Objectives
Main objective of this Yield Monitoring RIL is to unlock the potential of yield data from harvesters for European-wide yield monitoring.
Key issues that will be addressed:
- Access to often very scattered harvester data, while respecting the privacy of the data owners.
- Using the data in a yield monitoring tool to estimate crop productivity at local (field and sub-field) and regional scale throughout the EU
- Deriving essential information from these yield estimates to optimize crop production in a sustainable way.
Technology / Methodology
- Explore the potential of EO data to improve sensor yield estimates: solution for missing data, tare weight estimates...
- Turning yield variability data into essential information on where growth conditions were suboptimal, to the benefit of the farmers, using a Digital Twin concept.
- Setting up a flexible machine learning-based yield estimation model, that makes use of EO data, weather, soil and harvester data.
Expected outcome
- Innovative, privacy-preserving data exchange mechanism
- Improved sensor-based yield maps
- Yield maps & yield variability maps for potato and wheat fields located in Belgium
- Essential information for the farmer to optimize crop production (e.g. variable rate fertilization maps)
- Field-level yield estimates and regional yield statistics for at least 5 regions over Europe, covering different bio-geographical zones
Partners
Lab partners:
- VITO
- AVR
- CNH
- UGent
Technology providers:
- VTT
- LUKE
- DHI
- VITO
Application area
Target crops: wheat and potatoes
Target areas:
- Precision farming: Belgium
- Upscaling: smaller area in Belgium, France, Germany (wheat), Europe (potatoes)