Quantitative and qualitative analysis of VOCs mixtures by means of a microsensors array and different evaluation methods

In this work we show the capability of a sol-gel based electronic nose to be used in qualitative and quantitative analysis with the aim to recognize common volatile compounds usually present in the headspace of foods. Acetone, hexanal and 2-pentanone were chosen for this kind of measurements, performed both in dry air and in mixture of 50% humidity, just to simulate the experimental set-up in real applications. Moreover, different mixtures of 2-pentanone and hexanal at low concentration were investigated. We show how linear technique, such as principal component analysis (PCA) algorithm can be used for inspecting data distribution in simple cases like cluster discrimination. Moreover, non-linear techniques for difficult regression problems, such as artificial neural networks (multi-layer perceptron (MLP) and radial basis function (RBF)) are needed in particular for the prediction of different concentrations.