907 resultados para Mixed model under selection
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The aims of this study were to assess the validity and the feasibility of the qualitative behavior assessment (QBA) method as indicator of Nellore cattle temperament under field conditions, evaluating its associations with four other traditional methods and weight gain. The temperament and live weight of 2229 Nellore cattle was assessed at approximately 550 days of age. Five measurements of cattle temperament were recorded: flight speed test (FS, in m/s), visual scores of movement in the crush (MOV), crush score (CS), temperament score (TS), and the qualitative behavior assessment method (QBA), by using a list of 12 behavioral based adjectives as descriptors of temperament. Average daily weight gain (ADG) was calculated for each animal. For statistical analysis of QBA data, the Principal Component Analysis was used. A temperament index (TI) was defined for each animal using the scores for the first principal component. Pearson's correlation coefficients were estimated between TI with FS and ADG. A mixed model ANOVA was used to analyze the TI variation as a function of TS, CS, and MOV. The score plot for the first and second principal components was used to classify the cattle in four groups (from very bad to very good temperament). The first principal component explained 49.50% of the variation in the data set, with higher positive loadings for the adjectives 'agitated' and 'active', and higher negative loadings for 'calm' and 'relaxed'. TI was significantly correlated with FS (r=0.49; P<0.01) and ADG (r=-0.10; P<0.01). The means of ADG, FS, and the temperament scores (CS, TS, MOV) differed significantly (P<0.01) among the four groups, from very bad to very good temperament. The QBA method could discriminate different behavioral profiles of Nellore cattle and were in agreement with other traditional methods used as indicators of cattle temperament. Additional studies are needed to assess the inter- and intra-observers reliability and to study its association with physiological parameters. © 2013 Elsevier B.V.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Matematica Aplicada e Computacional - FCT
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Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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De acordo com o modo causal de seleção por consequências proposto por Skinner, o comportamento humano é o produto de processos seletivos em três níveis: filogênese, ontogênese e cultura. Investigações empíricas que se ocupem do terceiro nível apenas começam a ser realizadas na análise do comportamento. No campo teórico, Glenn introduziu o conceito de Metacontingência para enfocar relações funcionais entre contingências de reforçamento entrelaçadas e um produto agregado que seleciona o próprio entrelaçamento. Um trabalho pioneiro na reprodução em laboratório de uma metacontingência foi produzido por Vichi, a partir da adaptação de um método usado em estudos experimentais na sociologia. O estudo de Vichi sugere que o entrelaçamento dos comportamentos das pessoas de um pequeno grupo pôde ser modificado por produtos agregados que estes entrelaçamentos produziam, caracterizando uma Metacontingência. O presente trabalho consistiu de uma replicação do estudo de Vichi, com o objetivo de verificar se contingências comportamentais entrelaçadas podem de fato ser selecionadas e mantidas por um produto agregado contingente aos comportamentos dos membros de um pequeno grupo em uma microcultura de laboratório. Participaram da pesquisa oito alunos universitários, divididos em dois grupos de quatro, que realizaram uma tarefa em grupo. A tarefa consistiu em resolver um problema, escolhendo uma linha de uma matriz de 8 colunas por 8 fileiras, com sinais positivos e negativos. Os participantes escolhiam as linhas e o experimentador escolhia as colunas. Um sinal positivo na interseção das duas escolhas resultava em ganho para o grupo; um sinal negativo, em perda. A escolha da coluna pelo experimentador não foi aleatória, mas contingente ao modo de distribuição (igualitária ou desigual) dos ganhos pelo grupo na tentativa imediatamente anterior. Na condição experimental A, o acerto era contingente a distribuições igualitárias, já na condição experimental B, o acerto era contingente a distribuições desiguais. Os resultados mostram que o grupo 1 acertou 43% das jogadas (dividiu os recursos de acordo com a condição experimental que estava em vigor) e o grupo 2 acertou 19% das jogadas. Os resultados indicam que o fato do procedimento utilizar consequências (acertos ou erros) contingentes, porém não contíguas ao entrelaçamento do grupo, dificultou a seleção de tal entrelaçamento. Entretanto, contingências de reforçamento entrelaçadas foram selecionadas por seus produtos agregados sob controle de variáveis não controladas no experimento. Caracteriza-se este fenômeno enquanto um análogo experimental de uma metacontingência. Discute-se o procedimento utilizado, possíveis aprimoramentos deste e a complexidade da tarefa experimental, além, também, de discutir alguns padrões de regras supersticiosas que emergiram durante o experimento.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Adjusting autoregressive and mixed models to growth data fits discontinuous functions, which makes it difficult to determine critical points. In this study we propose a new approach to determine the critical stability point of cattle growth using a first-order autoregressive model and a mixed model with random asymptote, using the deterministic portion of the models. Three functions were compared: logistic, Gompertz, and Richards. The Richards autoregressive model yielded the best fit, but the critical growth values were adjusted very early, and for this purpose the Gompertz model was more appropriate.
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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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The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.
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Pós-graduação em Agronomia - FEIS
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The objective of this study was to assess families and highlight the superior progenies of sugarcane originating from 38 biparental crosses for the following attributes: tons of cane per hectare (TCH), tons of biomass per hectare (TBIOH), brix (% cane juice), fiber content, purity, pol and total recoverable sugar (TRS). The data were analyzed by mixed model REML / BLUP in the REML (Restricted Maximum Likelihood) allowed us to estimate genetic parameters and BLUP (best linear unbiased prediction) to predict the additive and genotypic values. The best family for the attributes TCH and TBIOH was 41, whose parents are cultivars IACSP022019 x CTC9. In individual selection for TCH, the plant number 3 of Block 2, the crossing 78, showed the best results. To TBIOH the plant number 33, Block 1, family 41, showed the best results. Families 40, 41, 43, 68, 69, 79, 91, 92 and 147, were higher for the variables brix, pol, purity, and ATR, where as 85 families, 147, 148, 149, 161, 163, 177, 178, 179, and 183 were higher for fiber. The family 147 whose parents are IACSP042286 x IACSP963055, showed three progenies ranked among the top ten for both brix, and for fiber, which identifies the combination as a potential source of progenies for bioenergy production.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Zootecnia - FMVZ