Search

The identification of key components relevant to sensory perception of quality from commercial chocolate samples was accomplished after chemometric processing of GC×GC-MS (Comprehensive Two-dimensional Gas Chromatography with Mass Spectrometric Detection) profiles corresponding to HS-SPME (Headspace Solid Phase Microextraction) extracts of the samples. Descriptive sensory evaluation of samples was carried out using Optimized Descriptive Profile (ODP) procedures, where sensory attributes of 24 commercial chocolate samples were used to classify them in two classes (low and high chocolate flavor). 2D Fisher Ratio analysis was applied to four-way chromatographic data tensors (1st dimension retention time 1tR × 2nd dimension retention time 2tR × m/z × sample), to identify the crucial areas on the chromatograms that resulted on ODP class separation on Principal Component Analysis (PCA) scores plot. Comparing the relevant sections of the chromatograms to the analysis of the corresponding mass spectra, it was possible to assess that most of the information regarding the sample main sensory attributes can be related to only 14 compounds (2,5-dimethylpyrazine, 2,6-dimethyl-4-heptanol, 1-octen-3-ol, trimethylpyrazine, β-pinene, o-cimene, 2-ethyl-3,5-dimethylpyrazine, tetramethylpyrazine, benzaldehyde, 1,3,5-trimethylbenzene, 6-methyl-5-hepten-2-one, limonene, benzeneethanol and 1,1-dimethylbutylbenzene) among the complex blend of volatiles found on these extremely complex samples.

In order to confirm that the mitigation of greenhouse gas emissions could indeed be achieved by farmers, determinations of soil organic carbon (SOC) in total and stabilized fractions are essential, proving the effectiveness of the sustainable practices adopted by the farmer. In this sense, this study proposes an analytical methodology based on near infrared spectroscopy (NIRS) and partial least squares regression (PLSR) as an alternative for the measurement of stabilized and total soil organic carbon (SOC) in agricultural production systems. A set of 122 samples of four different land uses were sampled and the stabilized and labile SOC content were determined by the dry combustion method. In order to eliminate the extra step regarding soil fractionation to determine the stabilized SOC content, this study investigated different strategies to build the regression model based on partial least squares regression for the determination of the stabilized SOC from the total soil fraction. Two strategies presented the same accuracy as the reference method used to determine the stabilized SOC content in stabilized fraction, with root mean square error in validation of 1.47 g/dm3. These results indicate that both strategies proposed can determine simultaneously the total and stabilized SOC from the total soil fraction, thus eliminating the extra sample preparation.

International audience; Solid dispersions are an interesting option to improve the solubility of Class II (high permeability, low water solubility) drugs of the Biopharmaceutical Classification System without the use of organic solvents. However, structural changes (polymorphism) may be present in both active pharmaceutical ingredients (API) and excipients, which require evaluation during pharmaceutical

Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq, Brasilia, Brazil) FAPESP Background: The objective of this study was to identify molecular alterations in the human blood serum related to bipolar disorder, using nuclear magnetic resonance (NMR) spectroscopy and chemometrics. Methods: Metabolomic profiling, employing H-1-NMR, H-1-NMR -T-2-edited, and 2D-NMR spectroscopy and chemometrics of human blood serum samples from patients with bipolar disorder (n = 26) compared with healthy volunteers (n = 50) was performed. Results: The investigated groups presented distinct metabolic profiles, in which the main differential metabolites found in the serum sample of bipolar disorder patients compared with those from controls were lipids, lipid metabolism-related molecules (choline, myo-inositol), and some amino acids (N-acetyl-L-phenyl alanine, N-acetyl-L-aspartyl-L-glutamic acid, L-glutamine). In addition, amygdalin, alpha-ketoglutaric acid, and lipoamide, among other compounds, were also present or were significantly altered in the serum of bipolar disorder patients. The data presented herein suggest that some of these metabolites differentially distributed between the groups studied may be directly related to the bipolar disorder pathophysiology. Conclusions: The strategy employed here showed significant potential for exploring pathophysiological features and molecular pathways involved in bipolar disorder. Thus, our findings may contribute to pave the way for future studies aiming at identifying important potential biomarkers for bipolar disorder diagnosis or progression follow-up. Univ Fed Sao Paulo UNIFESP, Dept Psychiat, Rua Borges Lagoa 570, BR-04038020 Sao Paulo, Brazil Univ Fed Sao Paulo UNIFESP, Dept Pharmacol, Rua Tres Maio 100, BR-04044020 Sao Paulo, Brazil ISCMSP, Dept Psychiat, Rua Major Maragliano 287, BR-04017030 Sao Paulo, Brazil Univ Estadual Campinas UNICAMP, Lab Quim Biol, Dept Organ Chem, Inst Chem, Caixa Postal 6154, BR-13083970 Sao Paulo, Brazil Univ Estadual Campinas UNICAMP, Dept Analyt Chem, Inst Chem, Caixa Postal 6154, BR-13083970 Sao Paulo, Brazil Univ Fed Sao Paulo UNIFESP, Dept Psychiat, Rua Borges Lagoa 570, BR-04038020 Sao Paulo, Brazil Univ Fed Sao Paulo UNIFESP, Dept Pharmacol, Rua Tres Maio 100, BR-04044020 Sao Paulo, Brazil CNPq FAPESP: 2014/18938-8 Web of Science

Raman imaging spectroscopy is a relatively new technique that has raised interest in several areas of knowledge due to the possibility of evaluating the spatial distribution of compounds based on their spectra. This paper presents a brief history of the development of this important technique, a theoretical description of the Raman effect and the preprocessing and processing (both univariate and multivariate) tools for Raman data. We also describe the current state of applications for major areas such as agriculture/biomass, environment, biology, medicine, pharmaceutical, geology, foodstuff, artwork, archaeology, material characterization and forensic.

In this study, a series of polymeric ionic liquid (PIL) sorbent coatings is evaluated for the extraction of polar volatile organic compounds (VOCs) from Brazilian wines using headspace solid-phase microextraction (HS-SPME), including samples from ?Isabella? and ?BRS Magna? cultivars?the latter was recently introduced by the Brazilian Agricultural Research Corporation ? National Grape & Wine Research Center. In this study, a series of polymeric ionic liquid (PIL) sorbent coatings is evaluated for the extraction of polar volatile organic compounds (VOCs) from Brazilian wines using headspace solid-phase microextraction (HS-SPME), including samples from ?Isabella? and ?BRS Magna? cultivars?the latter was recently introduced by the Brazilian Agricultural Research Corporation ? National Grape & Wine Research Center. The structurally tuned SPME coatings were compared to the commercial SPME phases, namely poly(acrylate) (PA) and divinylbenzene/carboxen/poly(dimethylsiloxane) (DVB/CAR/PDMS). The separation, detection and identification of the aroma profileswere obtained using comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS). The best performing PIL-based SPME fiber, namely 1-hexadecyl-3-vinylimidazolium bis[(trifluoromethyl)sulfonyl]imide with 1,12-di(3-vinylimidazolium)dodecane dibis[(trifluoromethyl)sulfonyl]imide incorporated cross-linker supported on an elastic nitinol wire, exhibited superior performance to DVB/CAR/PDMS regarding the average number of extracted peaks and extracted more polar analytes providing additional insight into the aroma profile of ?BRS Magna? wines. Four batches of wine were evaluated, namely ?Isabella? and ?BRS Magna? vintages 2015 and 2016, using highly selective PIL-based SPME coatings and enabled the detection of 350+ peaks. Furthermore, this is the first report evaluating the aroma of ?BRS Magna? wines. A hybrid approach that combined pixel-based Fisher ratio and peak table-based data comparison was used for data handling. This proof-of-concept experiment provided reliable and statistically valid distinction of wines that may guide regulation agencies to create high sample throughput protocols to screen wines exported by Brazilian vintners. Made available in DSpace on 2019-05-01T00:44:24Z (GMT). No. of bitstreams: 1 Crucelloetal2018AnalyticalandBioanalyticalChemistry.pdf: 1957393 bytes, checksum: d44c912271d094147ccc347b257e6d8e (MD5) Previous issue date: 2018

