偏最小二乘回归
化学计量学
高效液相色谱法
主成分分析
线性判别分析
色谱法
化学
模式识别(心理学)
人工智能
数学
分析物
计算机科学
统计
作者
Jiayin Diao,Xu Cheng,Huaping Zheng,Siyi He,Shumei Wang
出处
期刊:Planta Medica
[Thieme Medical Publishers (Germany)]
日期:2018-06-21
卷期号:84 (17): 1280-1291
被引量:10
摘要
Viticis Fructus is a traditional Chinese herbal drug processed by various methods to achieve different clinical purposes. Thermal treatment potentially alters chemical composition, which may impact on effectiveness and toxicity. In order to interpret the constituent discrepancies of raw versus processed (stir-fried) Viticis Fructus, a multivariate detection method (NIR, HPLC, and UPLC-MS) based on metabonomics and chemometrics was developed. Firstly, synergy interval partial least squares and partial least squares-discriminant analysis were employed to screen the distinctive wavebands (4319 - 5459 cm-1) based on preprocessed near-infrared spectra. Then, HPLC with principal component analysis was performed to characterize the distinction. Subsequently, a total of 49 compounds were identified by UPLC-MS, among which 42 compounds were eventually characterized as having a significant change during processing via the semiquantitative volcano plot analysis. Moreover, based on the partial least squares-discriminant analysis, 16 compounds were chosen as characteristic markers that could be in close correlation with the discriminatory near-infrared wavebands. Together, all of these characterization techniques effectively discriminated raw and processed products of Viticis Fructus. In general, our work provides an integrated way of classifying Viticis Fructus, and a strategy to explore discriminatory chemical markers for other traditional Chinese herbs, thus ensuring safety and efficacy for consumers.
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