MULTIVARIATE CALIBRATION OF INFRARED-SPECTRA FOR QUANTITATIVE-ANALYSIS USING DESIGNED EXPERIMENTS

The principal component regression (PCR) and partial least-squares (PLS) methods are used to calibrate and validate models for quantitative prediction of the composition of mixtures from FT-IR spectra. An experimental system of two- and three-component mixtures of xylene isomers was sampled with the use of statistical experimental designs. For two-component mixtures, the prediction error of independent validation samples decreased with increasing numbers of design points in the calibration. Four design points were needed to achieve a prediction accuracy of 0. 0013 weight fraction.