Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

GC Fingerprints Coupled to Pattern-Recognition Multivariate SIMCA Chemometric Analysis for Brazilian Gasoline Quality Studies

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis

The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance ((1)H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the (1)H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices. (C) 2010 Elsevier B.V. All rights reserved.

Comparative studies of the sample decomposition of green and roasted coffee for determination of nutrients and data exploratory analysis

The contents of some nutrients in 35 Brazilian green and roasted coffee samples were determined by flame atomic absorption spectrometry (Ca, Mg, Fe, Cu, Mn, and Zn), flame atomic emission photometry (Na and K) and Kjeldahl (N) after preparing the samples by wet digestion procedures using i) a digester heating block and ii) a conventional microwave oven system with pressure and temperature control. The accuracy of the procedures was checked using three standard reference materials (National Institute of Standards and Technology, SRM 1573a Tomato Leaves, SRM 1547 Peach Leaves, SRM 1570a Trace Elements in Spinach). Analysis of data after application of t-test showed that results obtained by microwave-assisted digestion were more accurate than those obtained by block digester at 95% confidence level. Additionally to better accuracy, other favorable characteristics found were lower analytical blanks, lower reagent consumption, and shorter digestion time. Exploratory analysis of results using Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) showed that Na, K, Ca, Cu, Mg, and Fe were the principal elements to discriminate between green and roasted coffee samples. ©2007 Sociedade Brasileira de Química.

Magnetic susceptibility to identify landscape segments on a detailed scale in the region of Jaboticabal, São Paulo, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chicken skeletal muscle-associated macroarray for gene discovery

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variabilidade espacial e temporal de parâmetros físico-químicos nos rios Turvo, Preto e Grande no estado de São Paulo, Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Breeding Habitat and Landscape Correlates of Frog Diversity and Abundance in a Tropical Agricultural Landscape

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Distribuição de mercúrio em diferentes solos da Bacia do médio Rio Negro-AM: influência da matéria orgânica no ciclo biogeoquímico do mercúrio

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A structure-activity relationship study of quinone compounds with trypanocidal activity

A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the density functional theory (DFT) method in order to calculate atomic and molecular properties to be correlated with the biological activity. The chemometric methods principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), Kth nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and to predict the anti-trypanocidal activity of new quinone compounds from a prediction set. Four descriptors were responsible for the separation between the active and inactive compounds: T-5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi. (c) 2005 Elsevier SAS. All rights reserved.

Screening Brazilian C gasoline quality: Application of the SIMCA chemometric method to gas chromatographic data

A total of 2400 samples of commercial Brazilian C gasoline were collected over a 6-month period from different gas stations in the São Paulo state, Brazil, and analysed with respect to 12 physicochemical parameters according to regulation 309 of the Brazilian Government Petroleum, Natural Gas and Biofuels Agency (ANP). The percentages (v/v) of hydrocarbons (olefins, aromatics and saturated) were also determined. Hierarchical cluster analysis (HCA) was employed to select 150 representative samples that exhibited least similarity on the basis of their physicochemical parameters and hydrocarbon compositions. The chromatographic profiles of the selected samples were measured by gas chromatography with flame ionisation detection and analysed using soft independent modelling of class analogy (SIMCA) method in order to create a classification scheme to identify conform gasolines according to ANP 309 regulation. Following the optimisation of the SIMCA algorithm, it was possible to classify correctly 96% of the commercial gasoline samples present in the training set of 100. In order to check the quality of the model, an external group of 50 gasoline samples (the prediction set) were analysed and the developed SIMCA model classified 94% of these correctly. The developed chemometric method is recommended for screening commercial gasoline quality and detection of potential adulteration. (c) 2007 Elsevier B.V. All rights reserved.

Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

High resolution ultra high pressure liquid chromatography-time-of-flight mass spectrometry dereplication strategy for the metabolite profiling of Brazilian Lippia species

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The influence of seasonalness on the structural characteristics of aquatic humic substances extracted from Negro River (Amazon state) waters: Interactions with Hg(II)

In this work, humic substances were extracted from water samples collected monthly from the Negro River basin in the Amazon state (Brazil) to study their properties in the Amazonian environment and interactions with the mercury ion considering the influence of seasonalness in this formation. The C/H, C/N and C/O atomic ratio parameters, functional groups, concentration of semiquinone-type free radicals, pH, pluviometric and fluviometric indices, and mercury concentrations were interpreted using hierarchical cluster analysis (HCA) and principal component analysis (PCA). The statistical analyses showed that when the pluviometric index was greater and the fluviometric index was smaller, the degree of humification of aquatic substances was greater. The following decreasing order of the degree of humification of the AHS collected monthly was established: Nov/02 to Feb/03 > Mar/02 to May/02 > Jun/02 to Oct/02. The greatest concentrations of mercury were detected in more humidified samples. These results suggest that due to inter and/or intra-molecular rearrangements, the degree of humification of aquatic humic substances is related to its affinity for Hg(II) ions. ©2007 Sociedade Brasileira de Química.

Auto-avaliação dos Discentes do Curso de Ciências Biológicas da Unemat, Campus de Nova Xavantina: um modelo para avaliação das disciplinas curriculares, segundo a percepção do corpo discente e docente

This paper presents an evaluation of the curriculum subjects of the Biological Sciences course in the University of the State of Mato Grosso (UNEMAT), Nova Xavantina campus, Brazil. The research was carried out by means of a self-assessment instrument, aimed at searching learners' and educators' points of view. The questionnaires were given in the first, third and seventh semesters, in which students were asked to assess pedagogical aspects regarding professors and their didacticism, as well as the subject matters being taught; in addition, they were invited to evaluate themselves as learners. The data was analyzed using statistical parameters, in order to measure teaching performance, and, subsequently, professors were given the opportunity to express their concepts about the students' assessment. The average value of the overall Cronbach's alpha coefficient was 0.923±0.001, a significant value considering that alpha varies between 0 and 1, which proves the questionnaire to be reliable. The hierarchical cluster analysis (HCA) does not permit teaching performance to be associated with professors' qualification or workload.