4 Minute read
The prediction of crop yield can be improved by correcting model simulations with measurement data using data assimilation methods. In this project, new data types captured by stationary and mobile cosmic-ray probes, and sun-induced fluorescence will be used for this purpose.
The improved quality of weather predictions for the next month and next three months will be evaluated at several study sites in Australia and Germany. It will be evaluated to which degree crop yield prediction is already possible at the beginning of the growing season (with seasonal weather predictions and initial soil moisture content), and to what degree it can be improved later in the growing season (with data assimilation).
Graduate researcher profile: Theresa Boas
- The University of Melbourne: Professor Andrew Western, Professor Dongryeol Ryu
- Forschungszentrum Jülich: Professor Harrie-Jan Hendricks Franssen, Dr Heye Bogena
First published on 12 May 2022.
Share this article
Studying how calcium channel blockers can protect against brain disease
How can we optimise a calcium-blocking compound to treat Alzheimer's?
The role of attention in predictive visual motion processing
How does attention affect predictive mechanisms in our visual cortex?
Development of next generation fertilisers and their interactions with the soil/plant system
How can we develop more effective fertilisers for future use?
Molecular mechanisms of microbe-enhanced plant performance under nitrogen limitation
How can we reduce our reliance on environmentally-unfriendly nitrogen fertilisers for farming?