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Optimization of cauliflower cultivation by monitoring with UAVs and machine-learning
The project OPTIKO will use unmanned aerial vehicles (UAVs) to monitor growth and plant performance using the example of cauliflower. By combining multispectral images taken by UAV-based low cost multispectral cameras with machine learning methods for data analysis, we will develop an innovative process to assess traits of individual plants. Machine learning methods will be trained to detect heterogeneities within a field based on spectral and spatial information, which indicate reduced plant performance due to abiotic and biotic stress. In the future, automatized, regular UAV overflights could be used for the early detection of stress symptoms and precise application of management procedures, such as fertilization or the application of pesticides. In addition, multispectral data will be used to predict the date of harvest, which will allow for improved management of sales and thus stabilize sales benefits. By developing this novel process, which will be transferable to further crops in the future, OPTIKO contributes to the digitalization of agriculture and complements already established operational processes and existing agro-technology.
Results and the Final report will be found here, as soon as the project is completed.
Rural development 2014-2020 for Operational Groups (in the sense of Art 56 of Reg.1305/2013)
Universität Bonn
Klein Altendorf 2
53359 Rheinbach
Phone: +49 2225 980 87 35
Email: h.jaenicke@uni-bonn.de
2020
ongoing
499,346
DEA22
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