Voltammetric electronic tongue to identify Brett character in wines. On-site quantification of its ethylphenol metabolites

Andreu González-Calabuig, Manel del Valle

Research output: Contribution to journalArticleResearchpeer-review

13 Citations (Scopus)

Abstract

© 2017 Elsevier B.V. This work reports the applicability of a voltammetric sensor array able to evaluate the content of the metabolites of the Brett defect: 4-ethylphenol, 4-ethylguaiacol and 4-ethylcatechol in spiked wine samples using the electronic tongue (ET) principles. The ET used cyclic voltammetry signals, obtained from an array of six graphite epoxy modified composite electrodes; these were compressed using Discrete Wavelet transform while chemometric tools, among these artificial neural networks (ANNs), were employed to build the quantitative prediction model. In this manner, a set of standards based on a modified full factorial design and ranging from 0 to 25 mg L−1 on each phenol, was prepared to build the model; afterwards, the model was validated with an external test set. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.02 and 0.05, for the training and test subsets respectively, and correlation coefficients better than 0.958.
Original languageEnglish
Pages (from-to)70-74
JournalTalanta
Volume179
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • Artificial neural networks
  • Brettanomyces defect
  • Electronic tongue
  • Phenolic defects
  • Wine

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