This work reports the application of a voltammetric electronic tongue system (ET) made from an array of modified graphite-epoxy composites plus a gold microelectrode in the qualitative and quantitative analysis of polyphenols found in wine. Wine samples were analyzed using cyclic voltammetry without any sample pretreatment. The obtained responses were preprocessed employing discrete wavelet transform (DWT) in order to compress and extract significant features from the voltammetric signals, and the obtained approximation coefficients fed a multivariate calibration method (artificial neural network-ANN-or partial least squares-PLS-) which accomplished the quantification of total polyphenol content. External test subset samples results were compared with the ones obtained with the Folin-Ciocalteu (FC) method and UV absorbance polyphenol index (I(280)) as reference values, with highly significant correlation coefficients of 0.979 and 0.963 in the range from 50 to 2400 mg L(-1) gallic acid equivalents, respectively. In a separate experiment, qualitative discrimination of different polyphenols found in wine was also assessed by principal component analysis (PCA).

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a b s t r a c tThis paper reports the use of a hybrid electronic tongue based on data fusion of two different sensor families, applied in the recognition of beer types. Six modified graphite-epoxy voltammetric sensors plus 15 potentiometric sensors formed the sensor array. The different samples were analyzed using cyclic voltammetry and direct potentiometry without any sample pretreatment in both cases. The sensor array coupled with feature extraction and pattern recognition methods, namely Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), was trained to classify the data clusters related to different beer varieties. PCA was used to visualize the different categories of taste profiles, while LDA with leave-one-out cross-validation approach permitted the qualitative classification. The aim of this work is to improve performance of existing electronic tongue systems by exploiting the new approach of data fusion of different sensor types.

This work demonstrates the use of a voltammetric electronic tongue formed by five modified graphite-epoxy electrodes in the qualitative and quantitative analysis of cava wines. The different samples were analyzed using cyclic voltammetry without any sample pretreatment. Recorded data were evaluated by Principal Component Analysis and Discrete Wavelet Transform in order to compress and extract significant features from the voltammetric signals. The preprocessed information was evaluated by an Artificial Neural Network that accomplishes the qualitative classification. Moreover, a preliminary study related to the quantification of sugar amount present was assessed by Second-Order Standard Addition Method.

Molecularly imprinted polymers (MIPs) are artificially synthesized materials to mimic the molecular recognition process of biological macromolecules such as substrate-enzyme or antigen-antibody. The combination of these biomimetic materials with electrochemical techniques has allowed the development of advanced sensing devices, which significantly improve the performance of bare or catalyst-modified sensors, being able to unleash new applications. However, despite the high selectivity that MIPs exhibit, those can still show some cross-response towards other compounds, especially with chemically analogous (bio)molecules. Thus, the combination of MIPs with chemometric methods opens the room for the development of what could be considered a new type of electronic tongues, i.e. sensor array systems, based on its usage. In this direction, this review provides an overview of the more common synthetic approaches, as well as the strategies that can be used to achieve the integration of MIPs and electrochemical sensors, followed by some recent examples over different areas in order to illustrate the potential of such combination in very diverse applications.

This paper reports the development of three peptide modified sensors in which glutathione (GSH) and its fragments Cys-Gly and γ-Glu-Cys were immobilized respectively through aryl diazonium electrochemical grafting onto the surface of graphite-epoxy composite electrodes (GEC), and used for the simultaneous determination of Cd(II), Pb(II) and Zn(II). The concentration interval ranged from 0.1 to 1.5 μmol L(-1) for each metal, and the technique used was differential pulse adsorptive stripping voltammetry. This study aimed to the comparison of the information provided by one single modified electrode at both fixed and multiple pH values (pH 6.8, 7.5 and 8.2) for the simultaneous determination of the three metals, with those supplied by the three-sensor array at multiple pH values. For the processing of the voltammograms, the fast Fourier transform was selected as the preprocessing tool for data compression coupled with an artificial neural network for the modeling of the obtained responses.

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