Combining spectrum, thermal, and texture features using machine learning algorithms for wheat nitrogen nutrient index estimation and model transferability analysis
Shaohua ZhangAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaJianzhao DuanAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaXinghui QiAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaYuezhi GaoAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaLi HeAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaLinru LiuAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaTiancai GuoAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, ChinaWei FengAgronomy College of Henan Agriculture University/State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450046, Henan, China
2024en
ABI
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