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A Precise and Autonomous System for the Detection of Insect Emergence Patterns
Published on: January 9, 2019
Development of a quantitative forecasting system for Septoria tritici based on a long-term monitoring
M Henze1, H Klink, J A Verreet
1Christian-Albrechts University Kiel, Faculty Agricultural Sciences Dept. Phytopathology, Hermann-Rodewald-Str. 9, DE-24118 Kiel, Germany.
Abstract:
Septoria tritici is the most important diseases in winter wheat in Schleswig-Holstein (northern Germany) and in many other regions over the world. But the disease severity as well as the timing of the epidemic progression varies between locations and seasons and so he influence on yield parameters like absolute yield or yield loss. To optimize the disease management a quantitative knowledge of the factors affecting the disease progression is necessary. Weather is the driving force of the disease progression, the weather from sowing until stem elongation influence mostly the disease severity on the lower leaves whereas the weather during the vegetation period determines the epidemic disease patterns of the upper yield relevant leaves (F-3 to flag leaf). The epidemic disease progression occurs in several pushes, also recognized as "sudden outbreaks", where such an increase is initiated by a weather scenario called infection cycle. The object of this study is the identification of the most important factors of each part of the disease progression and their interaction. So that weather scenarios as well as cropping parameters can be evaluated and recommendations for the disease management can be made.