Abstract
Cucumber (Cucumis sativus L.) is a widely cultivated and economically profitable crop. However, Fusarium wilt disease can seriously affect cucumber yields, as it is difficult to prevent and eliminate. Therefore, a reliable method is needed for the rapid and early detection of Fusarium infection in cucumbers, which could be provided via the kinetic imaging of chlorophyll fluorescence (ChlF). In this study, ChlF imaging and kinetic parameters were utilized with gray and radial basis function models to monitor cucumber Fusarium wilt disease. The results indicate that the disease can be detected and predicted using this imaging technique before symptoms become visible.
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