Various sensor technologies had been evaluated regarding their usability for the detection of the plant disease Cercospora in the joint project „Data Fusion in Plant Phenotyping for Cercospora Detection in Sugarbeets“ (DataPlant), funded by the German Ministry of Food and Agriculture. The sensor data acquired by georeferenced LIFT and hyperspectral systems, drone based RGB cameras and weather stations were processed and combined – among themselves as well as with traditional scoring methods - using sophisticated Big Data algorithms. Besides the already established RGB images, the determination of vegetation index values by hyperspectral measurements seems to be a promising sensor-based detection method.
The project partners Clausthal University of Technology, KWS SAAT SE & Co. KGaA, MG Optical Solutions GmbH and InfraTec GmbH Infrarotsensorik und Messtechnik developed an innovative sensor system, which shall detect a Cercospora infection by laser induced IR spectroscopy. The plant leaves are irradiated by a quantum cascade laser at wavelengths of typical absorption bands of Cercospora related molecules whereon the resulting surface temperature changes are detected by a radiometrically calibrated thermal camera VarioCAM® HD head by InfraTec.
So, the project „DataPlant“ demonstrated various sensor technologies which are potentially suited for an automated detection of plant diseases and could provide data for digital system solutions in plant production and breeding in future.
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