09-25, 11:20–11:55 (Europe/Amsterdam), Voyager
The scale-up company Solynta focuses on hybrid potato breeding, which helps achieve improvements in yield, disease resistance, and climate adaptation. Scientific innovation is part of our core business. Plant selections are highly data-driven, involving, for example, drone observations and genetic data. Minimal time-to-production for new ideas is essential, which is facilitated by our custom AWS devops platform. This platform focusses on automation and accessible data storage.
In this talk, we introduce how computer vision (YOLO and SAM modelling) enables monitoring traits of plants in the field, and how we operate these models. This further entails:
• Our experience from training and evaluating models on drone images
• Trade-offs selecting AWS services, Terraform modules and Python packages for automation and robustness
• Our team setup that allows IT specialists and biologists to work together effectively
The talk will provide practical insights for both data scientists and DevOps engineers. The main takeaways are that object detection and segmentation from drone maps, at scale, are achievable for a small team. Furthermore, with the right approach, you can standardise a DevOps platform to let operations and developers work together.
Outline (30 min):
• Introduction to hybrid potato breeding (3 min)
• Challenges/solutions in breeding (5 min)
• YOLO and SAM modelling using drone data (10 min)
• Working together on a DevOps platform (10 min)
• Summary (2 min)