Influence and correction of temperature perturbations on NIR spectra during the monitoring of a polymorph conversion process prior to self-modelling mixture analysis.

The influence of temperature variations on the rank of a NIR dataset, has been investigated by comparing the results of principal component analysis (PCA) and evolving factor analysis (EFA), applied to two datasets measured at constant temperature and varying temperature. After temperature correction, the concentration profiles and spectra were obtained with PCA, SIMPLISMA and the orthogonal projection approach (OPA). The same resolution methods were used on the dataset measured at constant temperature.