Help us predict the UK's next wheat disease outbreak
A new AI forecasting competition aims to improve prediction of major wheat diseases and support agricultural decision-making
The SPHERE-PPL Forecasting Contest, a collaboration between ADAS, Imperial College, and Defra, challenges participants to build models capable of forecasting the severity of Septoria tritici blotch and yellow rust across the UK during the 2026 growing season.
SPHERE-PPL aims to advance the application of AI forecasting to tackle real-world environmental and health challenges. A key part of the programme is running open forecasting contests to bring together interested researchers and data scientists.
Why forecasting wheat disease matters
Septoria tritici blotch, caused by Zymoseptoria tritici, and yellow rust, caused by Puccinia striiformis, are among the most significant diseases affecting UK wheat production. In severe outbreaks, yield losses can reach 50% in susceptible untreated crops.
Together, these diseases are estimated to cost the agricultural sector more than £250 million each year through crop losses and fungicide expenditure.
It is hoped that improving forecasts will help farmers, agronomists, and policymakers anticipate outbreaks earlier and make more informed, pre-emptive management decisions before significant damage occurs.
An open challenge for researchers and data scientists
The contest is open to anyone with a background in data science, statistics or machine learning and an interest in agricultural applications.
Participants will develop reproducible forecasting models and compete for awards recognising the most accurate predictions of Septoria tritici blotch and yellow rust, as well as the most insightful accompanying report.
Winning teams will be invited to present their work at the next SPHERE-PPL Annual Meeting, with travel costs covered.