title: [Study on early detection of gray mold on tomato leaves using hyperspectral imaging technique].
abstract: The present paper put forward the technology route for feature images extraction of grey mold sick on tomato leaves based on SIMCA--combination image extraction based on MLR-grey mold sick information extraction based on minimum distance method. Firstly, through the 680-740 nm band's variance image and the discrimination power parameter, the feature band images was found, then the feature bands information was used as the input of MLR analysis, and under the 0.5 accuracy threshold value, 99% accuracy was obtained, which showed the discrimination power of the features bands for grey mold sick tomato leaf detection, and using the MLR regression coefficient to extract a band combination image, and through the minimum distance method, tomato grey mold sick information was found. The result shows that the proposed method has a very good prediction ability and greatly reduces the hyperspectral data processing time.
authors.affiliation: College of Electrical and Electronics Engineering, Zhejiang Institute of Mechanical & Electrical Engineering, Hangzhou 310053, China. yuweiyan@126.com
authors.forename: Jia-Jia
authors.initials: JJ
authors.lastname: Yu
authors.forename: Yong
authors.initials: Y
authors.lastname: He
mesh_terms: D020171:Botrytis / Q000302:isolation & purification*; D018551:Solanum lycopersicum / Q000382:microbiology*; D010935:Plant Diseases / Q000382:microbiology*; D018515:Plant Leaves / Q000382:microbiology*; D013057:Spectrum Analysis / Q000379:methods*