124 resultados para principal component analysis (PCA)
Resumo:
The carcinogenic potential of carbendazim and its metabolites was analyzed using statistical treatment of electronic parameters obtained from DFT/ 6-311++G(d,p) and AM1 calculations. The carcinogen-DNA interaction is described in the framework of the theory of unsynchronized resonance of covalent bond as a process of electron transfer involving the HOMO and LUMO frontier orbitals. Through a Principal Component Analysis (PCA) of the electron affinity, carcinogen-DNA interaction energy, electrostatic attraction and cell membrane permeability (dipole moment m and partition coefficient LogP) evidence was obtained showing carbendazim displays carcinogenic activity. For the metabolites of carbendazim, no evidence was found in the literature of their carcinogenic activities. However, the electronic parameters for these metabolites exhibited similarity to known carcinogens, thereby showing the importance of the results obtained in this study for a policy based on the precautionary principle.
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The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.
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The objective of this work was to develop a free access exploratory data analysis software application for academic use that is easy to install and can be handled without user-level programming due to extensive use of chemometrics and its association with applications that require purchased licenses or routines. The developed software, called Chemostat, employs Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), intervals Principal Component Analysis (iPCA), as well as correction methods, data transformation and outlier detection. The data can be imported from the clipboard, text files, ASCII or FT-IR Perkin-Elmer “.sp” files. It generates a variety of charts and tables that allow the analysis of results that can be exported in several formats. The main features of the software were tested using midinfrared and near-infrared spectra in vegetable oils and digital images obtained from different types of commercial diesel. In order to validate the software results, the same sets of data were analyzed using Matlab© and the results in both applications matched in various combinations. In addition to the desktop version, the reuse of algorithms allowed an online version to be provided that offers a unique experience on the web. Both applications are available in English.
Resumo:
AbstractThe purpose of this study was to evaluate the best operating conditions of ICP OES for the determination of Na, Ca, Mg, Sr and Fe in aqueous extract of crude oil obtained after hot extraction with organic solvents (ASTM D 6470-99 modified). Thus, the full factorial design and central composite design were used to optimize the best conditions for the flow of nebulization gas, the flow of auxiliary gas, and radio frequency power. After optimization of variables, a study to obtain correct classification of the 18 samples of aqueous extract of crude oils (E1 to E18) from three production and refining fields was carried out. Exploratory analysis of these extracts was performed by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), using the original variables as the concentration of the metals Na, Ca, Mg, Sr and Fe determined by ICP OES.
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The calyxes of Hibiscus sabdariffa are used in traditional medicine around the world. However, quality assurance protocols and chemical variability have not been previously analyzed. In the present study, chemical characterization of a set of samples of H. sabdariffa calyxes commercialized in Colombia was accomplished with the aim to explore the chemical variability among them. Chemometrics-based analyses on the data obtained from the HPLC-UV-DAD-derived profiles were then performed. Thus, the pre-processed single-wavelength data were subjected to principal component analysis (PCA). The PCA-derived results evidenced different groups which were well-correlated to the corresponding total phenolic and total anthocyanin contents. Multi-wavelength chromatographic (HPLC-UV-DAD surfaces) data were additionally examined via parallel factor analysis (PARAFAC) as data reduction method and the obtained loadings were subsequently submitted to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). Results were thus consistent with those from single-wavelength data. PCA loadings were employed to determine those chemical components responsible for the data variance and OPLS-DA model, constructed from PARAFAC loadings, and indicated differentiation according total anthocyanin contents among samples. The present chemometric analysis therefore demonstrated to be an excellent tool for differentiation of H. sabdariffacalyxes according to their chemical composition.
Resumo:
Principal component analysis (PCA) is a chemometric method that allows for the extraction of chemical information that would otherwise be impossible to determine. Teaching chemometrics to undergraduates can contribute to the overall professional development and training of new teachers, whose profiles have been gaining attention due to the current demand for data interpretation. In this study, a didactic experiment involving PCA is proposed. Spectrophotometry was used in the ultraviolet-visible (UV-Vis) region to assess the behavior of anthocyanins extracted from red cabbage at different pH values. The results suggest the possible separation of anthocyanin structures into three distinct groups, according to their chemical characteristics displayed in acid, neutral, and basic media. The objective is to develop educational materials targeted to undergraduate courses, which encompass a larger number of concepts and introduce instrumental techniques currently being employed in both academic research and the industrial sector. Specifically, the proposed experiment introduces concepts related to spectrophotometry in the UV-Vis range and the PCA chemometric method. The materials used are easily accessible, and UV-Vis spectroscopy equipment is less expensive in comparison with other spectroscopy methods.
