Application of multiway-variate calibration to simultaneous voltammetric determination of three catecholamines.

Abstract

Three structurally similar catecholamines, adrenaline (AA), dopamine (DA) and noradrenaline (NA), which are neurotransmitters well known for their treatment of neural disorders and many other diseases, were investigated at a glassy carbon electrode (GCE) with the use of differential pulse stripping voltammetry (DPSV). The aim was to develop a simple, rapid and cost effective method of simultaneous analysis of these three substances in typical samples such as human urine. Each analyte showed typical reversible redox behaviour with the use of cyclic voltammetry in aqueous medium in the pH range of 4.0-7.9, and composite voltammograms of the three analytes were found to consist of three significantly overlapping peaks corresponding to the three individual substances. Thus, two- and three-way multi-variate data analysis methods were investigated. These included unfolding methods such as-partial least squares (UPLS), principal component regression (UPCR) and radial basis function-artificial neural networks (URBF-ANN), as well as trilinear models, such as parallel factor analysis (PARAFAC) and N-way PLS (NPLS). The results were compared with those obtained from two-way voltammetric data matrix with the use of conventional models, PLS, PCR and RBF-ANN. It was found that most of the three-way models, such as PARAFAC and UPLS, performed somewhat better than others on the basis of the %RPET (5.6∼5.9) and mean %Recovery (94∼102). The proposed methods were then applied for the determination of human urine samples spiked with the three catecholamines, and the results were satisfactory.