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| Hyperspectral imaging technology of nitrogen status diagnose for tomato leaves |
| 1.Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education ＆ Jiangsu Province, Jiangsu University, Zhenjiang, Jiangsu 212013, China; 2.Taizhou Electromechanical Vocational and Technical College, Taizhou, Jiangsu 225300, China |
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Abstract The data cube of hyperspectral image was translated into twodimension characteristic curve by extracting color and texture features, and all wavelengths were screened by the feature selection method of CFS.The characteristic wavelengths of color feature were determined as 549， 669， 742 and 830 mm，and those of texture feature were 482 and 684 nm. The 12 feature variables were extracted for each tomato leave sample to perform principal component analysis（PCA）.The 9 principal components (PCs) were extracted as input vectors to establish SVC model for the identification of nitrogen status. The experimental results show that the distinct nitrogen status accuracies of N1，N2， N3 and N4 are 96%，88%，92% and 92%, respectively. The hyperspectral imaging technology is suitable for nitrogen status diagnose of tomato leaves.
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2014, Vol. 35 
