Earlham Institute and Syngenta launch a new Innovate UK-funded project applying AI models to identify novel herbicide targets and improve management of resistance in agricultural weeds.
When agricultural weeds survive herbicide applications that would normally control them, resistant populations can emerge and spread. This can lead to increased herbicide use, greater competition with crops for resources, and the need for more complex management strategies, all of which increase costs and pressures on farmers. As a result, managing herbicide resistance has become a critical challenge for both farmers and the wider agricultural sector.
Funded by Innovate UK’s Knowledge Transfer Partnership award, the new collaboration will see genomics and AI expertise from Earlham Institute embedded within Syngenta’s Jealott’s Hill International Research Centre in Berkshire. The project will use genome large-language models – large-scale AI networks trained on genome sequences to predict patterns, structures, and relationships.
Researchers will focus on predicting and understanding target- and non-target site resistance (NTSR), (a challenging form of resistance where weeds survive herbicides by adapting how they absorb, move, or break down the chemical).