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The characterization of different ecological groups in a forest formation/succession is unclear. To better define the different successional classes, we have to consider ecophysiological aspects, such as the capacity to use or dissipate the light energy available. The main objective of this work was to assess the chlorophyll fluorescence emission of tropical tree species growing in a gap of a semi-deciduous forest. Three species of different ecological groups were selected: Croton floribundus Spreng. (pioneer, P), Astronium graveolens Jacq. (early secondary, Si), and Esenbeckia febrifuga A. Juss. (late secondary, St). The potential (Fv/Fm) and effective (deltaF/Fm') quantum efficiency of photosystem II, apparent electron transport rate (ETR), non-photochemical (qN) and photochemical (qP) quenching of fluorescence were evaluated, using a modulated fluorometer, between 7:30 and 11:00 h. Values of Fv/Fm remained constant in St, decreasing in P and Si after 9:30 h, indicating the occurrence of photoinhibition. Concerning the measurements taken under light conditions (deltaF/Fm', ETR, qP and qN), P and Si showed better photochemical performance, i.e., values of deltaF/Fm', ETR and qP were higher than St when light intensity was increased. Values of qN indicated that P and Si had an increasing tendency of dissipating the excess of energy absorbed by the leaf, whereas the opposite was found for St. The principal component analysis (PCA), considering all evaluated parameters, showed a clear distinction between St, P and Si, with P and Si being closer. The PCA results suggest that chlorophyll fluorescence may be a potential tool to differentiate tree species from distinct successional groups.
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The study of spatial variability of soil and plants attributes, or precision agriculture, a technique that aims the rational use of natural resources, is expanding commercially in Brazil. Nevertheless, there is a lack of mathematical analysis that supports the correlation of these independent variables and their interactions with the productivity, identifying scientific standards technologically applicable. The aim of this study was to identify patterns of soil variability according to the eleven physical and seven chemical indicators in an agricultural area. It was used two multivariate techniques: the hierarchical cluster analysis (HCA) and the principal component analysis (PCA). According to the HCA, the area was divided into five management zones: zone 1 with 2.87ha, zone 2 with 0.8ha, zone 3 with 1.84ha, zone 4 with 1.33ha and zone 5 with 2.76ha. By the PCA, it was identified the most important variables within each zone: V% for the zone 1, CTC in the zone 2, levels of H+Al in the zone 4 and sand content and altitude in the zone 5. The zone 3 was classified as an intermediate zone with characteristics of all others. According to the results it is concluded that it is possible to separate into groups (management zones) samples with the same patterns of variability by the multivariate statistical techniques.
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This work evaluated the physicochemical composition of 171 red Brazilian wines from the 2006 vintage, which were represented by 21 varietals. These wines were produced by 58 Brazilian wineries in different regions of the country, with latitudes varying from 9º to 31º South. Physicochemical wine analysis was performed in the same year and discrimination in the viticultural regions, varietal wines, and wineries was performed by means of the principal component analysis (PCA). The main results show that wines from São Joaquim had higher values of A420, A520, A620, color intensity, total phenolic compounds, anthocyanins, and dry extracts, while those from Toledo had lower values of these variables; those from Vale do São Francisco had higher values of potassium, pH, density, and volatile acidity; from Serra do Nordeste A, they had higher titratable acidity; and from Planalto Superior B, higher hue. Regarding the varietal wines, PCA mainly discriminated the wines produced from the varieties Ancellotta, Teroldego, Egiodola, Refosco, Marselan, Cabernet Sauvignon, Pinotage, Pinot Noir, Malbec, Arinarnoa, Barbera, and Alfrocheiro. In relation to wineries, twenty two of them were discriminated by their higher values of some variables, i.e., three were characterized by color intensity; three by hue; eight by alcohol content; six by potassium, dry extract, density, and pH; and two by titratablel acidity.
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The aim of this study was to determine the influence of process parameters and Passion Fruit Fiber (PFF) addition on the Glycemic Index (GI) of an extruded breakfast cereal. A 2³ Central Composite Rotational Design (CCRD) was used, with the following independent variables: raw material moisture content (18-28%), 2nd and 3rd barrel zone temperatures (120-160 ºC), and PFF (0-30%). Raw materials (organic corn flour and organic PFF) were characterized as to their proximate composition, particle size, and in vitro GI. The extrudates were characterized as to their in vitro GI. The Response Surface Methodology (RSM) and Principal Component Analysis (PCA) were used to analyze the results. Corn flour and PFF presented 8.55 and 7.63% protein, 2.61 and 0.60% fat, 0.52 and 6.17% ash, 78.77 and 78.86% carbohydrates (3 and 64% total dietary fiber), respectively. The corn flour particle size distribution was homogeneous, while PFF presented a heterogeneous particle size distribution. Corn flour and PFF presented values of GI of 48 and 45, respectively. When using RSM, no effect of the variables was observed in the GI of the extrudates (average value of 48.41), but PCA showed that the GI tended to be lower when processing at lower temperatures (<128 ºC) and at higher temperatures (>158 ºC). When compared to white bread, the extrudates showed a reduction of the GI of up to 50%, and could be considered an interesting alternative in weight and glycemia control diets.