The quality control of pellets homogeneity cannot be assessed by conventional techniques and near infrared-chemical imaging combined with multivariate curve resolution with alternating least squares is an attractive alternative. In this study, composition and spatial distribution of pellets components were determined after assessment of experimental parameters. The use of a 25 μm intermediate pixel size, an initial estimation matrix with instrumental signals for pure substances and individual matrices provided a model with explained variance of more than 99% and a value of 0.00263 for percentage of lack of fit. In addition, the similarity between the pure substances spectra and those recovered by the model were 0.9501 for sucrose, 0.9480 for starch, 0.9910 for ketoprofen and 0.5941 for SiO2. Chemical images were generated and show that the pellet is composed of an inert nucleus of starch and cellulose, surrounded by a ketoprofen layer. All this information was obtained quickly, in minutes, being an excellent alternative for pellets analysis.

Phenolic compounds are important environmental contaminants due to their high toxicity and persistence in the environment. The use of enzyme-based electrochemical biosensors is a simple, sensitive and low-cost alternative for the determination of these pollutants in contaminated waters. However, in most cases, it is impossible to detect specific compounds in a mixture of phenols due to signal-overlap, as the instruments operate at very close potentials, given that the system is based on a single enzyme to detect similar structures. In order to overcome this problem, in the present work we have successfully used multivariate calibration with partial least squares (PLS) for the simultaneous determination of hydroquinone and guaiacol by a tyrosinase-based biosensor that was assembled using an enzyme extract from yam. The use of PLS allowed us to work with a large number of voltammograms, leading to a single mathematical model for the simultaneous determination of phenols of similar structure in real samples with concentration values of mmol L-1.

Competitive adaptive reweighted sampling-partial least squares (CARS-PLS) and negative-ion mode electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI(-) FT-ICR MS) data were adopted to assess the total acid number (TAN) of crude oil distillation cuts. Two crude oil samples and 24 derivatives with TAN ranging from 0.20 to 0.39 mg of KOH g-1 were investigated. The multivariate calibration PLS model was built with 18 calibration samples and tested with 8 validation samples. CARS-PLS reduced the number of variables from 1610 to only 4, allowing the identification of molecular formulas that are truly related to the TAN. The root mean square error of prediction (RMSEP) obtained was 0.01 mg of KOH g-1, which is lower than the error when using all variables (0.03 mg of KOH g-1). Finally, it was observed that the N and O2 compound classes are the most important classes for providing a better correlation between ESI(-) FT-ICR mass spectra and TAN values.

Brazilian Ministry of Education Agency for Improvement of Graduate Personnel (CAPES) National Council for Scientific and Technological Development (CNPq) Sao Paulo Research Foundation (FAPESP) Comprehensive two-dimensional gas chromatography (GCxGC) was used in this work in order to reveal and identify minor compounds of several raw materials in biodiesel samples, which are not detected by conventional GC analysis. Multiway principal component analysis (MPCA) of the chromatographic profile allowed to identify compounds as C15: 1n-3, C18: 2n-6, C20: 1n-6, C20: 3n-3, C20: 3n-6, C20: 4n-6 C20: 5n-3, C21: 1n-6, C22: 1n-9, C23: 1n-9, C24: 1n-9 multi-unsaturated which were useful tracers to discriminate between biodiesel samples. In this way, the separation power of GCxGC combined with the MPCA algorithm proved to be a valuable strategy for biodiesel samples classification, allowing identification and providing additional compounds of the commonly known as chemical profile of biodiesel samples. Univ Estadual Campinas, Inst Quim, CP 6154, BR-13083970 Campinas, SP, Brazil Univ Estatal Bolivar, Dept Invest, Campus Univ Laguacoto 2,Km 1,Via San Simon, Canton Guaranda, Provincia Boliv, Ecuador Univ Estadual Campinas, Inst Quim, Dept Quim Analit, Inst Nacl Ciencia & Tecnol INCT Bioanalyt, BR-13083970 Campinas, SP, Brazil Univ Fed Sao Paulo, Inst Ciencias Ambientais Quim & Farmaceut, Dept Ciencias Exatas & Terra, Campus Diadema, BR-09972270 Diadema, SP, Brazil Univ Fed Sao Paulo, Inst Ciencias Ambientais Quim & Farmaceut, Dept Ciencias Exatas & Terra, Campus Diadema, BR-09972270 Diadema, SP, Brazil Web of Science

