Improving the Estimation of Apple Leaf Photosynthetic Pigment Content Using Fractional Derivatives and Machine Learning

As a key functional trait, leaf photosynthetic pigment content (LPPC) plays an important role in the health status monitoring and yield estimation of apples. Hyperspectral features including vegetation indices (VIs) and derivatives are widely used in retrieving vegetation biophysical parameters. The...

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書誌詳細

出版年:	Agronomy
主要な著者:	Jinpeng Cheng, Guijun Yang, Weimeng Xu, Haikuan Feng, Shaoyu Han, Miao Liu, Fa Zhao, Yaohui Zhu, Yu Zhao, Baoguo Wu, Hao Yang
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2022-06-01
主題:	apple leaf photosynthetic pigment content fractional derivative machine learning hyperspectral data
オンライン･アクセス:	https://www.mdpi.com/2073-4395/12/7/1497