Overview
The Digital Future Farm (DFF) project is driving the next generation of farm management with Digital Twin technology and AI-powered decision support. At the Agro-Innovation Centre De Marke in Hengelo, Wageningen University & Research (WUR) hosted an ELSA workshop to explore the ethical, legal, and societal dimensions of the technology.
DFF connects validated models with real-time farm data via the open-source MODCOM framework and integrates farm data spaces through the FarmMaps platform. Collaborating with the agrifoodTEF Dutch Node, the project ensures responsible and scalable digital innovation for sustainable farming.
Arable farming
Livestock farming
About the customer’s need
Farmers are under growing pressure to increase efficiency while meeting strict environmental targets. Current tools fall short when it comes to integrating diverse datasets and predicting complex outcomes such as nutrient flows or environmental impact. To address this, the Ministry of Agriculture, Nature and Food Quality tasked WUR with developing a robust data infrastructure that incorporates farm data spaces and enables the connection of multiple models. This foundation aims to support the creation of digital tools that empower farmers and stakeholders with real-time, evidence-based decision-making capabilities.
About the service
agrifoodTEF, through Wageningen University & Research (WUR), provided an ELSA Scan and facilitated a Quadruple Helix workshop bringing together farmers, researchers, and policymakers. This process identified key risks, governance requirements, and success conditions for adopting Digital Twin technology. Recommendations included enhancing transparency on data access and use, promoting an API-first approach for interoperability, and ensuring fair distribution of financial benefits among data owners.
Discover the ELSA scan service
Watch the agrifoodTEF ELSA scan: Building the Digital Future Farm Together
Impact
The Digital Future Farm project has demonstrated how Digital Twin technology can transform both arable and dairy farming. By mapping nitrogen flows in near real time, farmers gain a clearer understanding of nutrient efficiency and environmental impact. Continuous model validation enhances reliability, reducing operational risks and improving day-to-day decision-making.
The initiative has also established strong governance principles around data ownership, privacy, and distributed access, ensuring trust and fairness among all stakeholders. Farmers report that focusing on grassland management through these models naturally leads to reduced nitrogen losses.
With its adaptable framework and open-source MODCOM technology available on GitHub, the project not only supports sustainable dairy farming but also offers a blueprint for scaling digital innovation across other agricultural sectors and environmental challenges.
Learn more about the Digital Future Farm
This success story showcases how AI and robotics, supported by agrifoodTEF, can benefit agri-businesses. Could your business be the next? Discover our services and join the technological revolution in agriculture.