The development and optimization of a novel UV spectrophotometric methodology was proposed for simultaneous analysis of ethambutol (ETB), isoniazid (ISO), rifampicin (RIF) and pyrazinamide (PYR), using multivariate calibration based on the partial least squares method (PLS). The methodology was successfully applied for analysis of four-drug fixed dose combination (4-FDC) tablets used for tuberculosis treatment. A 34 Box-Behnken design, with triplicate in central point, was used for sample preparation in the calibration step. In the present case, nine latent variables were chosen for the model development that presented the smallest RMSECV and explain 98.76% of data variance in Y block (concentrations of ETB ISO, RIF and PYR) and 99.93% of data variance in X block (spectral data). PLS models for ETB, ISO, RIF and PYR presented RMSEP and R2 values of 0.23 mg L−1 and 0.971; 0.14 mg L−1 and 0.731; 0.11 mg L−1 and 0.990 and 0.57 mg L−1 and 0.972, respectively. A validation step was performed based on the comparison between the UV spectrophotometric proposed methodology and capillary zone electrophoresis (CZE) in 4-FDC real samples and no significant difference was found between two methodologies at 95% of confidence level.

Sendo o solo um dos principais pilares de sustentabilidade de todo sistema de produção, a análise integrada dos atributos edafobiológicos pode constituir-se em ferramenta importante para avaliar a qualidade do mesmo. O objetivo do trabalho foi avaliar a qualidade do solo em função das práticas agrícolas adotadas, mediante a análise integrada de atributos físicos, químicos e biológicos. A pesquisa foi realizada em 2006 e 2007 nas microrregiões de Ibiúna e Socorro, no estado de São Paulo, em pequenas propriedades familiares orgânicas e convencionais. Foram avaliados os atributos físicos, químicos e biológicos, mediante coletas de amostras de solos sob cultivo de hortaliças e em solos de mata ou pastagem. O levantamento de dados sobre as práticas agrícolas foi realizado em cada sistema de produção. Os dados obtidos foram submetidos à análise de componentes principais (ACP). A ACP identificou maior grau de similaridade entre os solos sob cultivo em Socorro e suas respectivas testemunhas que os solos de Ibiúna, nitidamente separados em função do seu uso (mata ou cultivo) e indicando melhor manejo dos mesmos em Socorro. De maneira geral, concluiu-se que as práticas agrícolas utilizadas na maioria das propriedades orgânicas e convencionais favoreceram a degradação do solo, devida principalmente ao revolvimento intensivo e à ausência de cobertura do solo. Estes fatores provocaram redução dos teores de matéria orgânica do solo, da biomassa microbiana, da emergência de plântulas e da estabilidade de agregados nas áreas de cultivo em relação às áreas testemunhas.The soil is one of the most important sustainability columns of the production system. The integrated analysis of the edaphobiological attributes can be an important tool for soil quality evaluation. We evaluated the soil quality regarding the adopted agriculture practices, using the integrated analysis of physical, chemical and biological attributes. The research was carried out in Ibiúna and Socorro, São Paulo state, Brazil, in organic and conventional production, on small and family farms. Physical, chemical and biochemical parameters were evaluated during 2006 and 2007 in soils under vegetable cultivation, native forest or fallow, taken as reference of natural soil. Agricultural practices data were collected in each production system. The obtained data were submitted to principal component analysis (PCA). There was no pronounced grouping trend according to the production system, organic or conventional, but there was a grouping according to the soil use (forest/fallow land or cultivation). The PCA identified greater degree of similarity between Socorro's cultivation soil and its respective controls compared to Ibiuna's soil, clearly separated according to its use (forest or cropping), indicating better soil management in Socorro. In general, the results allow to conclude that agricultural practices in most of both organic and conventional production systems, caused soil degradation, due to, mainly, intensive soil tillage and no soil mulching, as indicated by the reduction of soil organic matter, microbial biomass, plant emergence and aggregate stability in cultivated areas relative to control ones.

