Appl Opt. 2020 Oct 10;59(29):9118-9125. doi: 10.1364/AO.399320.
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.
黄瓜（Cucumis sativus L.）是一种广泛种植且经济效益高的作物。然而，枯萎病会严重影响黄瓜的产量，因为它很难预防和消除。因此，需要一种可靠的方法来快速和早期检测黄瓜中的枯萎病菌感染，这可以通过叶绿素荧光（ChlF）的动力学成像来提供。在这项研究中，利用 ChlF 成像和动力学参数，结合灰度和径向基函数模型，监测黄瓜枯萎病。结果表明，在症状出现之前，这种成像技术可以检测和预测枯萎病。
