Predicting crop performance outside observed trial environments remains a central challenge in plant science. However, integrating genotypic data with large-scale environmental characterization—spanning weather, soil, and satellite-derived variables—enables accurate prediction across diverse and previously untested conditions. This work extends traditional genotype × environment × management (G×E×M) frameworks by capturing environmental characteristics at high resolution, allowing inference beyond the set of observed trial locations. I will discuss implications for variety placement, entry into new production regions, and reducing reliance on extensive field trials, highlighting how predictive models can directly inform real-world crop deployment decisions.

The seminar will start at 14:00 am in the lecture hall plus Video stream via Zoom.

Speaker: 

Prof. Dr. Eric Lam (Department of Plant Biology School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ/USA)