Temporal alignment of UAV hyperspectral and phenotype data via autoencoders for predicting nitrogen and nicotine content in cured tobacco leaves.
- DOI
- 10.1186/s13007-026-01570-1
- Published
- 2026-07-19
- Container
- Plant Methods
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1186/s13007-026-01570-1,
title = {Temporal alignment of UAV hyperspectral and phenotype data via autoencoders for predicting nitrogen and nicotine content in cured tobacco leaves.},
author = {Zhang M and Kuai Y and Chen D and Guo W and Zhao L and Yuan S and Zhao R and Xu Q and Gu X and Chen T.},
year = {2026},
journal = {Plant Methods},
doi = {10.1186/s13007-026-01570-1},
url = {https://doi.org/10.1186/s13007-026-01570-1}
}RIS
TY - JOUR TI - Temporal alignment of UAV hyperspectral and phenotype data via autoencoders for predicting nitrogen and nicotine content in cured tobacco leaves. AU - Zhang M AU - Kuai Y AU - Chen D AU - Guo W AU - Zhao L AU - Yuan S AU - Zhao R AU - Xu Q AU - Gu X AU - Chen T. PY - 2026 JO - Plant Methods DO - 10.1186/s13007-026-01570-1 UR - https://doi.org/10.1186/s13007-026-01570-1 ER -
APA
M, Z., Y, K., D, C., W, G., L, Z., S, Y., R, Z., Q, X., X, G., & T., C. (2026). Temporal alignment of UAV hyperspectral and phenotype data via autoencoders for predicting nitrogen and nicotine content in cured tobacco leaves.. Plant Methods. https://doi.org/10.1186/s13007-026-01570-1
Source records
- europe-pmc · retrieved 2026-09-27T09:11:54.457Z