Multivariate versus univariate calibration for nonlinear chemiluminescencedata - Application to chromium determination by luminol-hydrogen peroxide reaction

Multivariate calibration is tested as an alternative to model chromium(III) concentration versus chemiluminescence registers obtained from luminol-hyd rogen peroxide reaction. The multivariate calibration approaches included h ave been: conventional linear methods (principal component regression (PCR) and partial least squares (PLS)), nonlinear methods (nonlinear variants an d variants of locally weighted regression) and linear methods combined with variable selection performed in the original or in the transformed data (s tepwise multiple linear regression procedure). Both the direct and inverse univariate approaches have been also tested. The use of a double logarithmic transformation previous to the linear regre ssion has been also evaluated. A new double logarithmic transformation prev ious to the linear regression is proposed in order to avoid the effect of t he noise in the calibration model. Pre-processing, optimization and predict ion ability of the multivariate calibration models has been studied at nine different experimental conditions including batch and FIA measurements. Bo x-plots, PCA and cluster analysis have been employed to test the prediction ability of the different models tested. Nonlinear PCR and nonlinear PLS pr ovide the best results. Real samples have been analyzed and compared with t he reference method. The results confirm the successful use of the proposed methodology. (C) 2001 Elsevier Science B.V. All rights reserved.