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%

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

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

Caracterização infravermelho e distribuição espectral de energia para as estrelas com planetas

Neste trabalho estudamos o comportamento das estrelas pertencentes a sistemas planetários no que diz respeito às suas características infravermelho e à distribuição espectral de energia (SED). Nosso estudo tem como base uma análise detalhada do comportamento da emissão no infravermelho de 48 estrelas com planetas, classificadas como estrelas da seqüência principal, subgigantes ou gigantes. Foram analisados dados de fotometria infravermelho nas bandas 12, 25 e 60µm do catálogo de fontes IRAS puntiformes (IPSC) e nas bandas JHK do projeto 2 Micron All Sky Survey (2MASS). A partir do cálculo da discrepância na posição de apontamento da fonte e do cálculo do índice de cor, selecionamos e localizamos os objetos no diagrama de cor-cor do IRAS. Este diagrama permite-nos identificar possíveis objetos detentores de disco de poeira. Fizemos também uma análise da distribuição espectral de energia onde observamos também traços de excesso de fluxo no infravermelho, com isso, confirmarmos a presença do disco de poeira nos objetos identificados no diagrama de cor. Apesar da atual amostra de estrelas com planetas incluir apenas um subconjunto de estrelas com planetas detectadas na vizinhança solar, a presente análise do fluxo infravermelho nesses objetos oferecem uma possibilidade única de estudar as características infravermelho das estrelas pertencentes aos sistemas planetários extra-solar. Neste contexto, nosso estudo aponta resultados interessantes, entre outros destacamos o fato de algumas estrelas com planetas apresentarem um peculiar fluxo IRAS [60-25], indicando a co-existência de poeira juntamente com os planetas destes sistemas extra solar

Uso das técnicas de infravermelho e de ressonância magnética nuclear na caracterização da reação ácido-base de um cimento odontológico experimental

Glass ionomer cements (GICs) are products of the acid-base setting reaction between an finely fluoro-alumino silicate glass powder and poly(acrylic acid) in aqueous solution. The sol gel method is an adequate route of preparation of the glasses used to obtain the GICs. The objective of this paper was to compare two powders: a commercial and an experimental and to investigate the structural changes during hardening of the cements by FTIR and Al MAS NMR. These analyses showed that the experimental glass powder reacted with organic acid to form the GICs and it is a promising material to manufacture dental cements.

Correlação entre dados estruturais e bandas de vibração no infravermelho para a fase espinélio Zn7-xNi xSb2O12

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

Determinação do índice de estresse hídrico em cultura do feijoeiro com termômetro de infravermelho

In order to calculate the daily stress degree of a bean crop submitted to four water regime applications, cover crop and air daily measurements temperatures were accomplished by using a hand-held infrared thermometer. The treatments did not present crop water stress except the control (without irrigation). The highest yield was obtained by the treatment that received less irrigation frequency, and among the treatments that had the same number of irrigation. The largest yield was obtained with the one that received larger amount of applied water. The largest irrigation frequency did not result in larger productivity. The methodologies used for the irrigation planning were efficient for the replacement of soil water. The daily stress degree index was effective in determining crop water stress; and it was reliable presenting negative values in good water soil condition.

Identificação do teor de nitrogênio foliar em cana-de-açúcar no estágio inicial de crescimento utilizando infravermelho próximo e sistemas inteligentes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimação de variáveis físico-químicas de solo por espectroscopia no visível e no infravermelho próximo através de sistemas inteligentes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo de transições durante o processo de desenovelamento térmico da RNase A por meio da calorimetria (DSC) e espectroscopia de correlação bidimensional no infravermelho médio (2D-IR)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo do desenovelamento da papaína via espectroscopias de fluorecência e correlação bidimensional no infravermelho

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise quantitativa de espectros de absorção no infravermelho de compósitos odontológicos fotoativados

Pós-graduação em Ciência dos Materiais - FEIS