Please login first
Comparative study of two Electronic Tongues for the detection of ethylphenols by MIP-based and chemically modified voltammetric sensors
, , *
1  Sensors and Biosensors Group, Chemistry Department, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain

Published: 14 November 2020 by MDPI in 7th International Electronic Conference on Sensors and Applications session Posters

This work reports the comparison of two different Electronic Tongues (ETs) approaches for the detection and quantification of the main chemicals responsible of Brett character in wines, namely 4-Ethylphenol (4-EP), 4-Ethylguaiacol (4-EG) and 4-Ethylcatechol (4-EC).

On the one hand, a sensor array based on Molecularly Imprinted Polymers (MIPs) was designed to be individually selective to each of the analytes which give the Brett character, i.e., 4-EP, 4-EG and 4-EC. These polymers were designed and synthesised using each of the analytes, respectively, as template molecules. Once obtained, these materials were characterised and integrated onto the Graphite Epoxy Composites sensors (GECs). Then, the readout was done by Differential Pulse Voltammetry (DPV), optimizing previously the measurement conditions. On the other hand, the voltammetric ET based on a chemically modified sensor array, was formed by 5 modified-GECs and 1 GEC, as bare electrode. The different sensors were modified with Cu nanoparticles, WO3 nanoparticles, Co phtalocyanine, Bi2O3 nanoparticles and polypyrrole. This choice was intended as to maximize the differences in the obtained voltammograms for the different sensors using cyclic voltammetry (CV) as electrochemical technique.

Once the sensor arrays were developed Principal Component Analysis (PCAs) were done in order to discriminate the phenols among other interferent species. Finally, Artificial Neural Networks (ANNs) were used for the quantification of these analytes in aqueous samples in the case of the MIPs-based sensor array and in wine samples in the case of modified sensor array.

Keywords: Molecularly Imprinted Polymers; Brett Character; Artificial Neural Networks; Electronic Tongues; Wine