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<p><i>Panax vietnamensis</i>, indigenous to Vietnam and southern China, is classified into three subspecies: <i>Panax vietnamensis</i> Ha et Grushv. (PVV), <i>Panax vietnamensis</i> var. <i>fuscidiscus</i> (PVF), and <i>Panax vietnamensis</i> var. <i>langbianensis</i> (PVL). A method to distinguish these varieties in their intact form is absent, which poses a possible risk of misclassification. Here, we aimed to devise a plant metabolite-based discrimination algorithm for the three varieties, without causing significant damage to individual plants. A multivariate analysis on mass spectral data of PVV, PVF, and PVL revealed that a peak at <i>m/z</i> 426, which was subsequently identified as an indole alkaloid glycoside, was exclusive to PVF and therefore clearly distinguished PVF from PVV and PVL. Additionally, global metabolic profiling was conducted to elucidate the discrimination markers between PVV and PVL, and lysophospholipids and hydroxy fatty acids were selected as potential discrimination markers. The performance of these markers was validated by cross-validation using machine learning algorithm.</p>

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Development of a leaf metabolite-based intact sample distinguishing algorithm for the three varieties of Panax Vietnamensis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月7日

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  • Ranran Cheng,
  • Young Cheol Yoon,
  • Cheol Woon Jung,
  • Tae Ha Kim,
  • Qiang Wang,
  • Woohyeon Cho,
  • Tae-Jin Yang,
  • Thi Hong Van Le,
  • Chan Jae Cho,
  • Jae Hyun Kim,
  • Gyu Hwan Hyun,
  • Jeong Hill Park,
  • Sung Won Kwon,
  • Sun Jo Kim

摘要

Panax vietnamensis, indigenous to Vietnam and southern China, is classified into three subspecies: Panax vietnamensis Ha et Grushv. (PVV), Panax vietnamensis var. fuscidiscus (PVF), and Panax vietnamensis var. langbianensis (PVL). A method to distinguish these varieties in their intact form is absent, which poses a possible risk of misclassification. Here, we aimed to devise a plant metabolite-based discrimination algorithm for the three varieties, without causing significant damage to individual plants. A multivariate analysis on mass spectral data of PVV, PVF, and PVL revealed that a peak at m/z 426, which was subsequently identified as an indole alkaloid glycoside, was exclusive to PVF and therefore clearly distinguished PVF from PVV and PVL. Additionally, global metabolic profiling was conducted to elucidate the discrimination markers between PVV and PVL, and lysophospholipids and hydroxy fatty acids were selected as potential discrimination markers. The performance of these markers was validated by cross-validation using machine learning algorithm.