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Estimation of Flavonoids Content of the Wheat Disease Leaves Based on Hyperspectra

文献类型： 外文期刊

作者： Du, Shizhou 1 ; Wu, Liquan 1 ; Wang, Rongfu 1 ;

作者机构： 1.Anhui Agr Univ, Sch Agron, Hefei 230036, Peoples R China

2.Anhui Acad Agr Sci, Crops Inst, Hefei 230031, Peoples R China

关键词： Wheat Disease;Hyperspectral;Flavonoid content;Least Square Support Vector Machine

期刊名称：RESEARCH JOURNAL OF CHEMISTRY AND ENVIRONMENT （ 影响因子：0.636； 五年影响因子：0.511 ）

ISSN： 0972-0626

年卷期： 2012 年 16 卷

页码：

收录情况： SCI

摘要： The flavonoid (Flav) content can be used as evaluation index of plant damage and disease grade. To obtain Flay value of wheat disease leave rapidly and accurately, calibration prediction model of Flay value was established by spectroscopy technology and chemical metrology method. In this study, two algorithm Back Propagation Neural Network (BPNN) and the Least Square Support Vector Machine (LS-SVM) were applicated with the main factor of Partial Least Squares (PLS) as input variable. The results show that the algorithm of LS-SVM is superior to BPNN, and the correlation coefficient and root mean square errors of prediction (RMSEP) of LS-SVM algorithm are 0.9475 and 1.0037 respectively

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