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Detection and Classification of Hydrolyzed Dairy Additives Using Electronic Noses

2018; American Scientific Publishers; Volume: 16; Issue: 6 Linguagem: Inglês

10.1166/sl.2018.3973

1546-198X

Juan Vorobioff, Mauricio Adaro, Norberto Boggio, Jorge Magallanes, A. Boselli, A. Lamagna, Carlo Rinaldi,

Identification and Quantification in Food

In the present work the classification of dairies additives in a rapid and simple way, is proposed.Measurements were made by means of an Electronic Nose developed in our laboratories, which we named 'Patagonia E-Nose.'This E-Nose is composed of SnO 2 sensors located in a thermally stabilized chamber which improves the repeatability of the measurements.Samples of various hydrolyzed dairies were measured using air as a reference gas.Then, the integrals of the signals were analyzed using a combination of different multivariate chemometric methods such as linear discriminant analysis (LDA), principal components analysis (PCA), back-propagation neural network and different classifiers.Also, different algorithms were implemented and compared by calculating the number of correctly classified samples of each method.99.4% of correct classifications were obtained by using cross-validation and selecting the most appropriate algorithms.The results indicate that the samples were correctly classified through the implementation of a simple and low cost measurement protocol.