Application of near Infrared Spectroscopy Combined with Competitive Adaptive Reweighted Sampling Partial Least Squares for on-line Monitoring of the Concentration Process of Wangbi Tablets

As a rapid and accurate technique, near infrared (NIR) spectroscopy has been widely used in process monitoring to improve efficiency and ensure quality consistency. In the present work, the application of NIR spectroscopy for on-line quantitative monitoring of the concentration process of Wangbi tablets was investigated. Partial least squares regression (PLSR) models based on the full-range spectra or the key wavelengths selected by the competitive adaptive reweighted sampling (CARS) method were established. The accuracy of the CARS-PLSR method was greater than that of full-spectrum PLSR for three quality parameters (soluble solid contents, paeoniflorin and icariin). For the prediction set samples using the CARS-PLSR models the coefficients of determination ( r 2 ) and root mean square error [ RMSEP (%)] were 0.97 and 1.29 for soluble solid contents, 0.93 and 0.014 for paeoniflorin and 0.85 and 0.009 for icariin, respectively. Overall the results indicated that NIR spectroscopy coupled with CARS-PLSR calibration is a reliable and non-destructive alternative method for on-line monitoring of the concentration process of Wangbi tablets on an industrial scale.