In this age of artificial intelligence models, mechanistic crop growth models are more important than ever. Plant and crop growth simulation models are now a basic tool for many researchers. Yet, there is a shortage of model developers, scientists with knowledge about underlying mechanistic processes and skills to transform this knowledge into scientific equations and sound models. Such modelling skills are highly demanded in the labour market. Many of the more commonly used mechanistic crop models have a challenge to cope with climate change factors such as increased CO2, droughts and floods, temperature, variability, extreme events, and especially the interaction among these factors. There is, therefore, an urgent need to train the next generation of scientists on the further development of dynamic crop simulation models. This post-graduate course focusses on just that. Crop models refer to models that deal with crops, contrasting with e.g. virtual plant models that are focussing on interactions between individual plants. Together with international senior scientists in crop modelling, participants will take up the challenge to acquaint themselves with the process of crop modelling and to develop new insights to strengthen current crop models. We start with theory and concepts and state-of-the-art lectures on the key processes of crop growth to be modelled (and how) and we will also address the importance of both model calibration and evaluation and associated data requirements.
Research School for Socio-Economic and Natural Sciences of the Environment