Bombadil: A Foundation Model for Plant Electrophysiology
Training one AI to read electrical stress signals from any plant, anywhere
Researchers built Bombadil, a machine-learning model that learns to recognize electrical patterns common to all plants by analyzing 4 million hours of signals from 100 species across labs, greenhouses, orchards, and forests. Once trained this way, the model can detect seven different stress indicators in any plant—even species it never encountered during training—using just a pair of electrodes.
Farmers, orchardists, and plant breeders could diagnose crop stress—drought, disease, nutrient deficiency, heat—days before visible wilting appears, enabling faster intervention. A single standardized tool that works across species eliminates the need to develop separate detection systems for each plant type, making early-warning systems practical and affordable at commercial scale.