Special Issue Paper

Analytical and Bioanalytical Chemistry

, Volume 382, Issue 2, pp 471-476

First online:

Simultaneous determination of phenolic compounds by means of an automated voltammetric “electronic tongue”

  • A. GutésAffiliated withGrup de Sensors i Biosensors, Universitat Autònoma de Barcelona
  • , A. B. IbáñezAffiliated withGrup de Sensors i Biosensors, Escola Universitària Politècnica del Medi Ambient, Universitat Autònoma de Barcelona
  • , F. CéspedesAffiliated withGrup de Sensors i Biosensors, Escola Universitària Politècnica del Medi Ambient, Universitat Autònoma de Barcelona
  • , Salvador AlegretAffiliated withGrup de Sensors i Biosensors, Universitat Autònoma de Barcelona
  • , M. del ValleAffiliated withGrup de Sensors i Biosensors, Universitat Autònoma de Barcelona Email author 

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Abstract

This contribution describes the simultaneous determination of three phenolic compounds, o-cresol, p-chlorophenol and 4-chloro-3-methylphenol, using direct oxidation and amperometric detection coupled by signal deconvolution, accomplished via chemometric methods. Direct oxidation of phenolic compounds is performed at the surface of an epoxy-graphite transducer, by linear scan voltammetry. Due to strong signal overlapping, artificial neural networks (ANNs) were used during data treatment, in a combination of chemometrics and electrochemical sensors known as an “electronic tongue”. To calibrate this system properly, a total of 80 mixed samples were prepared automatically by employing a sequential injection analysis (SIA) system designed to automatically generate the information needed to train the network. The phenolic compound concentration varied from 1 to 70 μM for o-cresol, from 0.5 μM to 140 μM for p-chlorophenol and from 1 μM to 100 μM for 4-chloro-3-methylphenol. A good prediction capability was obtained, with correlation coefficients >0.964 when the obtained values were compared with those expected for a set of 24 external test samples not used for training. The results presented here indicate that this technique is a simple and robust analytical method of environmental interest.

Keywords

Phenols Voltammetry Artificial neural networks “Electronic tongue”