Interpretation of Voltammetric Data by Neural Networks for Simultaneous Determination of Glucose, Fructose, and Ascorbic Acid

This work describes the use of neural networks (NNs) for interpreting voltammetric data, i.e., current-voltage spectra that obtained from the electrochemical reaction of analyte species at a gold electrode. Current-voltage spectra of glucose, fructose and ascorbic acid in mixtures obtained from dual-pulse staircase voltammetry (DPSV) was in the form of the mixed responses contain characteristics of the individual analytes approximately in proportion to their concentration. Extraction of individual analyte concentration from combined data was subsequently achieved using NNs. The combination of DPSV and NNs opens a possibility for simultaneous determination of mixtures of the species for fruit juices quality monitoring.