Estimation of wheat tiller density using remote sensing data and machine learning methods

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...

Full description

Bibliographic Details
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
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-12-01
Series:Frontiers in Plant Science
Subjects:
winter wheat
tiller density
UAV hyperspectral
vegetation index
random forest
gradient boosted regression trees
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2022.1075856/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2022.1075856/full

Similar Items