The Governors of the University of Alberta

Published purpose

As the demands for plant-based protein and ingredients are growing, Canada is becoming a leading producer and exporter of field pea. However, climate change is negatively impacting pea yield and seed quality, necessitating the development of climate-resilient pea cultivars. Omics-driven approaches have facilitated crop improvement, but the complex datasets created are highly heterogeneous and beyond the capability of conventional statistical analysis for data integration to develop new insights at a system level. By leveraging data from ongoing SPP projects, the team will use machine learning (ML) to integrate multi-omics data as a means to elucidate molecular mechanisms underlying pea yield and seed quality. Furthermore, predictive ML models will be developed to enable selection and design of climate-resilient pea cultivars, and prediction of functional properties of pea flour. The project aims to advance translation of lab findings and genomic tools to the field, accelerating the development of high yield, climate-resilient pea cultivars with enhanced seed quality.