DiPredict – Digital intelligence for the wheat of tomorrow

Wheat is the most important crop in Saxony-Anhalt – and faces enormous challenges: In particular, increasing drought stress events require varieties with stable yields under more difficult conditions. To this end, DiPredict is developing a unique system of digital phenotyping, AI-supported modelling and targeted selection to fundamentally accelerate the breeding of climate-resilient wheat varieties.

At the heart of the project is a multidimensional Datacube in which sensor data from multi-temporal drone overflights, genome sequences as well as ground and weather data are fused. Various drone-based sensors (including multi-/hyperspectral cameras, LiDAR and thermal sensors) record a diverse set of wheat genotypes at numerous locations in Saxony-Anhalt, supplemented by experiments to model water use efficiency in the plantarray system at JKI Quedlinburg. With the help of machine learning and other AI methods, predictive models for genotype×environment interactions are developed, enabling breeding companies to select genotypes for variety development in a faster, more targeted manner. In addition, conclusions are drawn as to the conditions under which sensor technology can be used with maximum effectiveness in order to enable transfer to practical breeding.

DiPredict project website

DiPredict is funded by the European Regional Development Fund (ERDF).