Juiz de Fora, Brazil
Juiz de Fora, Brazil

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da Silva F.L.,Federal University of Viçosa | Ferreira H.A.L.,Gemacom Technology | de Souza A.B.,Gemacom Technology | Almeida D.D.F.,Gemacom Technology | And 4 more authors.
LWT - Food Science and Technology | Year: 2015

This study evaluated the effect of addition of modified starch on the characteristics of dulce de leche, being conducted in two phases. In the initial phase, starches were evaluated for their ability to provide viscosity in model solutions representing the composition of dulce de leche during processing, thus evaluating the effect of solid concentration, which occurs during production, on the ability of starches to increase viscosity in simulated conditions of heat treatment and agitation promoted by Rapid Visco Analyser (RVA). It has been chosen 2 starches and 2 concentrations of soluble solids from the results of the initial phase, being employed as a criterion of choice starches with the highest viscosities at each solid concentration processing phase. In the second stage, 6 treatments were applied in triplicate, in which it's been determined the chemical composition, the instrumental color, texture profile and yield. Analyses were performed on crystallization of lactose during storage. According to the established conditions of the experiment, the starch configures itself as an important optional ingredient for the production of dulce de leche providing then longer shelf life without change in texture, composition, yield and sensory characteristic. © 2014 Elsevier Ltd.

de Almeida M.R.,Federal University of Juiz de fora | de Sa Oliveira K.,Federal University of Juiz de fora | Stephani R.,Gemacom Technology | Cappa de Oliveira L.F.,Federal University of Juiz de fora
Analytical Letters | Year: 2012

In this work, FT-Raman spectroscopy is explored as a rapid technique for the assessment of the milk powder quality. Based on information provided by Raman spectra of samples adulterated with starch and whey, a quantitative method is developed to identify the fraud, using Partial Least Squares regression (PLS). In regression models using PLS the results are satisfactory, and such models can be used to identify and quantify samples presenting whey and starch in milk powder at concentrations of 2.32% and 1.64% (w/w), respectively. In the whey determination, the obtained values in the PLS model of the new samples are compared with those obtained by the spectrophotometric method of acid ninhydrin. This result shows that there is no significant difference with the 95% level of confidence between the values provided by the PLS regression method and the acid ninhydrin. The present work shows Raman spectroscopy as an analytical tool which can be used in quality control of milk powder, even in fraud processes, and the calculated figures of merit such as sensitivity, accuracy, limit of detection and limit of quantification clearly demonstrate this potential use. Although the multivariate models developed are not strictly quantitative, especially for low concentrations, they can be used as screening methods for routine analysis, as showed by this work. © 2012 Copyright Taylor and Francis Group, LLC.

Almeida M.R.,Federal University of Juiz de fora | Oliveira K.D.S.,Federal University of Juiz de fora | Stephani R.,Gemacom Technology | De Oliveira L.F.C.,Federal University of Juiz de fora
Journal of Raman Spectroscopy | Year: 2011

In this work, FT-Raman spectroscopy was explored as a fast and reliable screening method for the assessment of milk powder quality and the identification of samples adulterated with whey (1-40% w/w). Raman measurements can easily differentiate milk powders without the need of sample preparation, whereas the traditional methods of quality control, including high-performance liquid chromatography, are laborious and slow. The FT-Raman spectra of whole, low-fat, and skimmed milk powder samples were obtained and distinguished from commercial milk powder samples. In addition, the exploratory analysis employing data from Raman spectroscopy and principal component analysis (PCA)allowed the separation of milk powder samples according to type,identifying differences between samples in the same group. Multivariate analysis was also developed to classify the adulterated milk powder samples using PCA and partial least squares discriminate analysis (PLS-DA). The resulting PLS-DA model correctly classified 100% of the adulterated samples. These results clearly demonstrate the utility of FT-Raman spectroscopy combined with chemometrics as a rapid method for screening milk powder. © 2011 John Wiley & Sons, Ltd.

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