Yield monitoring


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


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)