The global population is rising, generating a need to produce more food to feed the world. Canadian and global food crops are facing growing challenges from climate change including pests, pathogens and viruses that attack and destroy crops.  As the climate warms, diseases such as wheat rust spread further north and create an increasing threat to food production.  The threats are large.  For example, Canada exports more than $7 billion worth of wheat every year. At the same time, increasing the use of pesticides brings risks to the environment.

The goal of the Terramera-led Digital Technology Supercluster project was to tackle crop loss, in partnership with Sightline Innovation, Metaspectral, Canada’s Michael Smith Genome Sciences Centre, Trent University, Simon Fraser University, the University of Saskatchewan, Agriculture and Agri-Food Canada.  Together, the team worked to develop new pest and pathogen controls using computational biochemistry, genomics, machine learning and robotics. Large amounts of data are being brought together in new ways. Machine learning and robotics are being used to quickly identify and test new pest management formulations and determine their ability to attack specific fungi on specific crops

The project initially focused on leaf rust disease, a fungus which attacks some of Canada’s most important crops, including wheat and barley. The computational platform developed helps teams to design antifungal formulations and predict their effectiveness in wheat leaf rust eventually other crop diseases in Canada. Worldwide, more than $85 billion is spent on crop protection. New pest-control products can tap into this market while protecting the world’s food supply and lessening impacts on the environment.