Entropy Weight Ensemble Framework for Yield Prediction of Winter Wheat Under Different Water Stress Treatments Using Unmanned Aerial Vehicle-Based Multispectral and Thermal Data.

Fei, Shuaipeng; Hassan, Muhammad Adeel; Ma, Yuntao; Shu, Meiyan; Cheng, Qian; Li, Zongpeng; Chen, Zhen; Xiao, Yonggui

Fei, Shuaipeng; Hassan, Muhammad Adeel; Ma, Yuntao; Shu, Meiyan; Cheng, Qian; Li, Zongpeng; Chen, Zhen; Xiao, Yonggui.

Afiliación

Fei S; Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences, Xinxiang, China.
Hassan MA; National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Ma Y; College of Land Science and Technology, China Agricultural University, Beijing, China.
Shu M; National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Cheng Q; Dezhou Academy of Agricultural Sciences, Dezhou, China.
Li Z; College of Land Science and Technology, China Agricultural University, Beijing, China.
Chen Z; College of Land Science and Technology, China Agricultural University, Beijing, China.
Xiao Y; Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences, Xinxiang, China.

Front Plant Sci ; 12: 730181, 2021.

Article en En | MEDLINE | ID: mdl-34987529

Palabras clave

UAV; machine learning; multispectral indices; remote sensing; thermal infrared; wheat yield

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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Plant Sci Año: 2021 Tipo del documento: Article País de afiliación: China

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