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Hyperspectral Estimation Methods for Chlorophyll Content of Apple Based on Random Forest

文献类型： 外文期刊

作者： Pei, Haojie 1 ; Li, Changchun 5 ; Feng, Haikuan 1 ; Yang, Guijun 1 ; Liu, Mingxing 1 ; Wu, Zhichao 1 ;

作者机构： 1.Minist Agr Peoples Republ China, Beijing Res Ctr Informat Technol Agr, Key Lab Quantitat Remote Sensing Agr, Beijing 100097, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.Minist Agr, Key Lab Informat Technol Agr, Beijing 100097, Peoples R China

4.Beijing Engn Res Ctr Agr Internet Things, Beijing 100097, Peoples R China

5.Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Henan, Peoples R China

关键词： Apple leaf; Hyperspectral; Chlorophyll; RF

期刊名称：COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE XI, CCTA 2017, PT II

ISSN： 1868-4238

年卷期： 2019 年 546 卷

页码：

收录情况： SCI

摘要： Chlorophyll content is a good indicator of fruit tree nutrition stress, photosynthesis, and another physiological state. 10 vegetation indices were selected and used as input variables of RF model, the number of input variables was gradually increased from 1 to 10. The modeling accuracy of 10 RF models with vegetation indices was compared. Finally, the accuracy of 2 estimation models, the RF model with the original spectrum, and the RF optimal model with vegetation indices were established and compared. The result, For modeling accuracy of 2 models, the R-2 of four models are 0.527 and 0.609, and the RMSE of 2 models are 8.728 and 7.930 mu g/cm(2), respectively. For validation accuracy of 2 models, R-2 of 2 models is 0.411 and 0.843, RMSE is 14.455 and 11.034 mu g/cm(2), respectively. The result showed, (1) the accuracy of RF model with vegetation indices is higher than the other model. (2) The RF model with vegetation indices can estimate the chlorophyll content of apple leaves more accurately and it had the potential for estimating chlorophyll content of apple leaf. And it provides a new method for the accurate estimation of chlorophyll of apple leaves.

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