Hyperspectral imaging combined with texture features for maize hybrid purity detection: a multi-model comparison based on machine learning and SHAP interpretability study.
- DOI
- 10.1016/j.saa.2026.128407
- Published
- 2026 Dec 15
- Container
- Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
- Publisher
- Not recorded
- Open access
- unknown
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BibTeX
@article{allodium:10.1016/j.saa.2026.128407,
title = {Hyperspectral imaging combined with texture features for maize hybrid purity detection: a multi-model comparison based on machine learning and SHAP interpretability study.},
author = {Han X and Li X and Wu S and Liu X and Li Z and Song Y and He Y and Tian X and Wan X},
year = {2026},
journal = {Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy},
doi = {10.1016/j.saa.2026.128407},
url = {https://doi.org/10.1016/j.saa.2026.128407}
}RIS
TY - JOUR TI - Hyperspectral imaging combined with texture features for maize hybrid purity detection: a multi-model comparison based on machine learning and SHAP interpretability study. AU - Han X AU - Li X AU - Wu S AU - Liu X AU - Li Z AU - Song Y AU - He Y AU - Tian X AU - Wan X PY - 2026 JO - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy DO - 10.1016/j.saa.2026.128407 UR - https://doi.org/10.1016/j.saa.2026.128407 ER -
APA
X, H., X, L., S, W., X, L., Z, L., Y, S., Y, H., X, T., & X, W. (2026). Hyperspectral imaging combined with texture features for maize hybrid purity detection: a multi-model comparison based on machine learning and SHAP interpretability study.. Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy. https://doi.org/10.1016/j.saa.2026.128407
Source records
- pubmed · retrieved 2026-09-25T23:43:23.359Z