1000 resultados para espectroscopia no infravermelho


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In this work a fast method for the determination of the total sugar levels in samples of raw coffee was developed using the near infrared spectroscopy technique and multivariate regression. The sugar levels were initially obtained using gravimety as the reference method. Later on, the regression models were built from the near infrared spectra of the coffee samples. The original spectra were pre-treated according to the Kubelka-Munk transformation and multiplicative signal correction. The proposed analytical method made possible the direct determination of the total sugar levels in the samples with an error lower by 8% with respect to the conventional methodology.

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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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O tema “Plataforma smartphone para biossensores de Espectroscopia de Infravermelho Próximo”, surge no âmbito da instrumentação médica, na área das BCI – Brain Computer Interfaces, devido à necessidade de encontrar um dispositivo portátil, de custo acessível e elevada performance que permita obter informação acerca da actividade neuronal do córtex motor no decorrer duma determinada tarefa. O objectivo do trabalho consiste no desenvolvimento duma sonda capaz de detectar as alterações hemodinâmicas que ocorrem no córtex, bem como toda a instrumentação inerente à aquisição do sinal e transmissão dos dados para um computador, a análise dos dados e por fim o desenvolvimento de uma aplicação em Android para visualização dos resultados. Foi desenvolvida uma banda para a cabeça, composta pela sonda NIRS: LEDs (Light-Emiting Diodes) de 940nm e 660nm e os respectivos fototransístores de detecção, bem como toda a electrónica de condicionamento do sinal captado. Num módulo à parte, alimentado por duas baterias de 9V, encontram-se os circuitos electrónicos onde é possível regular ganhos de amplificação e offsets. Os dados foram adquiridos pelo microcontrolador Arduíno Uno, usando uma taxa de amostragem de 50Hz em cada um dos dois canais utilizados. O controlo do Arduíno foi feito utilizando o LabVIEW. Para o processamento dos dados, visualização e cálculo das concentrações de oxi e desoxi-hemoglobina no sangue recorreu-se ao Matlab. O sistema foi calibrado com recurso a um oxímetro de pulso clínico usado em cinco indivíduos saudáveis. Finalmente o sistema foi testado ao colocar-se o sensor NIRS sobre o córtex motor esquerdo de nove indivíduos saudáveis destros, fazendo-se uma aquisição de dados durante dois minutos. Utilizou-se um paradigma de 10s de repouso seguido de 10s a abrir e fechar a mão. O sistema NIRS conseguiu medir as alterações que ocorrem nas concentrações de oxi e desoxi-hemoglobina devido à actividade motora de abrir e fechar a mão. Dado o princípio físico ser o mesmo do dos oxímetros convencionais, conseguiu-se ainda medir com sucesso a frequência cardíaca e a saturação percentual de oxigénio após a calibração do sensor. As medidas podem ser visualizadas numa aplicação desenvolvida para o Android. Os resultados sugerem que com esta abordagem, este tipo de dispositivo pode estar disponível a baixo custo quer para doentes quer para indivíduos saudáveis, por exemplo em aplicações de telemóvel.

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A aplicação de técnicas espectroscópicas que utilizam a radiação infravermelha (NIRS-Near Infrared Spectroscopy e DRIFTS-Diffuse Reflectance Fourier Transformed Spectroscopy) na análise inorgânica do solo tem sido proposta desde a década de 1970, mas até os dias atuais são raros os métodos implementados rotineiramente no Brasil. Isso deve-se à dificuldade em construir modelos de calibração, por meio de métodos estatísticos multivariados, utilizando-se amostras reais de solo, de constituição complexa, que varia geograficamente e de acordo com o manejo. Por isso, os objetivos deste trabalho foram construir modelos de calibração em NIRS e DRIFTS para a quantificação das frações de argila e areia, em amostras de solos de classes diferentes - Latossolo Vermelho (predominante), Nitossolo, Argissolo Vermelho e Neossolo Quartzarênico - e avaliar qual dessas duas técnicas é mais adequada para essa finalidade, assim como a interferência do agrupamento de amostras e da seleção de variáveis espectrais na qualidade desses modelos. Para isso, valores de referência obtidos pelo método do densímetro, método largamente utilizado nos laboratórios de análise de solo, foram correlacionados com valores de absorbância em NIRS e DRIFTS pela ferramenta estatística PLS (Partial Least Squares), obtendo-se altos coeficientes de determinação (R²), de 0,95, 0,90 e 0,91 para argila, silte e areia, respectivamente, na validação externa. Isso confirma a aplicabilidade das técnicas espectroscópicas na análise granulométrica do solo para fins agrícolas. O agrupamento das amostras segundo a localização e a seleção de variáveis espectrais pouco influenciou na qualidade dos modelos. A técnica espectroscópica mais indicada para essa finalidade foi a DRIFTS.

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The influence of the presence of hydrogen on Pt/TiO2 catalysts submitted to reduction treatment has been studied by FT-IR at room temperature. After submitting to LTR treatment, the hydrogen spillover has been detected and the presence of hydrogen at the bulk is shown to produce a strong absorption in the infrared spectral region. After HTR treatment, the hydrogen is strongly chemissorbed.

