Wavelet neural networks to resolve the overlapping signal in the voltammetric determination of phenolic compounds.
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 2.5mM) 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.
Gutiérrez
Juan Manuel
JM
Bioelectronics Section, Department of Electrical Engineering, CINVESTAV, 07360 Mexico DF, Mexico.
Gutés
Albert
A
Céspedes
Francisco
F
del Valle
Manuel
M
Muñoz
Roberto
R
D002138:Calibration; D004563:Electrochemistry / Q000379:methods* / Q000592:standards; D016571:Neural Networks, Computer; D010084:Oxidation-Reduction; D010636:Phenols / Q000032:analysis*
D010636:Phenols