16 resultados para Análise de originais

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Foram utilizados dados de 288 codornas de corte (Coturnix coturnix coturnix) para avaliar a possibilidade de resumir a informação contida no complexo de variáveis originais, eliminando-se variáveis inexpressivas por meio da técnica de componentes principais. Foram registrados o peso vivo (PVIVO) e pesos do peito (PPEITO), das coxas (PCOXA), da gordura abdominal (GA), das vísceras comestíveis (fígado, moela e coração) (FIG, MOELA e CORA) e da carcaça eviscerada (PCEVIS). As carcaças foram secas e trituradas para a avaliação do teor matéria seca (MS), gordura (GORD) e proteína bruta (PB). Dos 11 componentes principais, sete (63,6%) apresentaram variância menor que 0,7 (autovalor inferior a 0,7), sendo sugeridas para descarte, respectivamente, em ordem de menor importância, para explicar a variação total das seguintes variáveis: PCEVIS, PPEITO, PCOXA, CORA, FIG MOELA e GORD. Com base nos resultados, recomenda-se manter as seguintes variáveis em experimentos futuros: PVIVO, MS, PB e GA.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

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

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The soybean crop is considered a high expression around the world. In plant breeding programs, knowledge of genetic diversity is extremely important and in this context, are frequently used multivariate analyzes. Thus, the aim of the present study was to evaluate the genetic divergence between soybean crosses through multivariate techniques. In total, 16 crosses were evaluated, which were in the F2 generation of inbreeding. The evaluated characteristics were plant height at maturity, height of the first pod, number of branches per plant, number of pods per plant, number of nodes per plant, hundred seed weight, grain yield and oil content. For the analyzes was used Euclidean distance, methods of hierarchical clustering UPGMA and Ward and principal component analysis. Genetic distances estimated using Euclidean distance ranged from 1.24 to 8.13, with the smallest distance observed between crosses C1 and C4, and the greatest distance between the C2 crosses and C6. The methods UPGMA clustering and Ward met crossings in five different groups. The principal component analysis explained 86.2% of the variance contained in the original eight variables with three main components. The APM characters, NV, NR, NN, PG% and oil were the main contributors to genetic divergence among traits. Multivariate techniques were crucial to the analysis of genetic diversity, and the methods of Ward and UPGMA clustering and principal components have consistent results in this way, the simultaneous use of these tools in genetic analysis of crosses is indicated

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Pós-graduação em Estudos Linguísticos - IBILCE

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The objective of this paper is to relate the set of financial ratios that are directly related to the success of public traded companies using a methodological approach and the method of multivariate principal component analysis. This study consists in the use of profitability ratios, debt and liquidity, to define the relationship between financial ratios with the best public traded companies listed in the magazine Exame Melhores e Maiores of 2013. Multivariate analysis was used to reduce the dimensionality of multivariate data, making linear combinations of the original variables (financial ratios) and express the data in principal components that result in new variables that contains much of the original data. As a result, we got the optimal number of five principal components, and both represent 95.6% of the original data. Among of all financial ratios, we can highlight the direct relationship between profitability ratios for the first principal component, and the direct relationship between the liquidity ratios, both inversely related with non-capital participation rates and degree indebtedness to the second principal component

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Pós-graduação em Biometria - IBB

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)