您好，欢迎访问中国农业科学院 机构知识库！

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Combining stable isotopes and multi-elements with machine learning chemometric models to identify the geographical origins of Tetrastigma hemsleyanum Diels et Gilg

文献类型： 外文期刊

作者： Bai, Lu 1 ; Zhang, Zixuan 1 ; Li, Yalan 2 ; Zhao, Shanshan 2 ; Yang, Xiaoting 2 ; Chen, Chengqun 1 ; Zhao, Shilin 2 ; Zhang, Ping 3 ; Peng, Xin 4 ; Zhao, Yan 2 ; Liang, Kehong 1 ;

作者机构： 1.Minist Agr & Rural Affairs, Inst Food & Nutr Dev, Beijing 100081, Peoples R China

2.Chinese Acad Agr Sci, Inst Stand & Testing Technol Agroprod, Key Lab Agroprod Qual & Safety, Beijing 100081, Peoples R China

3.Griffith Univ, Biostat unit, Nathan, Australia

4.Zhejiang Chinese Med Univ, Ningbo Municipal Hosp TCM, Affiliated Hosp, Ningbo, Peoples R China

关键词： Origin traceability; Stable isotope ratio; Multi-elements analysis; Discriminant analysis; Climatic factors

期刊名称：FOOD CHEMISTRY （ 影响因子：9.8； 五年影响因子：9.7 ）

ISSN： 0308-8146

年卷期： 2025 年 469 卷

页码：

收录情况： SCI

摘要： Tetrastigma hemsleyanum Diels et Gilg (T. hemsleyanum) is an edible plant with considerable medicinal properties, the quality of which varies depending on its origin. Therefore economically motivated adulteration has emerged. So there is an urgent need to develop effective techniques for determining the origin of T. hemsleyanum. This study combined stable isotopes and multiple elements with machine learning chemometric models (SVM, RF and FNN models) for T. hemsleyanum origin traceability. The results showed that this approach successfully distinguished T. hemsleyanum form different regions with the SVM, RF and FNN models all displaying a 100 % prediction accuracy and the FNN model exhibiting superior performance. This study provides a technical and theoretical basis for research on the origin traceability of T. hemsleyanum.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：中国农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台