Real-time process monitoring of critical quality attributes of white sugar crystals in an agitator dryer using near-infrared spectroscopy for automatic manufacturing

To quantitatively monitor moisture content (MC) and particle size (PS) as the main critical quality attributes (CQAs) of white sugar crystals, samples were placed in a small agitator dryer, and near-infrared (NIR) spectroscopy was performed continuously in real-time using a diffuse reflectance fiber-optic probe. The MCs of the granules were calculated as weight loss after drying statically at 80 degrees C, and the PS and its distribution were determined using the sieving method. The best-fitted calibration models for predicting MC and PS were obtained using the partial least squares regression method for the NIR datasets. All the fitted models exhibited good linearity, with a correlation coefficient above 0.98. The MC of the samples decreased linearly with drying time, reaching an equilibrium MC of less than 0.5 wt% at 140 s. The NIR method can be useful for real-time evaluation of the MC and PS of white sugar crystals during continuous drying.