Wavelet neural networks to resolve the overlapping signal in the voltammetric determination of phenolic compounds

Juan Manuel Gutiérrez, Albert Gutés, Francisco Céspedes, Manuel del Valle, Roberto Muñoz

Research output: Contribution to journalArticleResearchpeer-review

30 Citations (Scopus)

Abstract

Three phenolic compounds, i.e. phenol, catechol and 4-acetamidophenol, were simultaneously determined by voltammetric detection of its oxidation reaction at the surface of an epoxy-graphite transducer. Because of strong signal overlapping, Wavelet Neural Networks (WNN) were used in data treatment, in a combination of chemometrics and electrochemical sensors, already known as the electronic tongue concept. To facilitate calibration, a set of samples (concentration of each phenol ranging from 0.25 to 2.5 mM) was prepared automatically by employing a Sequential Injection System. Phenolic compounds could be resolved with good prediction ability, showing correlation coefficients greater than 0.929 when the obtained values were compared with those expected for a set of samples not employed for training. © 2008 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)373-381
JournalTalanta
Volume76
Issue number2
DOIs
Publication statusPublished - 15 Jul 2008

Keywords

  • Phenols
  • Signal resolution
  • Voltammetry
  • Wavelet neural network

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