Deciphering quality decline in Peucedani Radix: An interpretable deep learning framework integrating multimodal analysis across the supply chain
• Comprehensive quality assessment of Peucedani Radix across the entire supply chain. • Integrated chemical, molecular, and spectroscopic analyses reveal multifactorial quality decline. • Interpretable deep learning model achieves over 90% accuracy for rapid authentication. • Proposes a novel "gold-standard verification and on-site rapid screening" quality control paradigm.
Authors
- Leilei Gao (ORCID: https://orcid.org/0000-0003-3752-6543)
- Fang Wang (ORCID: https://orcid.org/0000-0002-5971-2622)
- Bangxing Han
- XIANGWEN SONG (ORCID: https://orcid.org/0009-0001-3356-6428)
- Bin Jia
- Biqi Liyao
- Hui Yan
Institutions
- Anhui University of Traditional Chinese Medicine (CN)
- Jiangsu University of Science and Technology (CN)
Publication Details
- Journal
- Industrial Crops and Products
- Published
- 2026-05-23
- DOI
- https://doi.org/10.1016/j.indcrop.2026.123509
- Primary Topic
- Spectroscopy and Chemometric Analyses
- Type
- article
- Field-Weighted Citation Impact
- 0.00