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Estimation of chlorophyll content in maize canopy using wavelet denoising and SVR method

作     者:Haojie Liu Minzan Li Junyi Zhang Dehua Gao Hong Sun Liwei Yang 

作者机构:Key Laboratory of Modern Precision Agriculture System Integration ResearchMinistry of EducationChina Agricultural UniversityBeijing 100083China Key Laboratory of Agricultural information acquisition technologyMinistry of AgricultureChina Agricultural UniversityBeijing 100083China 

出 版 物:《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报(英文))

年 卷 期:2018年第11卷第6期

页      面:132-137页

核心收录:

学科分类:09[农学] 0901[农学-作物学] 

基  金:This study was supported by the Chinese High Technology Research and Development Research Fund(2016YFD0300600-2016YFD0300606,2016YFD0300600-2016YFD0300610) NSFC program(31501219) the Fundamental Research Funds for the Central Universities(2018TC020,2018XD003) Industry Research Project(QingPu 2017-12) 

主  题:maize canopy spectral reflectance wavelet denoising SVR model chlorophyll content 

摘      要:In order to estimate the chlorophyll content of maize plant non-destructively and rapidly,the research was conducted on maize at the heading stage using spectroscopy *** spectral reflectance of maize canopy was measured and processed following wavelet denoising and multivariate scatter correction(MSC)to reduce the noise ***,the signal to noise ratio(SNR)and curve smoothness(CS)were used to evaluate the denoising effect of different wavelet functions and decomposition *** a result,the Sym6 wavelet basis function and the 5th level decomposition were determined to denoise the original *** MSC method was used to eliminate the scattering effect after *** three spectral ranges were extracted by interval partial least squares(IPLS)including the 525-549 nm,675-749 nm and 850-874 ***,the chlorophyll content estimation model was developed by using support vector regression(SVR)*** calibration Rc2 of the SVR model was 0.831,the RMSEC was 1.3852 mg/L;the validation Rv2 was 0.809,the RMSEP was 0.8664 mg/*** results show that the SNR and CS indicators can be used to select the parameters for wavelet denoising and model can be used to estimate the chlorophyll content of maize canopy in the field.

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