Chemometrics, VIS-NIR-SWIR spectroscopy, and deep learning algorithms to classify and predict qualitative attributes of rice in grain processing and storage units.
- DOI
- 10.1016/j.foodchem.2026.149275
- Published
- 2026 Jun 30
- Container
- Food chemistry
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.foodchem.2026.149275,
title = {Chemometrics, VIS-NIR-SWIR spectroscopy, and deep learning algorithms to classify and predict qualitative attributes of rice in grain processing and storage units.},
author = {Arf MV and Filho EAM and Dos Santos Bilhalva N and Santana DC and Teodoro LPR and Teodoro PE and Coradi PC},
year = {2026},
journal = {Food chemistry},
doi = {10.1016/j.foodchem.2026.149275},
url = {https://doi.org/10.1016/j.foodchem.2026.149275}
}RIS
TY - JOUR TI - Chemometrics, VIS-NIR-SWIR spectroscopy, and deep learning algorithms to classify and predict qualitative attributes of rice in grain processing and storage units. AU - Arf MV AU - Filho EAM AU - Dos Santos Bilhalva N AU - Santana DC AU - Teodoro LPR AU - Teodoro PE AU - Coradi PC PY - 2026 JO - Food chemistry DO - 10.1016/j.foodchem.2026.149275 UR - https://doi.org/10.1016/j.foodchem.2026.149275 ER -
APA
MV, A., EAM, F., N, D. S. B., DC, S., LPR, T., PE, T., & PC, C. (2026). Chemometrics, VIS-NIR-SWIR spectroscopy, and deep learning algorithms to classify and predict qualitative attributes of rice in grain processing and storage units.. Food chemistry. https://doi.org/10.1016/j.foodchem.2026.149275
Source records
- pubmed · retrieved 2026-09-26T09:54:49.101Z