Evaluation of classical and three-way multivariate calibration procedures in kinetic-spectrophotometric analysis

Abstract

The bidimensional multivariate regression procedures: multiple linear regression (MLR), principal component regression (PCR), partial least squares regression (PLS) and continuum regression (CR), and several N-way methods such as N-way PLS (nPLS) and parallel factor analysis (PARAFAC) are tested as calibration methods for the kinetic-spectrophotometric determination of ternary mixtures in a pseudo first-order kinetic system. The different calibration procedures were first applied to computer simulated kinetic-spectrophotometric data where the effect of spectral overlap and the differences in the kinetic constants were evaluated at a low level of experimental noise. Later they were applied to the stopped-flow kinetic-spectrophotometric simultaneous resolution of Co(II), Ni(II) and Ga(III) using 4-(2-pyridylazo)resorcinol (PAR) as a chromogenic reagent. Accurate estimations of concentrations with relative standard errors of prediction of about 8% were obtained even though a high degree of spectral overlap and similar rate constants were present. The study of the influence of experimental noise on the 3-component system justifies the difference between the simulations and the experimental results for the different calibration procedures. PARAFAC and MLR did not allow the resolution of the proposed 3-component system. CR provided slightly better results than those obtained by PLS, PCR and nPLS.