Rapid and accurate PLS-RBF neural networks for multi-constituent prediction in intact fresh maize kernels using NIR spectroscopy
- DOI
- 10.1016/j.foodchem.2026.151324
- Published
- 2026-12
- Container
- Food Chemistry
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.foodchem.2026.151324,
title = {Rapid and accurate PLS-RBF neural networks for multi-constituent prediction in intact fresh maize kernels using NIR spectroscopy},
author = {Xuejin Zhu and Jiang Shi and Shengtao Qu and Erkui Yue and Lin Zhao and Bote Wang and Jianguo Wu and Weifeng Chen and Zhengyan Ling and Zhengfang Zhang},
year = {2026},
journal = {Food Chemistry},
doi = {10.1016/j.foodchem.2026.151324},
url = {https://doi.org/10.1016/j.foodchem.2026.151324}
}RIS
TY - JOUR TI - Rapid and accurate PLS-RBF neural networks for multi-constituent prediction in intact fresh maize kernels using NIR spectroscopy AU - Xuejin Zhu AU - Jiang Shi AU - Shengtao Qu AU - Erkui Yue AU - Lin Zhao AU - Bote Wang AU - Jianguo Wu AU - Weifeng Chen AU - Zhengyan Ling AU - Zhengfang Zhang PY - 2026 JO - Food Chemistry DO - 10.1016/j.foodchem.2026.151324 UR - https://doi.org/10.1016/j.foodchem.2026.151324 ER -
APA
Zhu, X., Shi, J., Qu, S., Yue, E., Zhao, L., Wang, B., Wu, J., Chen, W., Ling, Z., & Zhang, Z. (2026). Rapid and accurate PLS-RBF neural networks for multi-constituent prediction in intact fresh maize kernels using NIR spectroscopy. Food Chemistry. https://doi.org/10.1016/j.foodchem.2026.151324
Source records
- crossref · retrieved 2026-11-10T20:04:22.908Z