The 2022 Outstanding Student and PhD candidate Presentation (OSPP) Award is awarded to Mercy Appiah for the poster/PICO entitled:
The impact of high quality field data on crop model calibration (Appiah, M.; Bracho-Mujica, G.; Svane, S.; Styczen, M.; Kersebaum, K.-C.; Rötter, R. P.)
Mercy Appiah is a final year PhD-Student at the Department of “Tropical Plant Production and Agricultural Systems Modelling (TROPAGS)” at the University of Goettingen, Germany. Under the supervision of Prof. R.P. Rötter, Prof. S.Siebert, Dr. Bracho-Mujica and Prof. T. Beissinger she works on “Linking crop modelling and experimentation to fully utilize genotypic diversity in barley for climate change adaptation in Europe”. In the framework of the EU-funded projected “BARISTA” she researched on major steps contributing to crop model assisted ideotyping which can accelerate the breeding of resilient barley cultivars that are adapted to changing production conditions. These steps include mapping agroclimatic conditions for barley to see where ideotypes could be useful and improving the tools necessary for ideotyping such as crop simulation models. Part of crop model improvement is to reduce the sources of model uncertainty, like poor quality of model input and calibration data. By using high quality calibration data from model guided field experiments not only the prediction results for known and unknown environments improves notably but also possible model deficiencies, like wrong formulation of physiological processes, can be detected as she laid out in the short presentation held at the EGU 2022.