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

Journal: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Published Date:

Abstract

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.

Authors

  • Le Wang
    Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • Xiuhuan Wang
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Xiaoyun Liu
    Department of General Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Yu Wang
    Clinical and Technical Support, Philips Healthcare, Shanghai, China.
  • Xueyang Ren
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Ying Dong
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Ruolan Song
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Jiamu Ma
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Qiqi Fan
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Jing Wei
    School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong, China.
  • AXiang Yu
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
  • Lanzhen Zhang
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China. Electronic address: zhanglanzhen01@126.com.
  • Gaimei She
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Fangshan District, Beijing, China. Electronic address: shegaimei@126.com.