TY - JOUR
T1 - A voltammetric electronic tongue made of modified epoxy-graphite electrodes in the qualitative analysis of wine
AU - Gutiérrez, Juan Manuel
AU - Moreno-Barón, Laura
AU - Pividori, Maria Isabel
AU - Alegret, Salvador
AU - del Valle, Manel
PY - 2010/6/1
Y1 - 2010/6/1
N2 - First results are presented of a new voltammetric electronic tongue which employs modified epoxy-graphite electrodes. This analytical tool has been applied to qualitative wine analysis, performing the classification of wine varieties, as well as recognition of the oxygenation effect. In the same way, studies related to the detection of some defects in wine production were also assessed, such as its vinegary taste in open-air contact or the use of excess sulphite preservative. The electronic tongue was formed by five voltammetric electrodes, four of them being bulk-modified with different substances: copper and platinum nanoparticles on one side, and polyaniline and polypyrrole powder on the other. The responses were preprocessed employing Principal Component Analysis (PCA) to visualize and identify distinct episodes. The resulting PCA scores were modelled with an artificial neural network that accomplishes final prediction with the qualitative classification of wines and/or detection of defects. © Springer-Verlag 2010.
AB - First results are presented of a new voltammetric electronic tongue which employs modified epoxy-graphite electrodes. This analytical tool has been applied to qualitative wine analysis, performing the classification of wine varieties, as well as recognition of the oxygenation effect. In the same way, studies related to the detection of some defects in wine production were also assessed, such as its vinegary taste in open-air contact or the use of excess sulphite preservative. The electronic tongue was formed by five voltammetric electrodes, four of them being bulk-modified with different substances: copper and platinum nanoparticles on one side, and polyaniline and polypyrrole powder on the other. The responses were preprocessed employing Principal Component Analysis (PCA) to visualize and identify distinct episodes. The resulting PCA scores were modelled with an artificial neural network that accomplishes final prediction with the qualitative classification of wines and/or detection of defects. © Springer-Verlag 2010.
KW - Artificial neural networks
KW - Electronic tongue
KW - Principal component analysis
KW - Voltammetric sensor
KW - Wine analysis
U2 - 10.1007/s00604-010-0351-z
DO - 10.1007/s00604-010-0351-z
M3 - Article
SN - 0026-3672
VL - 169
SP - 261
EP - 268
JO - Microchimica Acta
JF - Microchimica Acta
IS - 3
ER -