Use of microscale heterogeneity in samples for spectral factorization—A strategy to build robust prediction models for nondestructive analyses
- DOI
- 10.1016/j.foodchem.2024.140591
- Published
- 2024-12
- Container
- Food Chemistry
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.foodchem.2024.140591,
title = {Use of microscale heterogeneity in samples for spectral factorization—A strategy to build robust prediction models for nondestructive analyses},
author = {Michiko Sano and Tsuyoshi Yamashita and Yutaka Kitamura and Mito Kokawa},
year = {2024},
journal = {Food Chemistry},
doi = {10.1016/j.foodchem.2024.140591},
url = {https://doi.org/10.1016/j.foodchem.2024.140591}
}RIS
TY - JOUR TI - Use of microscale heterogeneity in samples for spectral factorization—A strategy to build robust prediction models for nondestructive analyses AU - Michiko Sano AU - Tsuyoshi Yamashita AU - Yutaka Kitamura AU - Mito Kokawa PY - 2024 JO - Food Chemistry DO - 10.1016/j.foodchem.2024.140591 UR - https://doi.org/10.1016/j.foodchem.2024.140591 ER -
APA
Sano, M., Yamashita, T., Kitamura, Y., & Kokawa, M. (2024). Use of microscale heterogeneity in samples for spectral factorization—A strategy to build robust prediction models for nondestructive analyses. Food Chemistry. https://doi.org/10.1016/j.foodchem.2024.140591
Source records
- crossref · retrieved 2026-09-26T11:08:13.934Z