Discrimination of rice panicles by hyperspectral reflectance data based on principal component analysis and support vector classification

Journal of Zhejiang University: Science B

Volumn 11, Issue 1, 2010, Pages 71-78

  Liu, Zhan Yu ^a,b   Shi, Jing Jing ^a   Zhang, Li Wen ^a   Huang, Jing Feng ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b Key Laboratory of Agricultural Remote Sensing and Information System of Zhejiang Province   (China)

Author keywords

Derivative spectra; Hyperspectral reflectance; Principal component analysis (PCA); Rice panicle; Support vector classification (SVC)

Indexed keywords

ACCURACY; ANALYTIC METHOD; ARTICLE; CLASSIFICATION; MEASUREMENT; NEAR INFRARED REFLECTANCE SPECTROSCOPY; NONHUMAN; PANICLE; PLANT DISEASE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; RICE; SUPPORT VECTOR MACHINE;

AGRICULTURE; ASCOMYCOTA; BIOTECHNOLOGY; DATA INTERPRETATION, STATISTICAL; FOOD CONTAMINATION; GENES, FUNGAL; ORYZA SATIVA; PRINCIPAL COMPONENT ANALYSIS;

HEXAPODA; NILAPARVATA LUGENS; SPRING VIREMIA OF CARP VIRUS; USTILAGINOIDEA VIRENS;

EID: 75949115510     PISSN: 16731581     EISSN: 18621783     Source Type: Journal    
DOI: 10.1631/jzus.B0900193     Document Type: Article

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