Risk models for decisions on fungicide use based on weather data, disease monitoring, and control thresholds are used as important elements in a sustainable cropping system. The need for control… Click to show full abstract
Risk models for decisions on fungicide use based on weather data, disease monitoring, and control thresholds are used as important elements in a sustainable cropping system. The need for control of leaf blotch diseases in wheat (caused by Zymoseptoria tritici, Parastagonospora nodorum and Pyrenophora tritici-repentis) vary significantly across years and locations. Disease development is mainly driven by humidity events during stem elongation and heading. Two risk models were tested in field trials in order to identify situations favourable for the development of leaf blotch diseases in Lithuania, Norway, Sweden, Finland and Denmark. The Crop Protection Online (CPO) model uses days with precipitation (>1 mm), while the humidity model (HM) uses 20 continuous hours with relative humidity (RH) ≥ 85% as criteria for the need of a fungicide application. Forty-seven field trials were carried out during two seasons to validate these two risk-models against reference fungicide treatments. The season 2018 was dry and 2019 had an average precipitation profile. The two risk models with few exceptions provided acceptable disease control. In 2018, very few treatments were recommended by the models, saving 85–98% of treatments compared to the reference treatments, while in the wetter season 2019, 31% fewer applications were recommended. Based on specific criteria including fungicide input and net yield responses the models gave correct recommendations in 95% of the trials in 2018 and in 54–58% of the trials in 2019 compared with reference treatments dominated by 2–3 sprays. In comparison with single spray references, the models gave correct recommendations in 54–69% of the situations.
               
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