1000 resultados para Multivariada Analysis


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The acceptability of nine commercial brazilian varietal white table wines (Riesling, Chardonnay and Gewürztraminer) was evaluated using sensory affective tests. The samples were assessed by 43 consumers of brazilian white wines using he nine-point structured hedonic scale. Judges were recruited based on their responses to a questionnary about consumer?s behavior towards white wines consumption. Subsequently, Analysis of Variance (ANOVA) with means comparision (Tukey test) and Internal Analysis of Preference Mapping (MDPREF) were performed on data. Analysis of Variance showed that two samples (a Riesling and a Gewürztraminer, both sweet table wines) had significantly (p < 0.05) higher acceptance means, around 7 in the hedonic scale. The least acceptance means (4,3) was obtained by a demi-sec Chardonnay wine and the other six samples achieved means around 5 in the hedonic scale, all of them either demi-sec or dry table wines. MDPREF confirmed the results showed by ANOVA showing that samples were segmented into two groups of preference. The first group was composed by 86% of consumers who prefered the sweet table wines (higher acceptance), converging to the region on the map where these samples were represented. Only 14% showed preference for the demi-sec and dry table wines, being represented on the region of the MDPREF where these samples were located. This study suggests that sweet table wines are prefered by Brazilian consumers, instead of dry or demi-sec table wines.

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Breast weight has great economic importance in poultry industry, and may be associated with other variables. This work aimed to estimate phenotypic correlations between performance (live body weight at 7 and 28 days, and at slaughter, and depth of the breast muscle measured by ultrasonography), carcass (eviscerated body weight and leg weight) and body composition (heart, liver and abdominal fat weight) traits in a broiler line, and quantify the direct and indirect influence of these traits on breast weight. Path analysis was used by expanding the matrix of partial correlation in coefficients which give the direct influence of one trait on another, regardless the effect of the other traits. The simultaneous maintenance of live body weight at slaughter and eviscerated body weight in the matrix of correlations might be harmful for statistical analysis involving systems of normal equations, like path analysis, due to the observed multicollinearity. The live body weight at slaughter and the depth of the breast muscle as measured by ultrasonography directly affected breast weight and were identified as the most responsible factors for the magnitude of the correlation coefficients obtained between the studied traits and breast weight. Individual pre-selection for these traits could favor an increased breast weight in the future reproducer candidates of this line if the broilers' environmental conditions and housing are maintained, since the live body weight at slaughter and the depth of breast muscle measured by ultrasonography were directly related to breast weight.

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The aim of the present study was to evaluate the effect of soil characteristics (pH, macro- and micro-nutrients), environmental factors (temperature, humidity, period of the year and time of day of collection) and meteorological conditions (rain, sun, cloud and cloud/rain) on the flavonoid content of leaves of Passiflora incarnata L., Passifloraceae. The total flavonoid contents of leaf samples harvested from plants cultivated or collected under different conditions were quantified by high-performance liquid chromatography with ultraviolet detection (HPLC-UV/PAD). Chemometric treatment of the data by principal component (PCA) and hierarchic cluster analyses (HCA) showed that the samples did not present a specific classification in relation to the environmental and soil variables studied, and that the environmental variables were not significant in describing the data set. However, the levels of the elements Fe, B and Cu present in the soil showed an inverse correlation with the total flavonoid contents of the leaves of P. incarnata.

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S'ha portat a terme una analisi estadística de les dades craniometriques de les principals poblacions catalano-balears del passat, des de J'Edat del Bronze fins a l'Edat Mitjana, i posteriorment s'han integrat les poblacions en un context peninsular més ampli. S'han analitzalles relacions entre poblacions per mitja d'un analisi d'agrupament (cluster), emprant els algoritmes UPGMA i del "veí més proper" i la distancia euclídea al quadrat. Així mateix, s'ha realitzat un re-mostreig (bootstrap) per comprovar la robustes de les agrupacions obtingudes i un test de Mantel per comprovar el grau de concordan~a entre les poblacions femenines i masculines. Els resultats mostren que, a nivell peninsular, els Bascos són la població més diferenciada de la resta des d'un punt de vista morfologic, la qual cosa pot estar relacionada amb una major antiguitat d'aquesta població, potser present des de temps pre-neolítics. La segona font de variació peninsular la constitueixen dues poblacions amb possibles influencies foranies d'origen africa: jueus i musulmans. La resta de poblacions, incloent-hi les de Mallorca, són notablement homogenies a pesar de la seva heterogene'itat cultural, temporal i geogràtfica. Finalment, es conclou que no hi ha cap analisi estadística que objectivament recolzi I'existencia deIs tipus racials tradicionalmcnt descrits a la Península Iberica, i que responen a una visió tipologica i estatica de la diversitat humana.

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A multivariate calibration method to determine chemical compositions of systems with severely overlapped bands is proposed. Q mode factors are determined from the spectral data and subsequently rotated using the varimax and oblique transformation of Imbrie. The method is applied to two sets of simulated data to test the sensitivity of analytical results to random experimental error. The chemical concentrations of alanine and threonine mixture are determined from spectral data of the 302,5 - 548,5 nm region.

