Potato Nematode Decision Support with AI
Root-knot nematode (RKN; Meloidogyne spp.) is a soil-borne pathogen that impacts multiple crops, including potatoes, grown in the Pacific Northwest.
Computational tools are necessary for modeling and analytics for nematode detection, mitigation, and decision support in general.
Two sets of major tasks are being carried out by PAPAS within the computational group using Artificial Intelligence (AI) and machine learning (ML) methods.
Task A: Development of interactive AI tools for querying literature for nematode detection, mitigation, and control for potatoes.
Task B: Development of ML-based data-driven predictive capabilities to predict nematode detection based on field attributes (both management and environment).
Key project personnel:
- Sejal Welankar, Paola Pesantez, Ananth Kalyanaraman, Jordan Jobe (Washington State University)
- Inga Zasada, Ph.D. (Oregon State University)
- Louise-Marie Dandurand, Ph.D. (University of Idaho)
