Simultaneous characterization of multiple properties of solid and liquid phases in crystallization processes using NIR

Near infrared spectroscopy (NIR) spectra contain rich information about both solids and liquids, giving the possibility of using the same instrument for multiple property characterization. In this study, transflectance NIR calibration data was used to develop predictive models through combining genetic algorithm (GA) for wavelength selection and support vector machine (SVM) for mode building. NIR is thus successfully applied to monitoring seeded and unseeded cooling crystallization processes of l-glutamic acid.