We use cookies on our website. Some are necessary for the operation of the website. You can also allow cookies for statistical purposes. You can adjust the data protection settings or agree to all cookies directly.
Data Protection Declaration
Imprint
Collaborative project: Sensor-based online detection of diseases in cereals - subproject 2
Project
Project code: 2815705715
Contract period: 01.08.2016
- 31.07.2019
Budget: 350,798 Euro
Purpose of research: Experimental development
"In the field trials conducted by the copartner ATB in the UAV-images (15 m above ground) only those stripe rust patches were visible which are clearly distinct from the neighboring healthy crop area according to the color. Using spectral features with the optical close-range sensors and also with the aerial UAV-images differences between infected and control plots (9 m x 9 m) were detected early enough to control the disease in practice. The close-range color images were sufficiently proximal (2 m above ground) to classify the uredospore layers which were arranged in a line using spectral and spatial features. The data coming from the sensors were imported together with the GPS position in the prototype “Agriport Fusion” developed by the copartner Agricon. The huge data sets were processed regarding to decision-making for fungicide use by the farmer. The copartner TOSS developed an optical red/infrared vertical sensor. It was possible to detect height dependent (younger and older crop tissue) health status differences inside the crop canopy between the infected and healthy plots using."
Section overview
Subjects
- Crop Protection
- Agricultural Engineering Plant Production
- Computer science
