AFC) with weight gain from birth to weaning (WG), yearling weight (YW) and mature weight (MW), in order to verify the possibility of using the traits measured directly in females as selection criteria for the genetic improvement of sexual precocity in Nelore cattle. (Co)variance components were estimated by Bayesian inference using a linear animal model for AFC, WG, YW and MW and a nonlinear (threshold) animal model for HP16. The posterior means of direct heritability estimates were: 0.45 +/- 0.02; 0.10 +/- 0.01; 023 +/- 0.02; 0.36 +/- 0.01 and 0.39 +/- 0.04, for HP16, AFC, WG, YW and MW, respectively. Maternal heritability estimate for WG was 0.07 +/- 0.01. Genetic correlations estimated between HP16 and WG, YW and MW were 0.19 +/- 0.04; 0.25 +/- 0.06 and 0.14 +/- 0.05, respectively. The genetic correlations of AFC with WG, YW and MW were low to moderate and negative, with values of -0.18 +/- 0.06; -0.22 +/- 0.05 and -0.12 +/- 0.05, respectively. The high heritability estimated for HP16 suggests that this trait seem to be a better selection criterion for females sexual precocity than AFC. Long-term selection for animals that are heavier at young ages tends to improve the heifers sexual precocity evaluated by HP16 or AFC. Predicted breeding values for HP16 can be used to select bulls and it can lead to an improvement in sexual precocity. The inclusion of HP16 in a selection index will result in small or no response for females mature weight. (C) 2011 Elsevier B.V. All rights reserved.
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ln this work, it was deveIoped a parallel cooperative genetic algorithm with different evolution behaviors to train and to define architectures for MuItiIayer Perceptron neural networks. MuItiIayer Perceptron neural networks are very powerful tools and had their use extended vastIy due to their abiIity of providing great resuIts to a broad range of appIications. The combination of genetic algorithms and parallel processing can be very powerful when applied to the Iearning process of the neural network, as well as to the definition of its architecture since this procedure can be very slow, usually requiring a lot of computational time. AIso, research work combining and appIying evolutionary computation into the design of neural networks is very useful since most of the Iearning algorithms deveIoped to train neural networks only adjust their synaptic weights, not considering the design of the networks architecture. Furthermore, the use of cooperation in the genetic algorithm allows the interaction of different populations, avoiding local minima and helping in the search of a promising solution, acceIerating the evolutionary process. Finally, individuaIs and evolution behavior can be exclusive on each copy of the genetic algorithm running in each task enhancing the diversity of populations
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Relaxed conditions for stability of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed methods provide better or at least the same results of the methods presented in the literature. Numerical results exemplify this fact. These results are also used for fuzzy regulators and observers designs. The nonlinear systems are represented by fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by linear matrix inequalities, that can be solved efficiently using convex programming techniques. The specification of the decay rate, constrains on control input and output are also discussed.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)