Estimating Wheat Chlorophyll Content Using a Multi-Source Deep Feature Neural Network

Estimating Wheat Chlorophyll Content Using a Multi-Source Deep Feature Neural Network

Chlorophyll plays a vital role in wheat growth and fertilization management. Accurate and efficient estimation of chlorophyll content is crucial for providing a scientific foundation for precision agricultural management. Unmanned aerial vehicles (UAVs), characterized by high flexibility, spatial re...

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Bibliographic Details
Main Authors: Jun Li, Yali Sheng, Weiqiang Wang, Jikai Liu, Xinwei Li
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Agriculture
Subjects:
remote sensing
UAV
chlorophyll content
wheat
deep learning
deep feature
Online Access:https://www.mdpi.com/2077-0472/15/15/1624
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