期刊
JOURNAL OF SEPARATION SCIENCE
卷 44, 期 20, 页码 3810-3821出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/jssc.202100399
关键词
alkaloids; Cinnamomum; feature-based molecular networking; metabolite profiling; proanthocyanidins
资金
- Research Project of Science and Technology Commission of Shanghai Municipality [18DZ2200800]
- National Key R&D Program of China [2018YFC1707903, 2018YFC1707900, 2018YFC1707905, 2018YFC1707001]
The study utilized advanced techniques to differentiate the components of Cinnamomum cassia Bark and Cinnamomum verum bark, providing new insights for discovering quality markers and identifying unknown components in natural products.
Cinnamon was been a widely used plant in medicinal and spices for a long time and has spread all over the world. However, the differences in the components of the bark from Cinnamomum cassia and Cinnamomum verum, the two most common types of cinnamon, have not been thoroughly investigated. In the present experiment, ultra-high-performance liquid chromatography LTQ-Orbitrap Velos Pro hybrid mass spectrometer-based metabolomics coupled with chemometrics and feature-based molecular networking were employed to dramatically distinguish and annotate Cinnamomum cassia Bark and Cinnamomum verum bark. As a consequence, principal component analysis, orthogonal projection to latent structures discriminates analysis, and heat map analysis demonstrated clear discrimination between the profiles of metabolites in cinnamon. Besides, as the known compounds, proanthocyanidins (cinnamtannin B1 and procyanidin B2) and alkaloids (norboldine, norisoboldine) with variable importance in the projection scores >6, and an unknown alkaloid (formula C24H33NO6) were selected as the best markers to discriminate cinnamon. Furthermore, large numbers of proanthocyanidins and alkaloids components were identified through feature-based molecular networking for the first time. Our investigation provides new ideas for the discovery of quality markers and identification of unknown components in natural products.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据