The Governors of the University of Calgary

Published purpose

The proposed Grant & Contribution project aims to perform essential computational analyses in support of the PeaCE (Pea Climate Efficient) project approved by Genome Canada. This entails evaluating the genetic variation present within the Climate-Smart Pea Germplasm Resource (CSPGR), a collection comprising 2000 lines. The project also seeks to develop an advanced genomic prediction framework for peas, with the potential to expedite the breeding cycle and facilitate the integration of greater genetic diversity into breeding programs. To achieve this, the project will employ a combination of cutting-edge statistical models and artificial intelligence/machine learning (AI/ML) algorithms to analyze genomic data and predict crucial traits in peas, including disease resistance, stress tolerance, yield potential, and other significant agronomic characteristics. By leveraging these computational tools, the project aims to enhance the efficiency and effectiveness of pea breeding programs.