Our goal is to establish an interoperable and scalable research data infrastructure in agricultural systems research and beyond. This is how we make research data FAIR and enable genuine knowledge transfer.
To address the resulting challenges, we have initially formulated six use cases focussing on the concepts and services developed by FAIRagro. They address domain- and discipline-specific challenges that we have scaled to benefit the entire agricultural system community. New use cases will be added to the portfolio – in September 2024 we will announce the results of the first FAIRagro Use Case Call.
On this page you will find the description of the currently six existing use cases and their tasks. We have also compiled current reports on the status quo of the individual use cases for you.
Use case 1: Exploiting genotype × location × year × management interactions for sustainable crop production
This use cases addresses challenges in breeding of crops and will exploit possibilities to build up required data management processes that enable genotype × location × year × management interactions.
Partners:
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)
University of Hohenheim
Use case 2: Assessing tradeoffs for optimal crop nitrogen management
This use cases addresses challenges for process-based crop model applications to optimize nitrogen use.
Partners:
Leibniz Centre for Agricultural Landscape Research (ZALF)
Thünen Institute, Helmholtz Centre for Environmental Research (UFZ)
Deutscher Wetterdienst (DWD)
Georg-August University Göttingen
Use case 3: Streamlining pest and disease data to advance integrated pest management
This use cases addresses challenges in pests and diseases management.
Partners:
Federal Research Centre for Cultivated Plants (JKI)
Zentralstelle der Länder für EDV-gestützte Entscheidungshilfen und Programme im Pflanzenschutz (ZEPP)
Informationssystem für die integrierte Pflanzenproduktion (ISIP e.V.)
Use case 4: Learning from incomplete data
This use cases addresses challenges how to deal with incomplete data on the case of data from long-term experiments.
Partners:
Leibniz Centre for Agricultural Landscape Research (ZALF)
Information Centre for Life Sciences (ZB MED)
University of Bonn
World Agricultural Systems Center of Technical University Munich
Use case 5: Noninvasive phenotyping with autonomous robots
This use cases showcases the potential of multimodal data analytics methods and machine-learning algorithms for in-field plant phenotyping.
Partners:
Forschungszentrum Jülich (FZJ)
University of Bonn
Use case 6: Automated data flows for crop simulation models
This use cases addresses data challenges with respect to the calibration and application of crop models.
Partners:
Technical University Munich
Bayerische Landesanstalt für Landwirtschaft
Weihenstephan-Triesdorf University of Applied Sciences
Directorate General of the Bavarian State Archives
Leibniz Institute for Agricultural Engineering and Bioeconomy