Fast discrimination and quantification analysis of Curcumae Radix from four botanical origins using NIR spectroscopy coupled with chemometrics tools

Curcumae Radix (Yujin) is a multi-origin herbal medicine with excellent clinical efficacy. For fast discrimination and quantification analysis of Yujin from four botanical origins (Guiyujin, Huangyujin, Lvyujin and Wenyujin), near infrared (NIR) spectroscopy combined with chemometrics tools was employed in this study. Based on NIR data, principal component analysis (PCA) could only realize the separation between Guiyujin and Wenyujin samples, and the partial least squares-discrimination analysis (PLS-DA), support vector machine (SVM) and k-nearest neighbors (KNN) models achieved the complete discrimination of the four species of Yujin with 100% accuracy. Moreover, the method for the simultaneous determination of six bioactive compounds in Yujin was developed by HPLC. Germacrone, curdione and curcumenol could be found in all samples, and curcumin, demethoxycurcumin and bisdemethoxycurcumin were only observed in Huangyujin samples. Then, the support vector machine regression (SVMR) model for the prediction of germacrone content was successfully constructed. And the coefficients of determination were 0.88 and 0.89 for calibration and validation sets, respectively. The present work proposes a quick, economic and reliable method for the discrimination of Yujin from four botanical origins and the prediction of germacrone content, which will contribute to its quality control researches. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

NIR spectroscopy combined with chemometrics tools was used for fast discrimination and quantification of Curcumae Radix from four botanical origins. HPLC was employed to develop a method for simultaneous determination of six bioactive compounds in Curcumae Radix. A support vector machine regression (SVMR) model successfully predicted the content of germacrone.