In January 2025, HelEx presented its work on pollinator detection models during the annual meeting of Phenome-Emphasis, the French national plant phenomics infrastructure. This infrastructure connects major phenotyping platforms and fosters methodological exchanges between leading teams in plant science and engineering.
Nicolas Langlade (INRAE) introduced HelEx Work Package 1.2 activities, including the machine-learning models developed to detect and classify pollinators from field imagery. These models are part of HelEx’s broader effort to turn biodiversity monitoring into a scalable and objective component of sunflower breeding.
For HelEx, this kind of engagement with the national plant phenomics community ensures that the project’s tools are developed in coherence with wider standards and can be reused beyond sunflower, strengthening the long-term legacy of the project.
