Precision Farming allows for an optimized application of pesticides. Currently the spatial distribution of plant diseases in fields is not taken into account, because reliable tools for a site specific disease detection or prognosis are not readily available. The aim of this work was to develop a tool for site specific disease prognosis, exemplarily for stem base diseases in winter wheat. In the years 2018 to 2020, disease measurements were made at milk ripening in several fields. Disease measurements were performed by grid sampling about 150 points per field. Per point, 20 tillers (2018: 10 tillers) were visually examined and disease severity of eyespot, Fusarium crown rot and sharp eyespot was assessed.
Using ancillary data sources like official geodata, remote sensing data and sensor data, information considering factors like crop density, soil moisture and plant vitality was derived and (geo-)statistically evaluated for suitability regarding a site specific disease prognosis. Data from a prior research project was included in the analysis. Here, results considering the site specific prognosis of Fusarium crown rot using official geodata is presented. A model was developed which differentiates three zones of relative disease risk. The accuracy of the model was evaluated using the aforementioned disease measurements. Depending on the data source and the considered disease zone the precision of the model lies around 60 to 70 %.
Authors: Marco Herrmann, Benno Kleinhenz, Paolo Racca and Stephan Estel
This work was funded by the federal ministry of food and agriculture based on a resolution of the German Bundestag. It is part of the research project ‘AssSys – Assistenzsystem zur teilflächenspezifischen Applikation von Pflanzenschutzmitteln’.