This works describes the use of experimental design and surface response methodology for optimization of saponin extraction from Ampelozizyphus amazonicus. For this purpose, a method employing extraction based on maceration assisted by ultrasound technique was utilized. The following factors were studied: extraction length of time and solvent composition. The total saponin was determined by using a gravimetric method and the results expressed by their relative proportion to total crude extract. For the specific condition, 60% hydro-alcoholic solution and 18 minutes extraction length of time has shown the best results. This method can be useful for extraction of substances with biological importance

In this work, a method for differentiation of gasoline according to its geographical origin is presented. Comprehensive two-dimensional gas chromatography-flame ionization detection (GC×GC-FID) combined with multivariate analysis was used to differentiate Brazilian and Venezuelan gasoline samples. Pattern recognition of the GC×GC-FID chromatograms was performed by parallel factor analysis (PARAFAC) and it was successfully applied for the differentiation of these gasoline samples. Eluates with medium to high volatility, both aliphatic and aromatic, were responsible for this differentiation, based on the inspection of the score and loading graphs generated by PARAFAC. Neste trabalho, um método para a diferenciação de gasolinas de acordo com a sua origem geográfica é proposto. Cromatografia gasosa bidimensional abrangente com detecção por ionização em chama (GC×GC-FID) em conjunto com a análise multivariada foi utilizada para diferenciar amostras de gasolina brasileira de amostras oriundas da Venezuela. A análise de fatores paralelos (PARAFAC) foi utilizada no reconhecimento de padrões dos cromatogramas GC×GC-FID e foi aplicada com êxito na diferenciação das amostras de gasolina. Através da análise dos gráficos de escores e pesos gerados pela análise PARAFAC, foi possível determinar que eluatos de média a alta volatilidade, tanto alifáticos quanto aromáticos, foram responsáveis por essa diferenciação.

In this work, near infrared (NIR) imaging spectroscopy was employed in the study of the distribution of the active pharmaceutical ingredient (API) spironolactone and its excipients in tablets. Analyses were performed using 50 µm spatial resolution to analyze 16 mm² of each standard tablet. Interval partial least squares models were used for API and excipients quantification in every pixel in order to obtain concentration maps for each compound. It was obtained errors of quantification between 0.49 and 1.26% when performed the cross-validation using spectral average of each tablet. These calibration models were used to predict individual concentration of each compound in the tablet, in every pixel. The average concentration of all pixels, for each compound yield errors, was between 0.05 and 1.06%. These results indicate that the models were able to quantify all compounds in each pixel. This approach is necessary since it is not possible to know the real concentration of each compound in the pixels. Neste trabalho, a espectroscopia de imagens no infravermelho próximo (NIR) foi empregada no estudo da distribuição do princípio ativo (API) espironolactona e seus excipientes em comprimidos. As análises foram realizadas utilizando resolução espacial de 50 µm, analisando 16 mm² de cada comprimido padrão. Modelos de mínimos quadrados parciais por intervalo (iPLS) foram utilizados para quantificação dos excipientes e API em cada pixel afim de obter mapas de concentração para cada composto. Foram obtidos erros de quantificação entre 0,49 e 1,26% quando realizada a validação cruzada utilizando a média espectral de cada comprimido. Esses modelos de calibração foram utilizados para prever a concentração individual de cada componente em cada pixel. A concentração média de todos os pixels, para cada composto, produziu erros entre 0,05 e 1,06%. Estes resultados indicaram que os modelos estavam aptos a quantificar todos os compostos em cada pixel, individualmente. Esta aproximação necessita ser realizada uma vez que não é possível conhecer a composição real em cada pixel.

