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 2400mgL -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). © 2012 Elsevier B.V.
|Journal||Analytica Chimica Acta|
|Publication status||Published - 30 Jun 2012|
- Artificial neural network
- Electronic tongue
- Voltammetric sensors
- Wine analysis