Monitoring of peanut leaves chlorophyll content based on drone-based multispectral image feature extraction

Author:

Qi Haixia,Wu Zeyu,Zhang Lei,Li Jianwen,Zhou Jingkang,Jun Zou,Zhu Bingyu

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference46 articles.

1. Yang, J., 2020. Peanut Industry Status and Measures. Agricultural Development & Equipment, 03,24+26. (In Chinese with English Abstract).

2. Types of peanut diseases in China and their control measures;You;Jiangxi J. Agric.,2010

3. Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data;Oppelt;Int. J. Remote Sens.,2004

4. Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery;Monteiro;ISPRS J. Photogramm. Remote Sens.,2007

5. Monitoring canopy biophysical and biochemical parameters in ecosystem scale using satellite hyperspectral imagery: an application on a Phlomis fruticose Mediterranean ecosystem using multiangular CHRIS/PROBA observations;Stagakis;Remote Sens. Environ.,2010

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