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Genetic algorithm was used for variable selection in simultaneous determination of mixtures of glucose, maltose and fructose by mid infrared spectroscopy. Different models, using partial least squares (PLS) and multiple linear regression (MLR) with and without data pre-processing, were used. Based on the results obtained, it was verified that a simpler model (multiple linear regression with variable selection by genetic algorithm) produces results comparable to more complex methods (partial least squares). The relative errors obtained for the best model was around 3% for the sugar determination, which is acceptable for this kind of determination.

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The application of analytical procedures based on multivariate calibration models has been limited in several areas due to requirements of validation and certification of the model. Procedures for validation are presented based on the determination of figures of merit, such as precision (mean, repeatability, intermediate), accuracy, sensitivity, analytical sensitivity, selectivity, signal-to-noise ratio and confidence intervals for PLS models. An example is discussed of a model for polymorphic purity control of carbamazepine by NIR diffuse reflectance spectroscopy. The results show that multivariate calibration models can be validated to fulfill the requirements imposed by industry and standardization agencies.

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In this work a fast method for the determination of the total sugar levels in samples of raw coffee was developed using the near infrared spectroscopy technique and multivariate regression. The sugar levels were initially obtained using gravimety as the reference method. Later on, the regression models were built from the near infrared spectra of the coffee samples. The original spectra were pre-treated according to the Kubelka-Munk transformation and multiplicative signal correction. The proposed analytical method made possible the direct determination of the total sugar levels in the samples with an error lower by 8% with respect to the conventional methodology.

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In this work an analytical methodology for the determination of relevant physicochemical parameters of prato cheese is reported, using infrared spectroscopy (DRIFT) and partial least squares regression (PLS). Several multivariate models were developed, using different spectral regions and preprocessing routines. In general, good precision and accuracy was observed for all studied parameters (fat, protein, moisture, total solids, ashes and pH) with standard deviations comparable with those provided by the conventional methodologies. The implantation of this multivariate routine involves significant analytical advantages, including reduction of cost and time of analysis, minimization of human errors, and elimination of chemical residues.

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Four tropical woods, were investigated to compare their performance and natural resistances to artificial weathering using the diffuse reflectance infrared Fourier transform spectroscopy (DRIFT). The species were garapeira (Apuleia leiocarpa), itaúba (Mezilaurus itauba) and tauari (Couratari sp.), woods traditionally indicated for exterior uses, and marupá (Simarouba amara), that served as reference. The samples were submitted to cycles of UV radiation (350 nm) and water until 2,000 h. The photodegradation processes of woods surfaces were accomplished monitoring the changes in the intensities associated to lignin (1508 cm-1) and carbonyl group (1736 cm-1) absorptions. The results have shown that lignin was the first component to be photodegradated, resulting in surfaces mainly composed by cellulose, after 2,000 h of UV irradiation. The processes of formation and lixiviation of carbonyl compounds were different for each species. The experimental conditions used in this work were too severe to evaluate the wood density and extractives content influences during the treatment.

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The main objective of the present work is represented by the characterization of the physical properties of industrial kraft paper (i.e. transversal and longitudinal tear resistance, transversal traction resistance, bursting or crack resistance, longitudinal and transversal compression resistance (SCT (Compressive Strength Tester) and compression resistance (RCT-Ring Crush Test)) by near infrared spectroscopy associated to partial least squares regression. Several multivariate models were developed, many of them with high prevision capacity. In general, low prevision errors were observed and regression coefficients that are comparable with those provided by conventional standard methodologies.

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The goal of this work is the development and validation of an analytical method for fast quantification of sibutramine in pharmaceutical formulations, using diffuse reflectance infrared spectroscopy and partial least square regression. The multivariate model was elaborated from 22 mixtures containing sibutramine and excipients (lactose, microcrystalline cellulose, colloidal silicon dioxide and magnesium stearate) and using fragmented (750-1150/ 1350-1500/ 1850-1950/ 2600-2900 cm-1) and smoothing spectral data. Using 10 latent variables, excellent predictive capacity were observed in the calibration (n=20, RMSEC=0.004, R= 0.999) and external validation (n=5, RMSEC= 9.36, R=0.999) phases. In the analysis of synthetic mixtures the precision (SD=3,47%) was compatible with the rules of the Agencia Nacional de Vigilância Sanitária (ANVISA-Brazil). In the analysis of commercial drugs good agreement was observed between spectroscopic and chromatographic methods.

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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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Mid-infrared spectroscopy and chemometrics were used to identify adulteration in roasted and ground coffee by addition of coffee husks. Consumers' sensory perception of the adulteration was evaluated by a triangular test of the coffee beverages. Samples containing above 0.5% of coffee husks from pure coffees were discriminated by principal component analysis of the infrared spectra. A partial least-squares regression estimated the husk content in samples and presented a root-mean-square error for prediction of 2.0%. The triangular test indicated that were than 10% of coffee husks are required to cause alterations in consumer perception about adulterated beverages.

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The aim of this manuscript was to show the basic concepts and practical application of Partial Least Squares (PLS) as a tutorial, using the Matlab computing environment for beginners, undergraduate and graduate students. As a practical example, the determination of the drug paracetamol in commercial tablets using Near-Infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression was shown, an experiment that has been successfully carried out at the Chemical Institute of Campinas State University for chemistry undergraduate course students to introduce the basic concepts of multivariate calibration in a practical way.