Arrabidaea chica (crajiru) e uma importante planta da Amazonia. Seus extratos sao usados como pigmento, agentes antimicrobianos e adstringentes. Tres variedades diferentes desta especie sao cultivadas na regiao Amazonica. Neste trabalho, infusoes diretas de extratos de A. chica destas tres variedade foram analisadas por impressao digital via espectrometria de massas com ionizacao por eletrospray (ESI(+)-MS). Dados derivados destes espectros foram classificados utilizando um metodo de analise multivariada (PLS-DA, analise discriminante com calibracao multivariada por minimos quadrados parciais). O metodo direto aqui apresentado baseia-se na extracao de folhas secas e em po com uma solucao de metanol/agua acidificada sem manipulacao adicional da amostra. A solucao sobrenadante foi analisada atraves de infusao direta por ESI(+)-MS, o que resultou em perfis de composicao para cada variedade. 3-Desoxiantocianidinas sao importantes substâncias presentes na A. chica, seus ions foram usados como marcadores no tratamento de dados utilizando PLS-DA, o que possibilitou a separacao das tres variedades. Impressao digital por ESI(+)-MS funciona como um metodo simples e rapido para diferenciacao de variedades de A. chica. Arrabidaea chica (crajiru) is an important Amazonian plant. Its extracts are used as red pigments, antimicrobial agents and astringents. Three different varieties of this species are cultivated in the Amazon region. In this work, direct infusions of A. chica extracts from these three varieties were analyzed via electrospray ionization mass spectrometry (ESI(+)-MS) fingerprinting. Derived data from the spectra were classified by using a multivariate method (PLS-DA, partial least squares-discriminant analysis). The direct method that is herein presented relies on extraction of dry, powdered leaves with acidified methanol/water solution with no further sample preparation. The resulting supernatants were analyzed by direct infusion ESI(+)-MS, which provides characteristic fingerprints of the sample composition. 3-Deoxyanthocyanidins are important substances in A. chica, their ions were used as markers in the PLS-DA data treatment. PLS-DA was able to differentiate the three varieties. ESI(+)-MS fingerprinting works as a simple and fast method to differentiate varieties of A. chica.

This paper presents the application of infrared spectroscopy in conjunction with chemometric methods for quality control in adhesive manufacturing. From 105 infrared spectra of pressure-sensitive adhesive samples of different formulations, employing principal component analysis (PCA), it was possible the separation in four groups. By using partial least squares regression (PLS), the solid contents of 28 samples of water-based adhesive were determined. The interval-PLS (iPLS) was used for the determination of the viscosity of 73 solvent-based adhesive samples, with errors less than 7% in both cases. These results indicate the feasibility of employing ATR- FTIR and chemometrics as an attractive alternative for quality control in adhesive manufacturing. Este trabalho apresenta o emprego da espectroscopia no infravermelho combinada com ferramentas quimiométricas para o controle de qualidade de adesivos. A partir de 105 espectros no infravermelho de amostras de adesivos de diferentes tipos de formulação empregou-se análise de componentes principais (PCA), sendo possível a separação das amostras em quatro diferentes grupos. A regressão por mínimos quadrados parciais (PLS) foi utilizada na quantificação do teor de sólidos a partir de um conjunto de 28 amostras de adesivos com base aquosa. O PLS por intervalos (iPLS) foi usado na determinação de viscosidade a partir de um conjunto de 73 amostras de adesivos com base solvente, obtendo-se erros menores que 7% em ambos os casos. Dessa forma, os resultados indicam que o emprego de ATR-FTIR, aliada a quimiometria, é uma excelente alternativa para o controle de qualidade de uma indústria de adesivos.

article i nfo A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macro- nutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic. A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 µs integration time gate, 1.1 µs delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem.

