Simultaneous enzymatic spectrophotometric determination of ethanol and methanol by use of artificial neural networks for calibration

Marcelo Blanco, Jordi Coello, Hortensia Iturriaga, Santiago Maspoch, Marta Porcel

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27 Citations (Scopus)

Abstract

Binary mixtures of ethanol-methanol were resolved by use of an enzymatic spectrophotometric method using artificial neural network (ANN) methodology for multivariate calibration. The chemical system involves two coupled reactions, viz. the oxidation of the primary alcohols to the corresponding aldehydes in the presence of alcohol oxidase and the oxidation of p-phenylenediamine to Bandrowski's base by hydrogen peroxide, catalysed by the previously formed aldehydes. The high complexity of the system studied entails the use of this non-linear calibration methodology, which provides significantly improved results relative to a multi-variate bilinear calibration, principal component regression (PCR), which was used for comparison. The optimized ANN allows the quantitation of both mixture components in ethanol to methanol mole ratios from 20:1 to 400:1, with relative standard errors of prediction in the region of 5% for both analytes. Copyright (C) 1999 Elsevier Science B.V.
Original languageEnglish
Pages (from-to)83-92
JournalAnalytica Chimica Acta
Volume398
Issue number1
DOIs
Publication statusPublished - 11 Oct 1999

Keywords

  • Artificial neural networks
  • Enzymatic methods
  • Kinetic analysis
  • Simultaneous determination
  • Spectrophotometry

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