Fourier transform near-infrared spectroscopy (FT-NIRS) application to estimate Brazilian soybean [Glycine max (L.) Merril] composition

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)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 230% and RMSEP of 038 to 3.71%. This result shows the viability of using NIR in controlling the quality parameters of soybeans. (C) 2012 Elsevier Ltd. All rights reserved.5115358Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [2010/50418-5

Method for assessing lead, cadmium, mercury and arsenic in high-density polyethylene packaging and study of the migration into yoghurt and simulant

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The purpose of this paper was to assess the concentration of lead (Pb), cadmium (Cd), mercury (Hg) and arsenic (As) in high-density polyethylene (HDPE) packaging intended for contact with yoghurt and the migration of these elements using the food itself and 3% acetic acid as a food simulant in accordance to ANVISA, the Brazilian Health Surveillance Agency. In order to perform this study, it was necessary to develop and validate a method by inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis. For method validation, the parameters linearity, limits of detection (LODs) and quantification (LOQs), accuracy and precision were determined. Fifteen commercial samples of yoghurt, marketed in Campinas - SAo Paulo (Brazil), were used for the analysis. The packaging and yoghurt were digested in high-pressure ashing equipment (HPA) and the migration of the elements into simulant were determined directly in the solution. The validated method proved adequate and the results obtained showed that all the packaging had levels of Hg and Cd below the LOQ, corresponding to 1.0 and 1.5gl(-1), respectively. The highest levels of As and Pb were 0.87 and 462.3mgkg(-1), respectively. The migration of these elements to the yoghurt after 45days of contact at 4oC was below the LOQ for all the samples assessed. The results of specific migration into 3% acetic acid simulant showed the concentrations of Cd, Hg and As below 5, 5 and 10 mu gkg(-1), respectively, which are the maximum limits set by ANVISA. However, for three samples the packaging lid showed migration of Pb into simulant ranging from 30.6 to 40.2 gkg(-1), exceeding the limit set by ANVISA of 10 gkg(-1).311156163Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP [2007/08211-0

Comparison and application of near-infrared (NIR) and mid-infrared (MIR) spectroscopy for determination of quality parameters in soybean samples

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Grain composition is directly related to maintenance of quality. Chemical analyses have been determined using traditional and laborious methods, which are time-consuming and generate chemical waste. This justifies the development of fast and accurate alternative methodologies to control the grain composition. Near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques associated with chemometric tools have been applied in the development of several analytical methodologies for agricultural products. The aim of this study is to develop and compare these two spectroscopic techniques to determine the parameters of quality, such as moisture, protein, lipid and ash content, in 20 varieties of soybean, which are grown in the cities of Ponta Grossa and Londrina, Brazil, totally 40 samples. It was used near-infrared and mid-infrared spectroscopy, with diffuse reflectance measurements, associated with multivariate calibration methods based on partial least squares algorithm. The determination coefficient (R-2) for moisture, ash, protein and lipid content were 0.72, 0.73, 0.88 and 0.81 for NIR and 0.63, 0.87, 0.91 and 0.67 for MIR, respectively, having an RMSECV (root mean square error of cross-validation) <2.09%. The results show that both infrared (NIR and MIR) techniques have predictive abilities. (C) 2013 Elsevier Ltd. All rights reserved.351227232Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP [2010/50418-3

Chemometrics optimization of carbohydrate separations in six food matrices by micellar electrokinetic chromatography with anionic surfactant

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Multivariate statistical design modeling and the Derringer-Suich desirability function analysis were applied to micellar electrokinetic chromatography (MEKC) results with anionic surfactant to separate carbohydrates (CHOs) in different food matrices. This strategy has been studied with success to analyze compounds of difficult separation, but has not been explored for carbohydrates. Six procedures for the analysis of different sets of CHOs present in six food matrices were developed. The effects of pH, electrolyte and surfactant concentrations on the separation of the compounds were investigated using a central composite design requiring 17 experiments. The simultaneous optimization of the responses for separation of six sets of CHOs was performed employing empirical models for prediction of optimal resolution conditions in six matrices, condensed milk, orange juices, rice bran, red wine, roasted and ground coffee and breakfast cereal samples. The results indicate good separation for the samples, with appropriate detectability and selectivity, short analysis time, low reagent cost and little waste generation, demonstrating that the proposed technique is a viable alternative for carbohydrate analysis in foods. (C) 2011 Elsevier B.V. All rights reserved.851237244Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [07/56714-0