Decoding faba bean yield stability: From in-field image data to mechanistic models (DIGIFABA)
The DIGIFABA project is addressing the critical need for sustainability and climate resilience in agriculture. The primary goal is to increase the cultivation of faba beans—a crucial grain legume—by leveraging state-of-the-art digital technologies thereby improving breeding programs. This will pave the way for faba bean varieties that can maintain stable yields even under the stress of drought, a growing concern in our changing climate. DIGIFABA represents expertise in agronomy, statistics, and machine learning, utilizing images captured in-field and by drones to identify and analyse traits specific to faba beans and critical for yield stability. In essence, DIGIFABA is providing a new path for the future of faba bean breeding. By integrating digital tools and advanced modelling, the project aspires to improve yield stability and drought resilience, thereby contributing to the development of sustainable agricultural practices that will withstand the challenges posed by climate change.