Miscanthus AI - Plant selection and breeding for Net Zero

Aberystwyth University

Human selection of crop plants for particular purposes such as food, fibre and fuel has already transformed our world, substantially relieving global hunger during the 20th century but arguably at very significant cost to the global environment from the negative impact of energy inputs and CO2 release from the soil due to changes in agricultural land use. However, intelligent and rapid exploitation of plant diversity, either as crops within intensively managed agriculture or as components of more natural ecosystems, holds promise in addressing NetZero. Breeding and technology play a major role, minimising inputs such as fertilisers while reducing handling costs in both food and biofuel crops. Genetic changes, whose performance benefits accumulate exponentially across time, represent an excellent investment. Predictive genetic x environment interaction modelling, based on multiple sources of spatio-temporal data (genomics combined with phenomics and environmental information across time and space) holds great promise for accelerated breeding in biofuel crops, many of which have not historically been subjected to selection and breeding. State-of-the-art plant breeding now interrogates vast quantities of data to understand how the plant genome leads to specific phenotypes or crop traits. However, the application of advanced artificial intelligence to this domain has been relatively unexplored. This project aims to integrate a suite of AI technologies across the plant breeding system, using Miscanthus as the key use case. "