Scottish seed potatoes are a premium global product, and the industry underpins UK potato production that is worth an estimated £4-5bn across all upstream and downstream sectors. The sustainability of this industry is under threat, however, due to increasing levels of potato virus Y and potato leaf roll virus.

These viral diseases are transmitted by aphids, and they cause growth disorders, leaf symptoms, and yield losses. The recent increase in the occurrence of these diseases is likely due to multiple factors, such as climate change, the loss of important aphicides, and a general lack of coordinated management strategies, including accurate predictive models to support decision-making. Current methods used to forecast these diseases at a national scale do not offer sufficient resolution to tackle localised virus health issues.

This project will employ state-of-the-art machine learning techniques to develop improved models for forecasting these diseases and contribute to a better understanding of virus epidemiology, which will support management strategies to reduce disease impacts.