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利用高效薄层色谱颜色标度指纹成像和气相色谱-质谱联用技术对东南亚胡椒科植物进行化学分类学研究

Chemotaxonomy of Southeast Asian (Piperaceae) Using High-Performance Thin-Layer Chromatography Colour Scale Fingerprint Imaging and Gas Chromatography-Mass Spectrometry.

作者信息

Banchong Yutthana, Leepasert Theerachart, Jarupund Pakawat, Hodkinson Trevor R, Boylan Fabio, Suwanphakdee Chalermpol

机构信息

Department of Botany, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.

Department of Chemistry, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.

出版信息

Plants (Basel). 2024 Sep 30;13(19):2751. doi: 10.3390/plants13192751.

Abstract

The morphological characters of Southeast Asia's indigenous species are very similar, especially in their flower structures. The flowers are simple, hermaphrodite and lack a perianth. Therefore, many species are hard to distinguish using morphological characters alone. Here, we apply chemometric data for species identification and classification, gathered using multiwavelength detection combined with the colour scale High-Performance Thin-Layer Chromatography (HPTLC) fingerprinting procedure and chemical compounds determined by Gas Chromatography-Mass Spectrometry (GC-MS). Fourteen taxa were investigated using hexane, ethyl acetate and ethanol solvent extractions. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used with the colour scale fingerprints to classify the species. The PCA and HCA using the chromatogram profile from hexane divided the taxa into six groups compared to the profile from ethyl acetate and ethanol, which each detected seven groups. The chromatogram from the combined dataset of all three solvents can differentiate all the species. The GC-MS data detected a total of 40 compounds from the hexane extract, and these differed among species. This approach based on HPTLC fingerprinting and GC-MS analysis can therefore be used as a tool for authentication and identification studies of species.

摘要

东南亚本土物种的形态特征非常相似,尤其是在花的结构方面。这些花很简单,是两性花且没有花被。因此,仅使用形态特征很难区分许多物种。在这里,我们应用化学计量数据进行物种鉴定和分类,这些数据是通过多波长检测结合彩色高效薄层色谱(HPTLC)指纹图谱程序收集的,以及通过气相色谱 - 质谱联用(GC - MS)测定的化合物。使用己烷、乙酸乙酯和乙醇溶剂提取物对14个分类单元进行了研究。主成分分析(PCA)和层次聚类分析(HCA)与彩色指纹图谱一起用于对物种进行分类。与乙酸乙酯和乙醇的图谱相比,使用己烷色谱图的PCA和HCA将分类单元分为六组,而乙酸乙酯和乙醇的图谱每组都检测到七组。来自所有三种溶剂组合数据集的色谱图可以区分所有物种。GC - MS数据从己烷提取物中总共检测到40种化合物,并且这些化合物在不同物种之间存在差异。因此,这种基于HPTLC指纹图谱和GC - MS分析的方法可以用作物种鉴定和识别研究的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7123/11478959/e7322bfd5a23/plants-13-02751-g001.jpg

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