Kohonen Neural Network maps were used for exploratory analysis of Brazilian Pilsner beers. The input data consisted of the peak areas of the volatile profile compounds of samples obtained after headspace solid phase microextraction coupled to gas chromatography. The chromatographic peaks were identified as originating from compounds such as alcohols, esters, organic acids, phenolic compounds, ketone and others typically found in the headspace of such samples. Analysis of the Kohonen maps showed that the 20 different brands of beer could be grouped into six sets, with three of these sets having only one sample, according to the composition of their volatile fractions. The volatile species associated with the similarities and differences between each sample group were tentatively identified by mass spectrometry mand their contributions to the grouping are discussed.

The diagnosis of the bacteria that cause pharyngitis through classical microbiological methods is a difficult, but usually very efficient task. However, the high cost of reagents and the time required for such identifications, about four days, could generate serious consequences, mainly when the patients concerned are children, the elderly or adults with low resistance. Thus, the search for new methods allowing a fast and reagentless differentiation of these microorganisms is extremely relevant. In this work, the main microorganisms responsible for pharyngitis, S. aureus, S. pyogenes and N. gonorrhoeae were studied. For each microorganism, sixty different dispersions were prepared using physiological solution as solvent. The Raman Spectra of these dispersions were recorded using a diode laser operating in the near infrared region. The PLS-discriminant analysis method was applied to bacteria differentiation through their respective Raman Spectra. This approach enabled the correct classification of 100% of all evaluated bacteria and unknown samples coming from clinical environment, in a reduced time interval (ca. 10 h), by using a low-cost, portable Raman spectrometer, which can be easily used in Intensive Care Units (ICU) and clinical environments. A diferenciação de bactérias causadoras de faringites através de métodos microbiológicos clássicos é muito eficiente, na maior parte dos casos. Todavia, o elevado custo dos reagentes e o tempo necessário para tais determinações, cerca de 4 dias, podem causar sérias conseqüências, quando os pacientes são crianças, idosos ou adultos com baixa resistência imunológica. Assim, a pesquisa por métodos espectroscópicos de baixo custo, que permitam tais determinações com pouco uso de reagentes e em curtos intervalos de tempo é extremamente relevante. Neste trabalho os principais microrganismos causadores de faringites, S. aureus, S. pyogenes and N. gonorrhoeae foram avaliados. Foram preparadas sessenta dispersões para cada um dos microrganismos, usando solução fisiológica como solvente, e seus espectros adquiridos. Os espectros Raman foram obtidos usando um laser de diodo operando na região do infravermelho próximo. A análise dos espectros foi feita usando PLS-discriminante. Esta abordagem permitiu classificar corretamente 100% de todas as bactérias avaliadas e amostras reais provenientes do laboratório de análises clinicas, em reduzido intervalo de tempo (ca. 10 h), com uso de espectrômetro Raman portátil, que pode ser facilmente usado em de Unidades de Tratamento Intensivo (UTI) e ambientes clínicos.

