A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy
- DOI
- 10.1016/j.foodchem.2026.150365
- Published
- 2026-10
- Container
- Food Chemistry
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.foodchem.2026.150365,
title = {A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy},
author = {Xijun Wu and Tianhao Du and Shibo Du and Congyu Lei and Heying Zhang and Xuan Zheng and Ruiling Tian},
year = {2026},
journal = {Food Chemistry},
doi = {10.1016/j.foodchem.2026.150365},
url = {https://doi.org/10.1016/j.foodchem.2026.150365}
}RIS
TY - JOUR TI - A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy AU - Xijun Wu AU - Tianhao Du AU - Shibo Du AU - Congyu Lei AU - Heying Zhang AU - Xuan Zheng AU - Ruiling Tian PY - 2026 JO - Food Chemistry DO - 10.1016/j.foodchem.2026.150365 UR - https://doi.org/10.1016/j.foodchem.2026.150365 ER -
APA
Wu, X., Du, T., Du, S., Lei, C., Zhang, H., Zheng, X., & Tian, R. (2026). A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy. Food Chemistry. https://doi.org/10.1016/j.foodchem.2026.150365
Source records
- crossref · retrieved 2026-09-26T09:56:17.555Z