929 resultados para Principal component analysis discriminant analysis
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The position of 125 countries is studied on the basis of a collection of 26 basic, health, economic and educational indicators. Multivariate statistical methods were used, including Cluster Analysis, Principal Component Analysis and Multivariate Analysis of Variance. The most discriminating variables were life expectancy the child mortality rate, the mortality rate of children of less than five years of age, the birth and fertility rates and the high-school female matriculation rate. The first principal component was interpreted as a measure of the living standard which made it possible to place the countries in order. Five clusters of countries are suggested.
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The slick hair coat (SLICK) is a dominantly inherited trait typically associated with tropically adapted cattle that are from Criollo descent through Spanish colonization of cattle into the New World. The trait is of interest relative to climate change, due to its association with improved thermo-tolerance and subsequent increased productivity. Previous studies localized the SLICK locus to a 4 cM region on chromosome (BTA) 20 and identified signatures of selection in this region derived from Senepol cattle. The current study compares three slick-haired Criollo-derived breeds including Senepol, Carora, and Romosinuano and three additional slick-haired cross-bred lineages to non-slick ancestral breeds. Genome-wide association (GWA), haplotype analysis, signatures of selection, runs of homozygosity (ROH), and identity by state (IBS) calculations were used to identify a 0.8 Mb (37.7-38.5 Mb) consensus region for the SLICK locus on BTA20 in which contains SKP2 and SPEF2 as possible candidate genes. Three specific haplotype patterns are identified in slick individuals, all with zero frequency in non-slick individuals. Admixture analysis identified common genetic patterns between the three slick breeds at the SLICK locus. Principal component analysis (PCA) and admixture results show Senepol and Romosinuano sharing a higher degree of genetic similarity to one another with a much lesser degree of similarity to Carora. Variation in GWA, haplotype analysis, and IBS calculations with accompanying population structure information supports potentially two mutations, one common to Senepol and Romosinuano and another in Carora, effecting genes contained within our refined location for the SLICK locus.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In this paper we describe how morphological castes can be distinguished using multivariate statistical methods combined with jackknife estimators of the allometric coefficients. Data from the polymorphic ant, Camponotus rufipes, produced two distinct patterns of allometric variation, and thus two morphological castes. Morphometric analysis distinguished different allometric patterns within the two castes, with overall variability being greater in the major workers. Caste-specific scaling variabilities were associated with the relative importance of first principal component. The static multivariate allometric coefficients for each of 10 measured characters were different between castes, but their relative magnitudes within castes were similar. Multivariate statistical analysis of worker polymorphism in ants is a more complete descriptor of shape variation than, and provides statistical and conceptual advantages over, the standard bivariate techniques commonly used.
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Beef quality control, particularly its sensory characteristics, is an important factor for producers and retailers in order to satisfy consumer’s choices. Sensory analysis is an important tool to evaluate attributes that cannot be measured by easily available instrumental techniques, as well as texture – tenderness and juiciness – whose human perception is more complete, through trained panels. The aim of this study was evaluate the use of a beef sensory analysis protocol in three different laboratories. Six commercial samples of different brands of aged beef and 14 samples from crossbred animals (Bonsmara × Nelore - 7 and Canchim × Nelore - 7), aged during 14 days were analyzed. The samples were distributed to each participant laboratory, where 7 to 12 panelists were trained. A sheet containing a 9 cm non-structured scale with 14 attributes was used. The attributes were brown colour (CMAR); aponevrosis (PNAP); hydration degree (GH); characteristic beef aroma (SCCB); salty taste (SS); liver flavour (SF); fat flavour (SG); metallic flavour (SM); tenderness (MZ); juiciness (SL); fibrosity (FBS) and liver texture (SF). Obtained data was analyzed using analysis of variance and principal component analysis (PCA). The results showed that there was no interaction between samples and laboratories, indicating that all of them responded in a similar manner in relation to the samples, except PNAP attribute, which was expected as meat is very non-uniform normally. Samples were well differentiated in all laboratories as it could be observed in PCA graphs. With proper training it is possible to use a standard protocol for beef sensory analysis.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)