Foi desenvolvida uma metodologia para quantificar compostos dialquilmercuricos usando Microextracao em Fase Solida em Headspace (HS-SPME) e Cromatografia Gasosa com Deteccao por Emissao Atomica (GC-AED). Os parâmetros para deteccao de Hg foram otimizados usando planejamento fatorial e superficies de resposta. Experimentos univariados foram empregados para determinar as condicoes de HS-SPME; as melhores fibras foram 75 Mm de Carboxen / PDMS e 65 Mm de PDMS / DVB. Porem, as primeiras foram descartadas pela extensa degradacao termica dos analitos na dessorcao. O procedimento otimizado permite detectar os analitos em amostras aquosas com limite de deteccao de 1,7 e 0,2 ng L -1 para dimetil- and dietilmercurio, respectivamente. As curvas analiticas sao lineares nas faixas de 36 a 180 ng L -1 (Me 2 Hg) e 38 a 190 ng L -1 (Et 2 Hg), com limite de quantificacao de 38 ng L -1 (Me 2 Hg) e 29 ng L -1 (Et 2 Hg) e coeficientes de correlacao de 0,998 para Me 2 Hg e 0,999 para Et 2 Hg. A methodology to quantify dialkylmercury compounds using Headspace Solid Phase Microextraction (HS-SPME) and Gas Chromatography with Atomic Emission Detection (GC-AED) was developed. The parameters for Hg detection were optimized by factorial design and response surfaces. Univariate experiments were employed to determine the HS-SPME conditions; 75 Mm Carboxen / PDMS and 65 Mm PDMS / DVB were the best fibers. However, the former was excluded from further experiments due to extensive thermal degradation of analytes during desorption. The optimized procedure allowed detection of the analytes from aqueous samples with LOD of 1.7 ng L -1 and 0.2 ng L -1 for dimethyl- and diethylmercury, respectively. The analytical curves are linear in the range from 36 to 180 ng L -1 (Me 2 Hg) and 38 to 190 ng L -1 (Et 2 Hg), with LOQ of 38 ng L -1 (Me 2 Hg) and 29 ng L -1 (Et 2 Hg) and correlation coefficients of 0.998 for Me 2 Hg and 0.999 for Et 2 Hg.

The determination of soluble solids (BRIX), polarizable sugars (POL) and reducing sugars (RS) sugar cane juice by using near infrared spectroscopy (NIR) and multivariate calibration was developed and validated by calculation of figures of merit. Due to the heterogeneity of the samples, first it was necessary to optimize the calibration set by outlier elimination. The figures of merit such as: sensitivity, analytical sensitivity, selectivity, confidence limit, precision (mean, repeatability), accuracy and signal-to-noise ratio were calculated. Feasible results were obtained for BRIX and POL with RMSEP values of 0.28 and 0.42% of juice and precision of 0.02 and 0.08% of juice, respectively. For both BRIX and POL goodness of fit showed correlation coefficients of 0.99. These results indicate that the models developed for BRIX and POL can be used as an alternative to standard procedures in the sugar cane industry. Os teores de sólidos solúveis (BRIX), açúcares polarizáveis (POL) e açúcares redutores (RS) em caldo de cana foram determinados utilizando espectroscopia na região do infravermelho próximo (NIR) e calibração multivariada, a qual foi validada pelo cálculo das figuras de mérito. Devido à heterogeneidade das amostras, foi necessário, como primeira etapa do trabalho, a otimização dos conjutos de calibração e validação através da eliminação das amostras anômalas (outliers). As figuras de mérito como: sensibilidade, sensibilidade analítica, seletividade, limites de confiança, precisão (média, repetibilidade), exatidão e razão sinal-ruído foram calculadas. Resultados viáveis foram obtidos para BRIX e POL apresentando resultados de RMSEP de 0,28 e 0,42% de caldo, respectivamente. Os coeficientes de correlação para ambos os parâmetros foram de 0,99. Estes resultados indicam que os modelos desenvolvidos para BRIX e POL podem ser seguramente utilizados como uma alternativa em relação ao método padrão utilizado na indústria alcooleira.

This study examined the ability of near-infrared reflectance spectroscopy method (FT-NIRS) and multivariate calibration to estimate the concentration of moisture, protein, lipid, ash and carbohydrate of Brazilian soybeans. The spectra obtained in the range of 4000 to 10,000 cm − 1 were preprocessed by several combinations of mathematical treatments: MSC (multiplicative scatter correction), SNV (standard normal variate) or first and second derivative and all data were mean centered before the calibration, for which was used the PLS method (partial least squares). The best calibration models found in this study were the ones used to determine protein and moisture contents (R 2 = 0.81, RMSEP = 1.61% and R 2 = 0.80, RMSEC = 1.55%, respectively). However, the technique shows high predictability for all parameters, including lipids, ashes and carbohydrates, with RMSECV of 0.40 to 2.30% and RMSEP of 0.38 to 3.71%. This result shows the viability of using NIR in controlling the quality parameters of soybeans.