CHARACTERIZATION OF THE SOURCES OF VARIATION AFFECTING NEAR-INFRARED SPECTROSCOPY USING CHEMOMETRIC METHODS

A rapid assessment of product quality can often be made using a combin ation of near-infrared spectroscopy (NIR) and multivariate calibration . The robustness of such a method is determined by the sensitivity of the multivariate calibration model to variations in the spectral data, An approach is described that uses a combination of experimental desi gn methodology and principal component analysis to identify the main s ources of variation in the spectra and to estimate their influence on the quantitative predictions. This is accomplished by comparing variat ions in a set of measured, replicate spectra to spectra with simulated variations. The approach was applied to the hydroxyl number determina tion of polyols by NIR spectroscopy and partial least-squares calibrat ion. The results indicated that the most significant sources of variat ion were due to a variable cell path length and a variable curved back ground. Correction for these errors resulted in a 58% reduction in the standard deviation of the hydroxyl number predictions, indicating tha t a substantial improvement in the method precision is possible.