Rapid and comprehensive quality assessment of Bupleuri Radix through near-infrared spectroscopy combined with chemometrics

Abstract

The quality of popular Chinese herbal medicine Bupleuri Radix (BR) is essential to its curative effect and economic value and has become an issue for customers and dealers. Traditional analytical techniques for evaluating BR quality are generally time-consuming, laborious, and costly. In this regard, a rapid and efficient method is warranted to supplement existing approaches. This study developed a comprehensive strategy based on near-infrared (NIR) spectroscopy and chemometrics for quality assessment of BR. From qualitative perspective, BR was identified according to geographical origin by using principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), and support vector machine (SVM). Saikosaponin A, saikosaponin D, polysaccharides, and total flavonoids, which are vital quality indicators of BR, were quantified through NIR spectroscopy and calibration models. Herein, a CARS-SVM model was constructed based on competitive adaptive reweighted sampling and SVM algorithm, and its prediction performance was compared with other calibration models (Full-PLS, CARS-PLS, and Full-SVM). Results indicated that the SVM model performed better than PCA and PLS-DA and had correct recognition rates of 97.37% and 94.44% in the calibration and prediction sets, respectively. The contents of saikosaponin A, saikosaponin D, polysaccharides, and total flavonoids were satisfactorily predicted through the CARS-SVM model. The coefficient of determination (Rp2) and root mean square error in the independent test sets (RMSEP) were 0.9135 and 0.0837%, 0.8132 and 0.1695%, 0.8810 and 0.7165%, and 0.7471 and 0.1766% for saikosaponin A, saikosaponin D, polysaccharides, and total flavonoids, respectively. The superiority of CARS-SVM compared with the other quantitative models demonstrated that CARS wavelength selection method and nonlinear SVM regression tool significantly improved the model performance. Overall the results demonstrated the potential of NIR spectroscopy and appropriate chemometrics for rapid quality evaluation of BR. The developed comprehensive quality assessment strategy could supplement existing methods for analysis of BR and is expected to provide reference for quality evaluation and control of other Chinese herbal medicines.