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The descriptive terminology and sensory prolife of four samples of Italian salami were determined using a methodology based on the Quantitative Descriptive Analysis (QDA). A sensory panel consensually defined sensory descriptors, their respective reference materials, and the descriptive evaluation ballot. Twelve individuals were selected as judges and properly trained. They used the following criteria: discriminating power, reproducibility, and individual consensus. Twelve descriptors were determined showing similarities and differences among the Italian salami samples. Each descriptor was evaluated using a 10 cm non-structured scale. The data were analyzed by ANOVA, Tukey test, and the Principal Component Analysis (PCA). The salami with coriander essential oil (T3) had lower rancid taste and rancid odor, whereas the control (T1) showed high values of these sensory attributes. Regarding brightness, T4 showed the best result. For the other attributes, T1, T2, T3, and T4 were similar.
Resumo:
The sensory quality of 'Douradão' peaches cold stored in three different conditions of controlled atmosphere (CA1, CA2, CA3 and Control) was studied. After 14, 21 and 28 days of cold storage, samples were withdrawn from CA and kept for 4 days in ambient air for ripening. The sensory profile of the peaches and the descriptive terminology were developed by methodology based on the Quantitative Descriptive Analysis (QDA). The panelists consensually defined the sensory descriptors, their respective reference materials and the descriptive evaluation ballot. Fourteen panelists were selected based on their discrimination capacity and reproducibility. Seven descriptors were generated showing similarities and differences between samples. The data were analyzed by ANOVA, Tukey test and Principal Component Analysis (PCA). Results showed significant differences in the sensory profiles of the peaches. The PCA showed that CA2 and CA3 treatments were more characterized by the fresh peach flavor, fresh peach appearance, juiciness and flesh firmness, and were effective in keeping the good quality of the 'Douradão' peaches during the 28 days of cold storage. The Control and CA1 treatments were characterized by the mealiness and were ineffective for quality maintenance of the fruits during cold storage.
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In this study, water uptake by poultry carcasses during cooling by water immersion was modeled using artificial neural networks. Data from twenty-five independent variables and the final mass of the carcass were collected in an industrial plant to train and validate the model. Different network structures with one hidden layer were tested, and the Downhill Simplex method was used to optimize the synaptic weights. In order to accelerate the optimization calculus, Principal Component Analysis (PCA) was used to preprocess the input data. The obtained results were: i) PCA reduced the number of input variables from twenty-five to ten; ii) the neural network structure 4-6-1 was the one with the best result; iii) PCA gave the following order of importance: parameters of mass transfer, heat transfer, and initial characteristics of the carcass. The main contributions of this work were to provide an accurate model for predicting the final content of water in the carcasses and a better understanding of the variables involved.
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The characterization of wine samples by direct insertion electrospray ionization mass spectrometry (ESI-MS), without pre-treatment or chromatographic separation, in a process denominated fingerprinting, has been applied to several samples of wine produced with grapes of the Pinot noir, Merlot and Cabernet Sauvignon varieties from the state o Rio Grande do Sul, in Brazil. The ESI-MS fingerprints of the samples detected changes which occurred during the aging process in the three grape varieties. Principal Component Analysis (PCA) of the negative ion mode fingerprints was used to group the samples, pinpoint the main changes in their composition, and indicate marker ions for each group of samples.
Resumo:
The production and commercialization of Brazilian grape juice is increasing annually, mainly due to its typicality, quality, and nutritional value. The present research was carried out in view of the great significance of Brazilian grape juice for the grape and wine industry. The purpose of this study, therefore, was to assess its composition as well as the discrimination between grape juice and other beverages. Twenty four samples of whole, sweetened, and reprocessed grape juices, grape nectar, and grape beverage were evaluated. Classical variables were analyzed by means of physicochemical methods; tartaric and malic acids, by HPLC; methanol, by gas chromatography; minerals, by atomic absorption spectrophotometry. These products were discriminated by the Principal Component Analysis (PCA). Results show that whole and sweetened grape juices were discriminated from other grape products because they featured higher values of total soluble solids, tartaric and malic acids, most minerals, phenolic compounds, and K/Na ratio, whereas grape nectar and grape beverage presented higher values of ºBrix/titratable acidity ratio. Reprocessed juice was discriminated due to its higher concentrations of Li and Na and lower hue.