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Voltammetric Electronic Tongue for the Qualitative Analysis of Beers
Author(s) -
Cetó Xavier,
Gutiérrez Juan Manuel,
Mimendia Aitor,
Céspedes Francisco,
del Valle Manel
Publication year - 2013
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.201200672
Subject(s) - electronic tongue , linear discriminant analysis , principal component analysis , partial least squares regression , artificial intelligence , pattern recognition (psychology) , cluster analysis , chromatography , analytical chemistry (journal) , mathematics , computer science , chemistry , statistics , food science , taste
This paper deals with the application of a voltammetric electronic tongue (ET) towards beers classification. For this purpose, samples were analyzed using cyclic voltammetry without performing any sample pretreatment, albeit its dilution with distilled water. The voltammetric signals were first preprocessed employing Fast Fourier Transform (FFT). Then, using the obtained coefficients, responses were evaluated using three different clustering techniques: Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS‐DA) and Linear Discriminant Analysis (LDA). In this case, the ET has demonstrated a good capability to correctly discriminate and classify the different beer samples according to its type (Lager, Stout and IPA) and manufacture process (commercial and craft).