124 resultados para principal component analysis (PCA)
Resumo:
The combination of high performance exclusion chromatography (HPEC) and gas chromatography (GC) was applied to the analysis of six coffee samples that were previously characterized by sensory tests as of good or poor quality. The data obtained by the two techniques were statistically evaluated by "Principal Components Analysis" (PCA) using selected peak areas. The results showed the potential of the described techniques for coffee analysis. The HPEC technique monitored with the U.V. detector at 272 nm and followed by PCA may be correlated with sensorial data, particularly if a wider group of samples is used.
Resumo:
The modern technological ability to handle large amounts of information confronts the chemist with the necessity to re-evaluate the statistical tools he routinely uses. Multivariate statistics furnishes theoretical bases for analyzing systems involving large numbers of variables. The mathematical calculations required for these systems are no longer an obstacle due to the existence of statistical packages that furnish multivariate analysis options. Here basic concepts of two multivariate statistical techniques, principal component and hierarchical cluster analysis that have received broad acceptance for treating chemical data are discussed.
Resumo:
The input of heavy metals concentrations determinated by ICP-AES, in samples of the Cambé river basin, was evaluated by using the Principal Component Analysis. The results distinguishes clearly one site, which is strongly influenced by almost all elements studied. Special attention was given to Pb, because of the presence of one battery industry in this area. Some downstream samples were associated with the same characteristics of this site, showing residual action of contaminants along the basin. Other sites presented influence of soil elements, plus Cr near a tannery industry. This study allowed to distinguish different sites in the upper basin of the Cambé (Londrina-PR-BR), in accordance to elements input.
Resumo:
Soils play an important role in the biogeochemical cycle of mercury as a sink for and source of this metallic species to atmospheric and hydrological compartments. In the study reported here, various types of soil were evaluated to ascertain the influence of parameters such as pH, organic matter content, Fe, Al, sand, silt, clay, C/H, C/N, C/O atomic ratios, and cation exchange capacity on the distribution of Hg in Amazonia's mid-Negro River basin. The data obtained were interpreted by multivariate exploratory analyses (hierarchical cluster analysis and principal component analysis), which indicated that organic matter plays an important role in mercury uptake in the various soils studied. The soils in floodable areas were found to contain 1.5 to 2.8-fold higher Hg concentrations than those in non-floodable areas. Since these soils are flooded almost year-round, they are less available to participate in redox processes at the soil/atmosphere interface. Hence, floodable areas, which comprise humic-rich soils, accumulate more mercury than non-floodable soils, thus playing an important role in the biogeochemical cycle of Hg in Amazonia's mid-Negro River basin.
Resumo:
Water quality was monitored at the upper course of the Rio das Velhas, a major tributary of the São Francisco basin located in the state of Minas Gerais, over an extension of 108 km from its source up to the limits with the Sabara district. Monitoring was done at 37 different sites over a period of 2 years (2003-2004) for 39 parameters. Multivariate statistical techniques were applied to interpret the large water-quality data set and to establish an optimal long-term monitoring network. Cluster analysis separated the sampling sites into groups of similarity, and also indicated the stations investigated for correlation and recommended to be removed from the monitoring network. Principal component analysis identified four components, which are responsible for the data structure explaining 80% of the total variance of the data. The principal parameters are characterized as due to mining activities and domestic sewage. Significant data reduction was achieved.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
This study examined the spatial and temporal variations of 13 physico-chemical parameters in water and sediment samples collected along the rural and urban section of Verruga Stream. The metal concentrations were determined by FAAS. The conductivity and the concentration of Na+, Cl-, and Ca2+ showed the largest variations in the urban area demonstrating that these parameters are appropriate indicators of urban contamination. The application of cluster and principal component analysis showed that the Cd2+ and Mn2+ are associated with the use of fertilizers in the rural area.
Resumo:
This work shows results on the characterization, by liquid chromatography coupled to high resolution tandem mass spectrometry (LC-IT-TOF-MS) with electrospray ionization, of organic compounds present in raw and treated effluents from a combined sewage treatment systems (upflow anaerobic sludge blanket-trickling filter). The sewage samples were prepared by C18 solid phase extraction and the spectra obtained from the various extracts were submitted to principal component analysis to evaluate their pattern and identify the major deprotonated species. Some target compounds were submitted to semiquantitative analysis, using phenolphtalein as internal standard. The results showed the anaerobic step had little impact on the removal of anionic surfactants (LAS), fatty acids, and some contaminantes such as bisphenol A and bezafibrate, whereas the aerobic post-treatment was very efficient in removing these organics.
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This paper presents the analytical application of a novel electronic tongue based on voltammetric sensors array. This device was used in the classification of wines aged in barrels of different origins and toasting levels. Furthermore, a study of correlation between the response of the electronic tongue and the sensory and chemical characterization of samples was carried out. The results were evaluated by applying both principal component analysis and cluster analysis. The samples were clearly classified. Their distribution showed a high correspondence degree with the characteristics of the analyzed wines, it also showed similarity with the classification obtained from organoleptic analysis.
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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.
Resumo:
A dataset of chemical properties of the elements is used herein to introduce principal components analysis (PCA). The focus in this article is to verify the classification of the elements within the periodic table. The reclassification of the semimetals as metals or nonmetals emerges naturally from PCA and agrees with the current SBQ/IUPAC periodic table. Dataset construction, basic preprocessing, loading and score plots, and interpretation have been emphasized. This activity can be carried out even when students with distinct levels of formation are together in the same learning environment.
Resumo:
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.
Resumo:
The concentration of 14 organic acids of 50 sugarcane spirits samples was determined by gas chromatography using flame ionization detection. The organic acids analytical quantitative profile in stills and column distilled spirits from wines obtained from the same must were compared. The comparison was also carried in "head", "heart" and "tail fractions of stills distilled spirits. The experimental data were analyzed by Principal Components Analysis (PCA) and pointed out that the distillation process (stills and column) strongly influences the lead spirits' organic acid composition and that producers' operational "cuts off" to produce "tail", "heart" and "head", fractions should be optimized.