Determinação do teor de diclofenaco sódico em comprimidos por espectroscopia no infravermelho próximo NIR com calibração multivariada PLS

This work is combined with the potential of the technique of near infrared spectroscopy - NIR and chemometrics order to determine the content of diclofenac tablets, without destruction of the sample, to which was used as the reference method, ultraviolet spectroscopy, which is one of the official methods. In the construction of multivariate calibration models has been studied several types of pre-processing of NIR spectral data, such as scatter correction, first derivative. The regression method used in the construction of calibration models is the PLS (partial least squares) using NIR spectroscopic data of a set of 90 tablets were divided into two sets (calibration and prediction). 54 were used in the calibration samples and the prediction was used 36, since the calibration method used was crossvalidation method (full cross-validation) that eliminates the need for a validation set. The evaluation of the models was done by observing the values of correlation coefficient R 2 and RMSEC mean square error (calibration error) and RMSEP (forecast error). As the forecast values estimated for the remaining 36 samples, which the results were consistent with the values obtained by UV spectroscopy

Desenvolvimento, validação, avaliação da incerteza de medição e análise de custos de método baseado em espectroscopia no infravermelho e análise multivariada para previsão de parâmetros de qualidade de amostras de E85

Pós-graduação em Química - IQ

Determinação de sólidos solúveis e firmeza em frutos íntegros de pessegueiro por meio da espectroscopia do infravermelho próximo (NIR)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação de espectroscopia no infravermelho médio e calibração multivariada para quantificação de adulterantes e teor em biodiesel de óleo de palma com óleo de soja, soja residual e diesel

In this work, it was developed and validated methodologies that were based on the use of Infrared Spectroscopy Mid (MIR) combined with multivariate calibration Square Partial Least (PLS) to quantify adulterants such as soybean oil and residual soybean oil in methyl and ethyl palm biodiesels in the concentration range from 0.25 to 30.00 (%), as well as to determine methyl and ethyl palm biodiesel content in their binary mixtures with diesel in the concentration range from 0.25 to 30.00 (%). The prediction results showed that PLS models constructed are satisfactory. Errors Mean Square Forecast (RMSEP) of adulteration and content determination showed values of 0.2260 (%), with mean error (EM) with values below 1.93 (%). The models also showed a strong correlation between actual and predicted values, staying above 0.99974. No systematic errors were observed, in accordance to ASTM E1655- 05. Thus the built PLS models, may be a promising alternative in the quality control of this fuel for possible adulterations or to content determination.

Determinação de teor de biodieseis de algodão e pinhão manso em misturas com diesel usando espectroscopia no infravermelho médio e quadrados mínimos parciais

Biodiesel is a renewable fuel derived from vegetable oils or animal fats, which can be a total or partial substitute for diesel. Since 2005, this fuel was introduced in the Brazilian energy matrix through Law 11.097 that determines the percentage of biodiesel added to diesel oil as well as monitoring the insertion of this fuel in market. The National Agency of Petroleum, Natural Gas and Biofuels (ANP) establish the obligation of adding 7% (v/v) of biodiesel to diesel commercialized in the country, making crucial the analytical control of this content. Therefore, in this study were developed and validated methodologies based on the use of Mid Infrared Spectroscopy (MIR) and Multivariate Calibration by Partial Least Squares (PLS) to quantify the methyl and ethyl biodiesels content of cotton and jatropha in binary blends with diesel at concentration range from 1.00 to 30.00% (v/v), since this is the range specified in standard ABNT NBR 15568. The biodiesels were produced from two routes, using ethanol or methanol, and evaluated according to the parameters: oxidative stability, water content, kinematic viscosity and density, presenting results according to ANP Resolution No. 45/2014. The built PLS models were validated on the basis of ASTM E1655-05 for Infrared Spectroscopy and Multivariate Calibration and ABNT NBR 15568, with satisfactory results due to RMSEP (Root Mean Square Error of Prediction) values below 0.08% (<0.1%), correlation coefficients (R) above 0.9997 and the absence of systematic error (bias). Therefore, the methodologies developed can be a promising alternative in the quality control of this fuel.

