Selecting and evaluation of key predictive factors in the primary infection stage of cucumber downy mildew in solar greenhouses
JI Tao
LIU Huiying
XU Jianping
LIU Rui
LIU Ran
LI Ming
Abstract：The outbreak of cucumber downy mildew in greenhouse depends on the combined effects of the environment conditions,the management activities and other factors.In production,plant disease prediction relies on all kinds of empirical models,but there are many kinds of input factors,which need to be simplified.The approach we adopt to solve the problem is using the principal component analysis to reduce the dimension of 14 groups of early predictors for cucumber downy mildew,based on field investigation experiment.Three principal components were selected out,which reflected the comprehensive humidity information,the temperature information and the management activities of the greenhouse,respectively.The cumulative contribution rate reached 80.76％,and an empirical model was established based on previous research results.The model had a good predictive effect (R2=0.94) on the occurrence date of cucumber downy mildew,and it could provide an decision reference for the early control of cucumber downy mildew in the solar greenhouses.
Keywords：CucumberPseudoperonospora cubensisEarly warning systemPrincipal component analysisEmpirical model
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 5-10 )