Newest papers

Bombadil: A Foundation Model for Plant Electrophysiology

James Kirk, Piotr Bednarski, Filip Twardy, Justin Mast, Lee von Kraus · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.26597 · cited by 0 works (OpenAlex) · open-access PDF

French

Les plantes vivantes, comme les animaux, utilisent des signaux électriques pour transporter des informations sur leur état physiologique à travers leur corps, des racines aux branches. Ces signaux peuvent être enregistrés, comme ils sont chez les animaux, à partir d'une paire d'électrodes extracellulaires différentielles insérées dans le tissu conducteur de signaux. Alors que les modèles d'apprentissage automatique ont été formés pour prédire des états de stress spécifiques des plantes à partir de ces signaux, chacun de ces modèles a été formé pour une seule tâche et aucun n'a été conçu pour transférer des tâches, des espèces ou des environnements. Ces approches ne permettent pas une échelle facile à travers une large gamme d'espèces

Machine translation (Meta M2M100); the English original follows.

Abstract

Living plants, like animals, use electrical signals to carry information about their physiological state across their body, from roots to branches. These signals can be recorded, as they are in animals, from a pair of differential extracellular electrodes inserted into signal-conducting tissue. While machine-learning models have been trained to predict specific plant stress states from these signals, each of these models has been trained for only a single task and none have been designed to transfer across tasks, species, or environments. These approaches do not allow easy scaling across the wide range of species and environments that are relevant to agriculture, forestry, and horticulture for both commercial and consumer plant care. Here we present Bombadil, a foundation model for plant electrophysiology, pretrained without labels on over 4 million hours of electrical signals recorded from 100 plant species in ten distinct environments, including laboratories, greenhouses, commercial orchards, and natural forests. In this way, Bombadil is able to learn the fundamental features of plant electrical signals across a wide array of species and environments. Then, from those same electrical signals, Bombadil tracks changes in seven physiological indicators of plant stress, even among species and stressors with no labels in training.

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Topics: Plant species, Plant life, Task (project management), Engineering, Foundation (evidence), Range (aeronautics)

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