Classification of red wines by chemometric analysis of voltammetric signals from PEDOT-modified electrodes.

Nine different types of Italian red wines of four different varieties were analysed, without any sample pre-treatments, by voltammetric techniques using a poly(3,4-ethylenedioxythiophene)-modified electrode. The data matrices consisting of the currents measured at different potentials, by repeated Cyclic Voltammetry or Differential Pulse Voltammetry, are submitted to chemometric analysis. After explorative tests based on Principal Component Analysis, Partial Least Squares-Discriminant Analysis classification models are built both for the training and for the test sets. To this aim, different classification strategies are adopted, considering the responses from the two techniques either separately or joined together to form a data matrix including the whole voltammetric information.

Amperometric sensors based on poly(3,4-ethylenedioxythiophene)-modified electrodes: discrimination of white wines.

The voltammetric responses on selected white wines of different vintages and origins have been systematically collected by three different modified electrodes, in order to check their effectiveness in performing blind analysis of similar matrices. The electrode modifiers consist of a conducting polymer, namely poly(3,4-ethylenedioxythiophene) (PEDOT) and of composite materials of Au and Pt nanoparticles embedded in a PEDOT layer. Wine samples have been tested, without any prior treatments, with differential pulse voltammetry technique. The subsequent chemometric analysis has been carried out both separately on the signals of each sensor, and on the signals of two or even three sensors as a unique set of data, in order to check the possible complementarity of the information brought by the different electrodes. After a preliminary inspection by principal component analysis, classification models have been built and validated by partial least squares-discriminant analysis. The discriminant capability has been evaluated in terms of sensitivity and specificity of classification; in all cases quite good results have been obtained.

Development of an electronic tongue based on a PEDOT-modified voltammetric sensor.

Three different electrodes were tested for use as nonspecific amperometric sensors for blind analysis on real matrices, namely different fruit juices from different fruits or different brands. The first two electrodes were traditional Pt and Au electrodes, while the third one was modified with poly(3,4-ethylenedioxythiophene) conducting polymer. The sensors were tested separately, tested coupled to each other, and also tested together. The responses of the electrode system(s) were first screened via PCA and then their discriminant capabilities were quantified in terms of the sensitivities and specificities of their corresponding PLS-DA multivariate classification models. Particular attention was paid to analyzing the evolution of the response over subsequent potential sweeps. The modified electrode demonstrated the most discriminating ability, and it was the only system capable of satisfactorily performing the most complex task attempted during the analysis: discriminating between juices from the same fruit but from different brands. Moreover, the electrode "cleaning" procedure required between two subsequent potential sweeps was much simpler for the modified electrode than for the others. This electrode system was therefore shown to be a good candidate for use as an informative element in an electronic tongue applied to the analysis of other food matrices.