FarmerSpaceAI

The FarmerSpaceAI project aims to evaluate, further develop, and clearly communicate AI-based digital technologies in plant protection under practical conditions. The goal is to support more precise, resource-efficient, and environmentally sustainable crop production. The project focuses on innovative approaches to weed control, precise and site-specific crop treatment, and the use of specialized chatbots as digital decision-support tools. A particular emphasis is placed on ensuring that the developed solutions can be transferred to both organic and conventional farming systems.

FarmerSpaceAI is one of the ‘digital experimental fields’ currently underway, aimed at developing AI applications and their use in agriculture. In May 2026, participants from the DIKI-Südwest, EXPRESS.smart and FarmerSpaceAI experimental fields met for a workshop in Darmstadt to establish links between the experimental fields and coordinate the use of large language models (LLMs) in agricultural practice.

The FarmerSpaceAI project aims to achieve the following outcomes:

• Development, implementation, and quantitative evaluation of an LLM (Large Language Model) prototype for digital decision support, including practical validation and assessment of its scalability toward multimodal LLM systems.

• Establishment of a practice-oriented testing concept for AI-based precision applicators, including systematic method comparison, concrete advisory recommendations, and evaluation of transfer potential between conventional and organic weed control.

• Testing of a concept for needs-based, small-scale crop treatment, including practice-oriented recommendations and evaluation of variable rate application (VRA) and site-specific application techniques.

• Assessment of the robustness, transparency, and traceability of the AI systems used through a structured overview of models and datasets, validated data collection, and transparent documentation of decision-making logic.

• Strengthening knowledge transfer through the provision of open-access datasets, scientific and practice-oriented publications, and intensified exchange between academia, industry, and agricultural practice.

Funded by the Federal Ministry of Agriculture, Food and Reginal Identity by decision of the German Bundestag, and by the Federal Office for Agriculture and Food as project manager.

Georg-August-Universität Göttingen, Department für Nutzpflanzenwissenschaften, Abteilung Agrartechnik

Fraunhofer-Institut Optronik, Systemtechnik und Bildauswertung IOSB

Landwirtschaftskammer Niedersachsen

hessian.AI - The Hessian Center for Artificial Intelligence