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<p>Euryales Semen (ES, <i>Euryale ferox</i> Salisb.) is a valuable aquatic food in Asia. Its quality and price depend on its geographical origins. To ensure the authenticity of ES, a tracing strategy using stable isotopes, elements, and starch composition with interpretable algorithms was successfully developed. Results indicated that ES from different regions exhibited different chemical fingerprinting profiles. Tree-based intelligent algorithms were introduced for classification, and light gradient boosting machine (LightGBM) achieved the highest accuracy of 97.67%. The SHapley Additive exPlanation (SHAP) interpreted the LightGBM output for feature impact. Notably, the top 10 significant variables, encompassing Na, V, Ba, Sb, Cu, Ti, Mn, %N, amylose, and ratio of amylose to amylopectin (SHAP value &gt;1.0), were selected as the key factors. Moreover, environmental factors were found to be significantly related to these key variables (<i>p</i> &lt; 0.05). Overall, this study offers an effective strategy for the geographical origin traceability of ES or other aquatic crops.</p>

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Interpretable AI-driven multidimensional chemical fingerprints for geographical authentication of Euryales Semen

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月9日

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  • Daixin Yu,
  • Cheng Qu,
  • Jing Nie,
  • Pei Wen,
  • Yuyang Zhao,
  • Caiyan Dai,
  • Hui Yan,
  • Yuwei Yuan,
  • Qinan Wu

摘要

Euryales Semen (ES, Euryale ferox Salisb.) is a valuable aquatic food in Asia. Its quality and price depend on its geographical origins. To ensure the authenticity of ES, a tracing strategy using stable isotopes, elements, and starch composition with interpretable algorithms was successfully developed. Results indicated that ES from different regions exhibited different chemical fingerprinting profiles. Tree-based intelligent algorithms were introduced for classification, and light gradient boosting machine (LightGBM) achieved the highest accuracy of 97.67%. The SHapley Additive exPlanation (SHAP) interpreted the LightGBM output for feature impact. Notably, the top 10 significant variables, encompassing Na, V, Ba, Sb, Cu, Ti, Mn, %N, amylose, and ratio of amylose to amylopectin (SHAP value >1.0), were selected as the key factors. Moreover, environmental factors were found to be significantly related to these key variables (p < 0.05). Overall, this study offers an effective strategy for the geographical origin traceability of ES or other aquatic crops.