Estimation of wheat tiller density using remote sensing data and machine learning methods
The tiller density is a key agronomic trait of winter wheat that is essential to field management and yield estimation. The traditional method of obtaining the wheat tiller density is based on manual counting, which is inefficient and error prone. In this study, we established machine learning model...
Main Authors: | Jinkang Hu, Bing Zhang, Dailiang Peng, Ruyi Yu, Yao Liu, Chenchao Xiao, Cunjun Li, Tao Dong, Moren Fang, Huichun Ye, Wenjiang Huang, Binbin Lin, Mengmeng Wang, Enhui Cheng, Songlin Yang |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-12-01
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Series: | Frontiers in Plant Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2022.1075856/full |
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