Multi-temporal UAV multispectral phenotyping and machine learning for modeling cotton defoliation dynamics across diverse accessions
- DOI
- 10.1016/j.plaphe.2026.100295
- Published
- 2026-12
- Container
- Plant Phenomics
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.plaphe.2026.100295,
title = {Multi-temporal UAV multispectral phenotyping and machine learning for modeling cotton defoliation dynamics across diverse accessions},
author = {Mingze Li and Qisheng Feng and Xiaofei Li and Guoping Wang and Mingwei Du and Sumei Wan and Hongqiang Dong and Mengyan Ren and Zuoren Yang and Lu Feng and Guodong Chen},
year = {2026},
journal = {Plant Phenomics},
doi = {10.1016/j.plaphe.2026.100295},
url = {https://doi.org/10.1016/j.plaphe.2026.100295}
}RIS
TY - JOUR TI - Multi-temporal UAV multispectral phenotyping and machine learning for modeling cotton defoliation dynamics across diverse accessions AU - Mingze Li AU - Qisheng Feng AU - Xiaofei Li AU - Guoping Wang AU - Mingwei Du AU - Sumei Wan AU - Hongqiang Dong AU - Mengyan Ren AU - Zuoren Yang AU - Lu Feng AU - Guodong Chen PY - 2026 JO - Plant Phenomics DO - 10.1016/j.plaphe.2026.100295 UR - https://doi.org/10.1016/j.plaphe.2026.100295 ER -
APA
Li, M., Feng, Q., Li, X., Wang, G., Du, M., Wan, S., Dong, H., Ren, M., Yang, Z., Feng, L., & Chen, G. (2026). Multi-temporal UAV multispectral phenotyping and machine learning for modeling cotton defoliation dynamics across diverse accessions. Plant Phenomics. https://doi.org/10.1016/j.plaphe.2026.100295
Source records
- crossref · retrieved 2026-11-10T11:24:22.402Z