913 resultados para morphological component analysis (MCA)


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Flavanones (hesperidin, naringenin, naringin, and poncirin) in industrial, hand-squeezed orange juices and from fresh-in-squeeze machines orange juices were determined by HPLC/DAD analysis using a previously described liquid-liquid extraction method. Method validation including the accuracy was performed by using recovery tests. Samples (36) collected from different Brazilian locations and brands were analyzed. Concentrations were determined using an external standard curve. The limits of detection (LOD) and the limits of quantification (LOQ) calculated were 0.0037, 1.87, 0.0147, and 0.0066 mg 100 g(-1) and 0.0089, 7.84, 0.0302, and 0.0200 mg 100 g(-1) for naringin, hesperidin, poncirin, and naringenin, respectively. The results demonstrated that hesperidin was present at the highest concentration levels, especially in the industrial orange juices. Its average content and concentration range were 69.85 and 18.80-139.00 mg 100 g(-1). The other flavanones showed the lowest concentration levels. The average contents and concentration ranges found were 0.019, 0.01-0.30, and 0.12 and 0.1-0.17, 0.13, and 0.01-0.36 mg 100 g(-1), respectively. The results were also evaluated using the principal component analysis (PCA) multivariate analysis technique which showed that poncirin, naringenin, and naringin were the principal elements that contributed to the variability in the sample concentrations.

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Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

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In this work, we discuss the use of multi-way principal component analysis combined with comprehensive two-dimensional gas chromatography to study the volatile metabolites of the saprophytic fungus Memnoniella sp. isolated in vivo by headspace solid-phase microextraction. This fungus has been identified as having the ability to induce plant resistance against pathogens, possibly through its volatile metabolites. Adequate culture media was inoculated, and its headspace was then sampled with a solid-phase microextraction fiber and chromatographed every 24 h over seven days. The raw chromatogram processing using multi-way principal component analysis allowed the determination of the inoculation period, during which the concentration of volatile metabolites was maximized, as well as the discrimination of the appropriate peaks from the complex culture media background. Several volatile metabolites not previously described in the literature on biocontrol fungi were observed, as well as sesquiterpenes and aliphatic alcohols. These results stress that, due to the complexity of multidimensional chromatographic data, multivariate tools might be mandatory even for apparently trivial tasks, such as the determination of the temporal profile of metabolite production and extinction. However, when compared with conventional gas chromatography, the complex data processing yields a considerable improvement in the information obtained from the samples. This article is protected by copyright. All rights reserved.

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In recent years, agronomical researchers began to cultivate several olive varieties in different regions of Brazil to produce virgin olive oil (VOO). Because there has been no reported data regarding the phenolic profile of the first Brazilian VOO, the aim of this work was to determine phenolic contents of these samples using rapid-resolution liquid chromatography coupled to electrospray ionisation time-of-flight mass spectrometry. 25 VOO samples from Arbequina, Koroneiki, Arbosana, Grappolo, Manzanilla, Coratina, Frantoio and MGS Mariense varieties from three different Brazilian states and two crops were analysed. It was possible to quantify 19 phenolic compounds belonging to different classes. The results indicated that Brazilian VOOs have high total phenolic content because the values were comparable with those from high-quality VOOs produced in other countries. VOOs from Coratina, Arbosana and Grappolo presented the highest total phenolic content. These data will be useful in the development and improvement of Brazilian VOO.

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Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

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Inductively Coupled Plasma Optical Emission Spectrometry was used to determine Ca, Mg, Mn, Fe, Zn and Cu in samples of processed and natural coconut water. The sample preparation consisted in a filtration step followed by a dilution. The analysis was made employing optimized instrumental parameters and the results were evaluated using methods of Pattern Recognition. The data showed common concentration values for the analytes present in processed and natural samples. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that the samples of different kinds were statistically different when the concentrations of all the analytes were considered simultaneously.

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In this work, the volatile chromatographic profiles of roasted Arabica coffees, previously analyzed for their sensorial attributes, were explored by principal component analysis. The volatile extraction technique used was the solid phase microextraction. The correlation optimized warping algorithm was used to align the gas chromatographic profiles. Fifty four compounds were found to be related to the sensorial attributes investigated. The volatiles pyrrole, 1-methyl-pyrrole, cyclopentanone, dihydro-2-methyl-3-furanone, furfural, 2-ethyl-5-methyl-pyrazine, 2-etenyl-n-methyl-pyrazine, 5-methyl-2-propionyl-furan compounds were important for the differentiation of coffee beverage according to the flavour, cleanliness and overall quality. Two figures of merit, sensitivity and specificity (or selectivity), were used to interpret the sensory attributes studied.

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This manuscript aims to show the basic concepts and practical application of Principal Component Analysis (PCA) as a tutorial, using Matlab or Octave computing environment for beginners, undergraduate and graduate students. As a practical example it is shown the exploratory analysis of edible vegetable oils by mid infrared spectroscopy.

