Identification of 37 kinds of herbs containing oligosaccharides by combining data fusion and machine learning
文献类型：期刊论文
| 作者 | Zhang, Li-jie3,4; An, Ya-ling3; Huang, Fei4; Zhao, Wen-jie4; Song, Chun-qian3; Huang, Yu-shi3; Li, Zhen-wei3; Liu, Xiao-kang3; Yang, Yang2; Chen, Qinhua2 |
| 刊名 | JOURNAL OF FOOD COMPOSITION AND ANALYSIS
 |
| 出版日期 | 2025-12-01 |
| 卷号 | 148页码:10 |
| 关键词 | Oligosaccharide-rich herbs HPLC-DAD/ELSD Data fusion Machine learning Discrimination |
| ISSN号 | 0889-1575 |
| DOI | 10.1016/j.jfca.2025.108190 |
| 通讯作者 | Guo, De-an(daguo@simm.ac.cn) |
| 英文摘要 | Oligosaccharide-rich herbs (ORHs) predominantly belong to the category of edible plants, making them an essential component of modern health-conscious diets, with their similar appearances often leading to misuse or misidentification. This study conducted an in-depth analysis of 487 batches across 37 varieties of ORHs, aiming to address critical challenges in their identification and quality control. Innovatively, the research employed two detection techniques-evaporative light scattering detector (ELSD) and diode array detector (DAD)-in conjunction with low-level and mid-level data fusion strategies. These approaches yielded four distinct datasets, which were utilized to develop seven classification machine learning models, culminating in the construction of 28 models in total. The findings revealed that data fusion significantly enhanced model accuracy and performance, particularly the Partial Least Squares-Discriminant Analysis (PLS-DA) model constructed using mid-level data fusion, which achieved training and testing set accuracies exceeding 98.0 %, and a validation set accuracy of 100 %. This study not only provides a comprehensive comparison of identification schemes for 37 types of ORHs, but also offers valuable insights for quality control in the herbs market. |
| WOS关键词 | AUTHENTICATION ; FOOD |
| 资助项目 | National Natural Science Foundation of China[82130111] ; Sanming Project of Medicine in Shenzhen[SZZYSM202106004] ; Qi-Huang Chief Scientist Project of National Administration of Traditional Chinese Medicine (2020) Guangdong Basic and Applied Basic Research Foundation[2023A1515111180] |
| WOS研究方向 | Chemistry ; Food Science & Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001560603100001 |
| 出版者 | ACADEMIC PRESS INC ELSEVIER SCIENCE |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/321369]  |
| 专题 | 中国科学院上海药物研究所 |
| 通讯作者 | Guo, De-an |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai Res Ctr Modernizat Tradit Chinese Med, Natl Engn Res Ctr TCM Standardizat Technol, Haike Rd 501, Shanghai 201203, Peoples R China 2.Shenzhen Baoan Authent TCM Therapy Hosp, Shenzhen 518101, Peoples R China 3.Chinese Acad Sci, Zhongshan Inst Drug Discovery, Shanghai Inst Mat Med, Zhongshan 528400, Peoples R China 4.Nanjing Univ Chinese Med, Sch Chinese Mat Med, 138 Xianlin Rd, Nanjing 210023, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Li-jie,An, Ya-ling,Huang, Fei,et al. Identification of 37 kinds of herbs containing oligosaccharides by combining data fusion and machine learning[J]. JOURNAL OF FOOD COMPOSITION AND ANALYSIS,2025,148:10. |
| APA | Zhang, Li-jie.,An, Ya-ling.,Huang, Fei.,Zhao, Wen-jie.,Song, Chun-qian.,...&Guo, De-an.(2025).Identification of 37 kinds of herbs containing oligosaccharides by combining data fusion and machine learning.JOURNAL OF FOOD COMPOSITION AND ANALYSIS,148,10. |
| MLA | Zhang, Li-jie,et al."Identification of 37 kinds of herbs containing oligosaccharides by combining data fusion and machine learning".JOURNAL OF FOOD COMPOSITION AND ANALYSIS 148(2025):10. |
入库方式： OAI收割
来源：上海药物研究所
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