Empathy in the Soil, Agents on the Desktop: Why Plant Pathology Needs a Scientist-in-the-Loop AI Paradigm

Plant pathology faces a cognitive bottleneck caused by the growing volume of biological data. Addressing it requires a shift from passive chatbots to autonomous AI research agents that operate in Goal-Action-State cycles. Researchers can set up a local, desktop-based agentic framework that combines semantic discovery, LLM-Wiki knowledge synthesis, and in silico prevalidation, managed under a human-directed three-tier organizational model. Strict “Scientist-in-the-Loop” boundaries, which means that a human researcher sets the goals, reviews AI-generated output before it is treated as evidence, and approves any consequential action, preserve human academic rigor and control, so plant pathologists can leave routine data processing to the system and focus on creative hypothesis design and physical validation.