Plant science has a core responsibility to both preserve the genetic diversity of our crops and to develop sustainable and efficient systems to produce food, energy and raw materials. Decoding the genomes of our leading crop species, specifically those of wheat, barley and oilseed rape, along with documenting their entire life cycle, will help determine the contribution of each gene, both individually and jointly, to the plants’ growth and development. In particular, this knowledge will facilitate a deeper understanding of how changes in either the physical environment (soil and climate) or the genome alter trait expression, be it related to the crop’s economic yield, its resistance to pests or its tolerance of abiotic stress.

Data science and IT have become central to our efforts to obtain meaningful biological insights from the ever-growing volume of genetic and phenotypic data being generated. Their application has the potential to develop the innovations in plant breeding methodology needed to address the pressing issues of feeding the world’s population and maintaining the supply of raw materials and energy.

The group is engaged in developing mathematical models to elucidate the molecular basis of both growth and development, and the regulation of metabolism. The complexity of these processes, along with the large volumes of heterogeneous data involved, require an integrative approach to be taken, in particular targeting the assembly of metabolic networks, which largely underlie trait expression. In addition to the assembly of metabolic models, several in silico-based and mathematical tools are also being used by the group, including graph theory, various statistical methods, machine learning, concepts derived from systems theory and control engineering, and stochastic and deterministic modelling.

Beyond attempting to decipher and understand growth and development, our goal is to develop models able to predict plant performance in response to changes in the environment. Such data- and mechanism-driven models could make a significant contribution to crop improvement as they would support a more rapid breeding response to climate change.