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Comprehensive multi-component analysis for authentication and differentiation of 6 Dendrobium species by 2D NMR-based metabolomic profiling

石斛 代谢组学 计算生物学 主成分分析 偏最小二乘回归 线性判别分析 传统医学 生物 化学 植物 计算机科学 生物信息学 人工智能 医学 机器学习
作者
Xiu Gu,Shu Zhu,Huan Du,Caihong Bai,Xiaohui Duan,Yiming Li,Kaifeng Hu
出处
期刊:Microchemical Journal [Elsevier]
卷期号:176: 107225-107225 被引量:10
标识
DOI:10.1016/j.microc.2022.107225
摘要

Discrimination of the multiple botanical origins of herbal medicines is important to appropriately control their qualities and comprehensively understand their therapeutic effects. In our study, the chemical profiling of 6 different botanical origins of Dendrobii herba was analyzed using 2D 1H–13C HSQC. High-throughput data processing and analysis methods were developed and applied to detect and quantitatively characterize the spectral features of the 6 different Dendrobium species. Principal components analysis (PCA) and hierarchical cluster analysis (HCA) analyses of these spectral features showed a clear distinction among different Dendrobium species. Characteristic metabolite markers of each of the 6 Dendrobium species were identified by integrating the pairwise partial least-squares discriminant analysis (PLS-DA) and univariate hypothesis test. Besides, 8 major common metabolites were identified and found to have comparable content in all 6 Dendrobium species. Our results allow species authentication and differentiation of Dendrobium. It may also represent a universal protocol for authentication and quality assessment of medicinal herbs.
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