Estudo da reação entre o metanol e o acetato de etila em catalisadores Mg/La por espectroscopia no infravermelho acoplada a espectrometria de massas

A transesterificação metílica em meio homogêneo é catalisada por bases, tais como hidróxidos e alcóxidos de sódio ou potássio e se processa em baixa temperatura de reação, mesmo em escala industrial. A utilização de catalisadores formados por sólidos básicos aparece como uma alternativa promissora aos processos homogêneos convencionais, tendo em vista as inúmeras vantagens como a redução da ocorrência das reações indesejáveis de saponificação e redução de custos dos processos pela diminuição do número de operações associadas. Em estudos anteriores realizados pelo grupo, catalisadores a base de Mg/La com diferentes composições químicas (9:1, 1:1 e 1:9) mostraram-se promissores para a obtenção de ésteres metílicos via reação de transesterificação, porém não foi possível fazer uma correlação entre atividade catalítica e as propriedades físico-químicas quando toda a série foi considerada. Assim, a realização de um estudo de caráter fundamental, baseado em reações modelo e uso de moléculas sonda, permite avançar no entendimento das propriedades de superfície destes catalisadores. Portanto, o presente trabalho estuda a reação entre metanol e acetato de etila em catalisadores a base de Mg/La utilizando espectroscopia de reflectância difusa no infravermelho com transformada de Fourier (DRIFTS) acoplada a espectrometria de massas (MS) identificando os intermediários e produtos formados para determinar a rota reacional. As análises de difração de raios X mostram que os precursores são predominantemente compostos por carbonatos hidratados de magnésio (Mg/La 1:1 e 9:1) e de lantânio (Mg/La 1:9). Os perfis de decomposição térmica e difratogramas de raios X obtidos a partir de tratamento térmico in situ indicaram que estes carbonatos se decompõem apenas a partir de 750 C. As análises de Dessorção a Temperatura Programada realizadas com moléculas sonda, metanol e acetato de etila, mostraram a adsorção em maior quantidade do metanol independente da composição química do sólido. A partir dos resultados obtidos por DRIFTS-MS foi proposta uma rota reacional para a reação de transesterificação do acetato de etila e metanol, que ocorre via adsorção do metanol e do acetato de etila na superfície do catalisador, seguida da formação de um intermediário tetraédrico formado pelas moléculas adsorvidas, que sofre um rearranjo formando etanol, acetato de metila, acetona e metano. Simultaneamente, parte do metanol adsorvido como metoxi monodentado é desidrogenado formando formiatos que são dessorvidos na forma de formaldeído e decompostos formando CO2 e H2

Avaliação da espectroscopia de infravermelho para determinação de características físico-químicas da carne suína

Dissertação de mest., Tecnologia de Alimentos, Instituto Superior de Engenharia, Univ. do Algarve, 2013

Monitoramento em tempo real de processos fermentativos por espectroscopia no infravermelho próximo (NIRS)

A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes

Construção de modelos multivariados para determinação de lipídios totais e unidade em leite em pó comercial utilizando espectroscopia no infravermelho próximo

In this work calibration models were constructed to determine the content of total lipids and moisture in powdered milk samples. For this, used the near-infrared spectroscopy by diffuse reflectance, combined with multivariate calibration. Initially, the spectral data were submitted to correction of multiplicative light scattering (MSC) and Savitzsky-Golay smoothing. Then, the samples were divided into subgroups by application of hierarchical clustering analysis of the classes (HCA) and Ward Linkage criterion. Thus, it became possible to build regression models by partial least squares (PLS) that allowed the calibration and prediction of the content total lipid and moisture, based on the values obtained by the reference methods of Soxhlet and 105 ° C, respectively . Therefore, conclude that the NIR had a good performance for the quantification of samples of powdered milk, mainly by minimizing the analysis time, not destruction of the samples and not waste. Prediction models for determination of total lipids correlated (R) of 0.9955, RMSEP of 0.8952, therefore the average error between the Soxhlet and NIR was ± 0.70%, while the model prediction to content moisture correlated (R) of 0.9184, RMSEP, 0.3778 and error of ± 0.76%

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Determinação de parâmetros (sólidos solúveis, pH e acidez titulável) em ameixas intactas usando espectroscopia no infravermelho próximo e seleção de comprimento de onda

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums

Uso da espectroscopia do infravermelho próximo e técnicas multivariadas para diferenciar escherichia coli e salmonella enteritidis inoculadas em polpa de fruta (abacaxi)

Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

Estudo da potencialidade da espectroscopia de infravermelho próximo na análise de cabelo utilizando ferramentas quimiométricas para diferenciar fumantes de não fumantes

This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification

Estudos de materiais ferroelétricos por espectroscopia no infravermelho

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Transições de fases estruturais do sistema PZT, estudados por espectroscopia no infravermelho

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)