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The aim of this work is to present a tutorial on Multivariate Calibration, a tool which is nowadays necessary in basically most laboratories but very often misused. The basic concepts of preprocessing, principal component analysis (PCA), principal component regression (PCR) and partial least squares (PLS) are given. The two basic steps on any calibration procedure: model building and validation are fully discussed. The concepts of cross validation (to determine the number of factors to be used in the model), leverage and studentized residuals (to detect outliers) for the validation step are given. The whole calibration procedure is illustrated using spectra recorded for ternary mixtures of 2,4,6 trinitrophenolate, 2,4 dinitrophenolate and 2,5 dinitrophenolate followed by the concentration prediction of these three chemical species during a diffusion experiment through a hydrophobic liquid membrane. MATLAB software is used for numerical calculations. Most of the commands for the analysis are provided in order to allow a non-specialist to follow step by step the analysis.

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Quantum chemistry and multivariate analysis were used to estimate the partition coefficients between n-octanol and water for a serie of 188 compounds, with the values of the q 2 until 0.86 for crossvalidation test. The quantum-mechanical descriptors are obtained with ab initio calculation, using the solvation effects of the Polarizable Continuum Method. Two different Hartree-Fock bases were used, and two different ways for simulating solvent cavity formation. The results for each of the cases were analised, and each methodology proposed is indicated for particular case.

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In this work, the impact of fish farming activities on the Queixada, Macuco and Pari-Veado Rivers in the Paranapanema watershed was evaluated. Physical, chemical and microbiological parameters were quantified in these aquatic systems followed by application of multivariate statistical analysis (MSA) and water quality index (WQI) tools. Watersheds where fish farming activities are predominant presented WQI > 52 indicating good quality, whereas MSA demonstrated bad quality for these aquatic bodies. The results showed that the degradation in this watershed follows the fish farming activity. The MSA index is more restricted than the "National Foundation Sanitation" (NFS) index routinely used to infer water quality.

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In this work a multivariate spectroscopic methodology is proposed for quantitative determination of sulfamethoxazole and trimethoprim in pharmaceutical associations. The multivariate model was developed by partial least-squares regression, using twenty synthetic mixtures and the spectral region between 190 and 350 nm. In the validation stage, which involved the analysis of five synthetic mixtures, prediction errors lower that 3% were observed. The predictive capacity of the multivariate models is seriously affected by spectral changes induced by pH variations, a fact that acquires a great significance in the analysis of real samples (pharmaceuticals) that contain chemical additives.

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The Brazilian legislation requires analysis of certain parameters to classify a wine and allow its commercialization. Some physico-chemical and some color parameters were determined in this work in samples of different red wines sold in the metropolitan area of Recife. Multivariate analysis comprising principal component analysis and hierarchical cluster analysis was employed to distinguish the analyzed wines. The results for pH, chloride concentration, color parameters and ammonium content were the most important variables for sample classification. It was also possible to classify the wines as soft or dry wines and amongst the soft wines we could determine two out of four winegrowing producers.

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The objective of this study was to develop and validate an analytical method for quantification of glucosamine and chondroitin in pharmaceutical formulations. Multivariate calibration combined with infrared spectrophotometry allowed this analysis. 25 mixtures of glucosamine-6-sulphate and chondroitin-6-sulphate were used for calibration. Average errors found with this model during external validation were 1.37% for glucosamine sulphate and 1.30% for chondroitin sulphate. This method presented satisfactory results for assessed variables, what indicating that it is suitable for simultaneous quantification of glucosamine and chondroitin.

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The goal of this work is the development and validation of an analytical method for fast quantification of sibutramine in pharmaceutical formulations, using diffuse reflectance infrared spectroscopy and partial least square regression. The multivariate model was elaborated from 22 mixtures containing sibutramine and excipients (lactose, microcrystalline cellulose, colloidal silicon dioxide and magnesium stearate) and using fragmented (750-1150/ 1350-1500/ 1850-1950/ 2600-2900 cm-1) and smoothing spectral data. Using 10 latent variables, excellent predictive capacity were observed in the calibration (n=20, RMSEC=0.004, R= 0.999) and external validation (n=5, RMSEC= 9.36, R=0.999) phases. In the analysis of synthetic mixtures the precision (SD=3,47%) was compatible with the rules of the Agencia Nacional de Vigilância Sanitária (ANVISA-Brazil). In the analysis of commercial drugs good agreement was observed between spectroscopic and chromatographic methods.

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In this study honey samples produced in the southwest of Bahia were characterized based on physicochemical and mineral (Ca, Mg, Na, K, Mn, Fe and Zn) composition. The metals were determined by atomic absorption spectrophotometry. The application of multivariate analysis showed that the honey colors are consequence of the mineral and physicochemical compositions. The darkest honey samples are characterized by higher values of pH and for presenting a strong relationship with Ca and Fe content.

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A multivariate spectrophotometric method was developed for analysis of kojic acid/hydroquinone associations in skin whitening cosmetics. The method is based on the reaction between kojic acid and Fe3+ and on the reduction of Fe3+ by hydroquinone and further complexation of Fe2+ with 1,10-phenanthroline. The multivariate model was developed by Partial Least Squares Regression (PLSR), using 25 synthetic mixtures and mean-centered spectral data (350-380 nm). The use of 3 (kojic acid) and 2 (hydroquinone) latent variables permits the observation of mean errors of about 5% in the external validation phase.