Comparative machine learning-assisted terahertz and ultraviolet-visible spectroscopy for rapid authentication and quantitative assessment of adulteration levels in Chinese medicinal herbs
Authors:
- Yaxuan JinYJYaxuan Jin
- Jia XuJXJia Xu
- Xianguo JiangXJXianguo Jiang
- Shaohua ZhangSZShaohua Zhang
- Lei HaoLHLei Hao
- Ning YangNYNing Yang
- Hao MengHMHao Meng
- Chao ZhouCZChao Zhou
- Wendeng HuangWHWendeng Huang
- Yan ZhouYZYan Zhou
Abstract
No abstract availableFunding Information
- Innovation Fund (SLGYCX2514)
- Innovation Fund (SLGYCX2511)
- Innovation Fund (SLGYCX2631)
- Shaanxi Science and Technology Association (20250512)
- Shenzhen Fundamental Research and Discipline Layout project (JCYJ20210324120213037)
- Young Talent Support Program of Shaanxi Province University
- National Natural Science Foundation of China (12374123)
- National Natural Science Foundation of China (12204296)
- National Natural Science Foundation of China (12204295)
- National Natural Science Foundation of China (12174238)
- Key Science and Technology Program of Shaanxi Province (2025ZC-KJXX-15)
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