Identification of Early Peach Aphid Infestation Based on Hyperspectral Imaging Technology  

作　　者：Yangyang Fan Wenjie Feng Zhengjun Qiu Shuai Wang 

机构地区：[1]Institute of Agricultural Information and Economics,Shandong Academy of Agricultural Sciences,Jinan 250000,China [2]College of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou 310000,China

出　　处：《Journal of Beijing Institute of Technology》2023年第3期374-383,共10页北京理工大学学报（英文版）

基　　金：supported by China National Key Research and Development Program(No.2016YFD0700304);Shandong Natural Science Foundation Youth Program(No.ZR2021QC216);Agricultural Scientific and Technological Innovation Project of Shandong Academy of Agricultural Science(No.CXGC2023A34)。

摘　　要：Peach aphid is a common pest and hard to detect.This study employs hyperspectral imaging technology to identify early damage in green cabbage caused by peach aphid.Through principal component transformation and multiple linear regression analysis,the correlation relation between spectral characteristics and infestation stage is analyzed.Then,four characteristic wavelength selection methods are compared and optimal characteristic wavelengths subset is determined to be input for modelling.One linear algorithm and two nonlinear modelling algorithms are compared.Finally,support vector machine(SVM)model based on the characteristic wavelengths selected by multi-cluster feature selection(MCFS)acquires the highest identification accuracy,which is 98.97%.These results indicate that hyperspectral imaging technology have the ability to identify early peach aphid infestation stages on green cabbages.

关 键 词：peach aphid hyperspectral imaging machine learning green cabbage 

分 类 号：S433.3[农业科学—农业昆虫与害虫防治] TP751[农业科学—植物保护]