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
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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