Machine-learning-assisted ultraviolet-visible spectroscopy for low-level multi-component adulteration identification in Coptis chinensis.
- DOI
- 10.1016/j.saa.2026.128951
- Published
- 2026 Oct 8
- Container
- Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.saa.2026.128951,
title = {Machine-learning-assisted ultraviolet-visible spectroscopy for low-level multi-component adulteration identification in Coptis chinensis.},
author = {Zhou C and Jin Y and Yang N and Jiang X and Zhang S and Hao L and Feng D and Lu C and Xu J and Huang W},
year = {2026},
journal = {Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy},
doi = {10.1016/j.saa.2026.128951},
url = {https://doi.org/10.1016/j.saa.2026.128951}
}RIS
TY - JOUR TI - Machine-learning-assisted ultraviolet-visible spectroscopy for low-level multi-component adulteration identification in Coptis chinensis. AU - Zhou C AU - Jin Y AU - Yang N AU - Jiang X AU - Zhang S AU - Hao L AU - Feng D AU - Lu C AU - Xu J AU - Huang W PY - 2026 JO - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy DO - 10.1016/j.saa.2026.128951 UR - https://doi.org/10.1016/j.saa.2026.128951 ER -
APA
C, Z., Y, J., N, Y., X, J., S, Z., L, H., D, F., C, L., J, X., & W, H. (2026). Machine-learning-assisted ultraviolet-visible spectroscopy for low-level multi-component adulteration identification in Coptis chinensis.. Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy. https://doi.org/10.1016/j.saa.2026.128951
Source records
- pubmed · retrieved 2026-11-10T10:30:46.051Z