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Easter egg is a popular chocolate-candy in egg form commercialized in Brazil during Easter time. In this research, Quantitative Descriptive Analysis was applied to select sensory attributes which best define the modifications in appearance, aroma, flavor and texture when cocoa butter equivalent (CBE) is added to Easter eggs. Samples with and without CBE were evaluated by a selected panel and fourteen attributes best describing similarities and differences between them, were defined. Terms definition, reference materials and a consensus ballot were developed. After a training period, panelists evaluated the samples in a Complete Block Design using a 9 cm unstructured scale. Principal Component Analysis, ANOVA and Tukey test (p<0.05) were applied to the data in order to select attributes which best discriminated and characterized the samples. Samples showed significant differences (p<0.05) in all attributes. Easter egg without CBE showed higher intensities (p<0.05) in relation to the following descriptors: brown color, characteristic aroma, cocoa mass aroma, cocoa butter aroma, characteristic flavor, cocoa mass flavor, hardness and brittleness.

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Descriptive terminology and sensory profile of three varieties of brazilian varietal white wines (cultivars Riesling, Gewürztraminer and Chardonnay) were developed by a methodology based on the Quantitative Descriptive Analysis (QDA). The sensory panel consensually defined the sensory descriptors, their respective reference materials and the descriptive evaluation ballot. Ten individuals were selected as judges based on their discrimination, reproducibility and individual consensus with the sensory panel. Twelve descriptors were generated showing similarities and differences among the wine samples. Each descriptor was evaluated using a nine-centimeters non-structured scale with the intensity terms anchored at its ends. The collected data were analysed by ANOVA, Tukey test and Principal Component Analysis (PCA). The results showed a great difference within the sensory profile of Riesling and Gewürztraminer wines, whereas Chardonnay wines showed a lesser variation. PCA separated samples into two groups: a first group formed by wines higher in sweetness and fruitty flavor and aroma; and a second group of wines higher in sourness, adstringency, bitterness, alcoholic and fermented flavors.

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Ferruginous "campos rupestres" are a particular type of vegetation growing on iron-rich primary soils. We investigated the influence of soil properties on plant species abundance at two sites of ferruginous "campos rupestres" and one site of quartzitic "campo rupestre", all of them in "Quadrilátero Ferrífero", in Minas Gerais State, southeastern Brazil. In each site, 30 quadrats were sampled to assess plant species composition and abundance, and soil samples were taken to perform chemical and physical analyses. The analyzed soils are strongly acidic and presented low fertility and high levels of metallic cations; a principal component analysis of soil data showed a clear segregation among sites due mainly to fertility and heavy metals content, especially Cu, Zn, and Pb. The canonical correspondence analysis indicated a strong correlation between plant species abundance and soil properties, also segregating the sites.

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Soil organic matter (SOM) plays an important role in physical, chemical and biological properties of soil. Therefore, the amount of SOM is important for soil management for sustainable agriculture. The objective of this work was to evaluate the amount of SOM in oxisols by different methods and compare them, using principal component analysis, regarding their limitations. The methods used in this work were Walkley-Black, elemental analysis, total organic carbon (TOC) and thermogravimetry. According to our results, TOC and elemental analysis were the most satisfactory methods for carbon quantification, due to their better accuracy and reproducibility.

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The spatial and temporal retention of metals has been studied in water and sediments of the Gavião River, Anagé and Tremedal Reservoirs, located in the semi-arid region, Bahia - Brazil, in order to identify trends in the fluxes of metals from the sediments to the water column. The determination of metals was made by ICP OES and ET AAS. The application of statistical methods showed that this aquatic system presents suitable conditions to move Cd2+ and Pb2+ from the water column to the sediment.

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Características físico-químicas (cor, pH, acidez total titulável, sólidos solúveis totais, conteúdo de lipídios e umidade) e níveis de compostos bioativos (ácido ascórbico, fenólicos totais) foram determinados em quinze amostras de polpas de frutos procedentes da região Amazônica (abiu, acerola, açaí, araçá-boi, bacaba, bacuri, buriti, cajá, cajarana, caju, cupuaçu, graviola, murici, noni e tamarindo). A atividade de radicais livres foi avaliada pelo método de ABTS. Algumas polpas apresentaram alta potencialidade antioxidante, associada com a atividade antirradicais livres obtida e os conteúdos dos componentes bioativos como compostos fenólicos e ácido ascórbico, destacando-se acerola e acaí. O conteúdo total de compostos fenólicos foi correlacionado à capacidade antioxidante das polpas.

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Medium density fiberboard (MDF) is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC) bagasse to Eucalyptus wood in MDF panels using near infrared (NIR) spectroscopy. Principal component analysis (PCA) and partial least square (PLS) regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96) between the NIR-predicted and Lab-determined values and a low standard error of prediction (similar to 1.5%) in the cross-validations. A key role of resins (adhesives), cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.