3D modelling of maize to design high-yielding ideotypes for future environments

Global food security is increasingly challenged by population growth and climate change. To help address this, my PhD research explores how maize plants can be designed to achieve high yields under future climate conditions. I developed a digital 3D model of the whole maize plant that links the structure of the canopy and the root system with genetic information. Using virtual experiments, I identified two simple but powerful parameters: how efficiently leaves fill canopy space (canopy occupation volume, COV) and how roots explore the soil (root occupation volume, ROV). These parameters strongly predict how well plants capture light and take up nitrogen. By applying the whole plant maize model, I identified plant designs that perform best in specific environments by balancing above- and below-ground growth. This approach helps breeders predict promising genetic combinations for future climates and supports the development of high-yielding, climate-resilient maize.