The application of an Electronic Tongue for the classification of cava samples based on their different ageing times is reported. As such, voltammetric responses were obtained from an array of six bulk-modified graphite-epoxy electrodes, which exhibited marked mix-responses towards the different samples. Obtained responses were then preprocessed employing FFT and the resulting coefficients were input to a LDA model which allowed the classification of the samples according to its vintage time. Besides, a quantitative model employing ANNs was built for the prediction of the total amount of sugar present in the samples, a parameter also used to classify cava samples. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
|Publication status||Published - 1 Jan 2014|
- Artificial neural network
- Cava wine
- Electronic tongue
- Linear discriminant analysis