文献类型： 外文期刊
作者： Miao, Mengke 1 ; Feng, Haikuan 2 ; Wang, Baoshan 1 ; Li, Changchun 1 ; Yang, Guijun 2 ; Zhai, Liting 1 ; Liu, Mingxing 1 ; Wu, Zhichao 1 ;
作者机构： 1.Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Henan, Peoples R China
2.Minist Agr, Beijing Res Ctr Informat Technol Agr, Key Lab Quantitat Remote Sensing Agr, Beijing 100097, Peoples R China
3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
4.Beijing Engn Res Ctr Agr Internet Things, Beijing 100097, Peoples R China
关键词： Apple; Continuous wavelet transform; Partial least squares
期刊名称：2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
ISSN： 2153-6996
年卷期： 2019 年
页码：
收录情况： SCI
摘要： Apple nitrogen status is a key indicator for evaluating quality of apple fruits. In order to study and estimate the nitrogen content of apple leaves, it provides a basis for making a reasonable estimate of the yield of fruit trees. In this paper, the continuous wavelet transform method is used to screen out the sensitive bands. Among them, in the range of 500-650 nm, the correlation coefficient between the nitrogen content of the leaves and the original spectrum is significantly higher. The most relevant band is 621 nm with a correlation coefficient of 0.71. Modeling and verificat ion by partial least squares method, the modeling accuracy is R-2 is 0.62, RMSE is 0.26g/(100g), NRMSE is 0.1, verification accuracy R-2 is 0.79, RMSE is 0.31 g/(100g), NRMSE is 0.1. It can be seen that the model has good stability, high prediction ability and good fitting effect, and can be used as an estimat ion model for nit rogen content in apple leaves.
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