化学计量学
主成分分析
色谱法
化学
根(腹足类)
偏最小二乘回归
近红外光谱
支持向量机
模式识别(心理学)
人工智能
计算机科学
传统医学
机器学习
植物
生物
医学
神经科学
作者
Le Wang,Xiuhuan Wang,Xiaoyun Liu,Yu Wang,Xueyang Ren,Ying Dong,Ruolan Song,Jiamu Ma,Qiqi Fan,Jing Wei,Axiang Yu,Lanzhen Zhang,Gaimei She
标识
DOI:10.1016/j.saa.2021.119626
摘要
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.
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