Abstract
The capacity of chemometric multivariate calibration methods, partial least square (PLS) and principal component regression (PCR), to extract quantitative analytical information from overlapping peaks in anodic stripping voltammetry is illustrated in the simultaneous analysis of synthetic mixtures containing Pb(II), In(III), Cd(II), and Tl(I). The influence of raw and first derivative data in the predictive ability of the calibration models was discussed and the results obtained in the analytical performance of synthetic mixtures by PLS and PCR were compared. The analytical results show no observable differences between the two methods and the utilization of derivative data did not improve the prediction step.
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