Fostering Innovation: BUas and NPEC Collaboration at UU Drives Student-Led Advancements in Phenotyping

A collaboration between Utrecht University, BUas, and NPEC has led to groundbreaking advancements in root phenotyping using deep learning, computer vision, and robotics. The expanded HADES system exemplifies how interdisciplinary teamwork can transform agricultural research and make phenotyping more accessible.

A special shoutout to Borislav Nachev, Fedor Chursin, Francisco Mansilha, Vlad Matache, and Wesley Van Gaalen, the dedicated students from Breda University of Applied Sciences, with whom we’ve been collaborating for the past year at Utrecht University. The tools they developed, combining deep learning, computer vision, and robotics, have significantly extended HADES’ capabilities, leading to novel root phenotyping methods that we’re excited to showcase soon. The coordinators from BUas (Alican Noyan, Dean van Aswegen, and Donald Jason Harty) and NPEC (Vinicius Lube, Marciel Pereira Mendes, and Valérian Méline) played an essential role by providing structure and guidance, which empowered the students to overcome challenges and ultimately ensured the project’s success.

HADES has been instrumental in advancing our research with Arabidopsis thaliana and crops like potato plants, providing fully autonomous imaging and trait acquisition, along with automated pathogen or growth-promoting bacteria inoculation. A final acknowledgment goes to Yang Song and Corné Pieterse from the Plant-Microbe Interactions (PMI) group at Utrecht University for their resource allocation contributions. Their students, along with those from BUas, provided the precise trait labels essential for modeling through our deep learning segmentation model.

We’re eager to apply the insights gained from HADES to our open-source modular system, making cutting-edge phenotyping more accessible and replicable for researchers around the world, and enabling everyone to leverage affordable high-throughput phenotyping solutions in their setup.

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