Interpretable AI-driven multidimensional chemical fingerprints for geographical authentication of Euryales Semen
文献类型： 外文期刊
作者： Yu, Daixin 1 ; Qu, Cheng 1 ; Nie, Jing 2 ; Wen, Pei 1 ; Zhao, Yuyang 3 ; Dai, Caiyan 4 ; Yan, Hui 1 ; Yuan, Yuwei 2 ; Wu, Qinan 1 ;
作者机构： 1.Nanjing Univ Chinese Med, Jiangsu Collaborat Innovat Ctr Chinese Med Resourc, Nanjing 210023, Peoples R China
2.Zhejiang Acad Agr Sci, Inst Agroprod Safety & Nutr, Key Lab Informat Traceabil Agr Prod, Minist Agr & Rural Affairs China, Hangzhou 310021, Peoples R China
3.China Acad Chinese Med Sci, Natl Resource Ctr Chinese Mat Med, State Key Lab Qual Ensurance & Sustainable Use Dao, Beijing 100700, Peoples R China
4.Nanjing Univ Chinese Med, Jiangsu Prov Engn Res Ctr TCM Intelligence Hlth Se, Sch Artificial Intelligence & Informat Technol, Nanjing 210023, Peoples R China
期刊名称：NPJ SCIENCE OF FOOD （ 影响因子：7.8； 五年影响因子：7.0 ）
ISSN：
年卷期： 2025 年 9 卷 1 期
页码：
收录情况： SCI
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.
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