title: [Chlorophyll fluorescence spectrum analysis of greenhouse cucumber disease and insect damage].
abstract: The present paper is based on chlorophyll fluorescence spectrum analysis. The wavelength 685 nm was determined as the primary characteristic point for the analysis of healthy or disease and insect damaged leaf by spectrum configuration. Dimensionality reduction of the spectrum was achieved by combining simple intercorrelation bands selection and principal component analysis (PCA). The principal component factor was reduced from 10 to 5 while the spectrum information was kept reaching 99.999%. By comparing and analysing three modeling methods, namely the partial least square regression (PLSR), BP neural network (BP) and least square support vector machine regression (LSSVMR), regarding correlation coefficient of true value and predicted value as evaluation criterion, eventually, LSSVMR was confirmed as the appropriate method for modeling of greenhouse cucumber disease and insect damage chlorophyll fluorescence spectrum analysis.
authors: Key Laboratory of Bionic Engineering, Ministry of Education, School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China. suiyuan0115@126.com
authors: Yuan-yuan
authors: YY
authors: Sui
authors: Hai-ye
authors: HY
authors: Yu
authors: Lei
authors: L
authors: Zhang
authors: Han
authors: H
authors: Luo
authors: Shun
authors: S
authors: Ren
authors: Guo-gang
authors: GG
authors: Zhao
mesh_terms: D000818:Animals; D002734:Chlorophyll / Q000032:analysis*; D018553:Cucumis sativus / Q000737:chemistry* / Q000382:microbiology; D005453:Fluorescence; D060434:Herbivory; D007313:Insecta; D016018:Least-Squares Analysis; D016571:Neural Networks, Computer; D010935:Plant Diseases; D018515:Plant Leaves; D025341:Principal Component Analysis; D013050:Spectrometry, Fluorescence
chemical_list: D002734:Chlorophyll