Projects

Plants do not function optimally under field conditions, which can in principle be resolved by adapting their microbiomes using microbial productsand minimal synthetic communities. The overall aim of the project is to leverage existing large-scale natural plant microbiome data and potato field-specific data to explore microbiome compositions and to define minimal microbial community structures that are prevalent across the data. Here,natural generalist community compositions can inform on how to possibly adapt and improve field-specific minimal compositions. This will becombined with mechanistic modelling to characterize the biochemical interactions underlying plant microbiome function and composition, in orderto establish and validate this methodology as a framework for improving potato phytobiomes, as well as to explore the community formulations thatcan lead to improved plant performance. Our model system is potato, among the world's most important food crops that exemplifies problems withyield loss and increased pesticide and fertilizer use due to climate change and pathogens. The results of the project will allow us to assess thepossibilities offered by the currently available data and to identify the capabilities or limitations of the mechanistic modelling approach, as well asoptions for improving both the data and modelling approach.