Accelerating pulse breeding using machine learning

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Advances in genomics and high throughput phenotyping are generating vast quantities of data that can be applied for crop improvement, however the lack of computational analysis tools and approaches limits the full exploitation of this data. Pulse legumes are currently under utilised in Australian agriculture due to poor adaptation, however they offer significant benefits both for soil improvement and the production of high protein crops. This project will develop machine learning (ML) tools for the analysis of pulse legume crop traits and their association with genomic variation to accelerate the breeding of high performance pulse legumes for Australian growers.