Sustainable, pesticide-free cultivation of sugar beet in the Uckermark region

Hinweis zur Verwendung von Bildmaterial: Die Verwendung des Bildmaterials zur Pressemitteilung ist bei Nennung der Quelle vergütungsfrei gestattet. Das Bildmaterial darf nur in Zusammenhang mit dem Inhalt dieser Pressemitteilung verwendet werden. Falls Sie das Bild in höherer Auflösung benötigen oder Rückfragen zur Weiterverwendung haben, wenden Sie sich bitte direkt an die Pressestelle, die es veröffentlicht hat.

BMBF project zUCKERrübe | Download

Within the framework of the WIR! initiative of the German Federal Ministry of Education and Research (BMBF), a new joint project called "zUCKERrübe" (sugar beet) aims to enable sustainable and pesticide-free cultivation of field crops using the example of sugar beet in the Uckermark region. For this purpose, field robots, UAS technology (UAS = unmanned aerial system) and artificial intelligence (AI) methods as well as the interaction of these components are to be investigated.

One milestone of the two-year project and funded with 540000 EUR will be the develop-ment of a new weed control technique to integrate sugar beet cultivation into the crop rotation of sustainable agriculture. In addition, the possibility of transferring the new method to other environmentally friendly cultivated crops will be created.

The project consortium consisting of the Eberswalde University of Applied Sciences, Zau-berzeug GmbH, Leibniz Centre for Agricultural Landscape Research (ZALF) e.V. and the Leibniz Institute for High Performance Microelectronics (IHP), which is supported in its work with a funding sum of 118000 euros by the BMBF.

In the development phase of the project, close cooperation with practical companies and regional processors plays a major role. This means that their needs and requirements can be taken into account from the beginning, thus ensuring practicality.

"In the project, IHP will dedicate itself to the development of AI-based image analysis on low-resource hardware platforms for determining weed infestation and relative location of the hoeing robot. To this end, we will develop various hardware accelerators so that drones will be able to use AI algorithms for image analysis in the future, despite their small computing capacity. This will allow hacking robots and drones to be used in areas with poor cellular reception because weed detection will be done on drones and not on cloud servers," says Dr. Marcin Brzozowski from IHP.

Wissenschaftlicher Ansprechpartner:
Dr. Marcin Brzozowski