An integrated chemical characterization based on FT-NIR, and GC-MS for the comparative metabolite profiling of 3 species of the genus Amomum

文献类型： 外文期刊

第一作者： He, Gang

作者： He, Gang;Yang, Shao-bing;Wang, Yuan-zhong;He, Gang

作者机构：

关键词： Genus Amomum; Quality markers; Identification research; Network pharmacology; Deep learning

期刊名称：ANALYTICA CHIMICA ACTA （ 影响因子：6.2； 五年影响因子：5.9 ）

ISSN： 0003-2670

年卷期： 2023 年 1280 卷

页码：

收录情况： SCI

摘要： Background: The fruits and seeds of genus Amomum are well-known as medicinal plants and edible spices, and are used in countries such as China, India and Vietnam to treat malaria, gastrointestinal disorders and indigestion. The morphological differences between different species are relatively small, and technical characterization and identification techniques are needed.Results: Fourier transform near infrared spectroscopy (FT-NIR) and gas chromatography-mass spectrometry (GC MS), combined with principal component analysis and two-dimensional correlation analysis were used to characterize the chemical differences of Amomum tsaoko, Amomum koenigii, and Amomum paratsaoko. The targets and pathways for the treatment of diabetes mellitus in three species were predicted using network pharmacology and screened for the corresponding pharmacodynamic components as potential quality markers. The results of "component-target-pathway" network showed that (+)-Nerolidol, 2-Nonanol, alpha-Terpineol, alpha-Pinene, 2-Nona none had high degree values and may be the main active components. Partial least squares-discriminant analysis (PLS-DA) was further used to select for differential metabolites and was identified as a potential quality marker, 11 in total. PLS-DA and residual network (ResNet) classification models were developed for the identification of 3 species of the genus Amomum, ResNet model is more suitable for the identification study of large volume samples. Significance: This study characterizes the differences between the three species in a visual way and also provides a reliable technique for their identification, while demonstrating the ability of FT-NIR spectroscopy for fast, easy and accurate species identification. The results of this study lay the foundation for quality evaluation studies of genus Amomum and provide new ideas for the development of new drugs for the treatment of diabetes mellitus.

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