From field testing to confident investment: how AgriFood4Future helps farmers and VET professionals make informed innovation choices

Every year, new agricultural technologies reach the market: RTK guidance systems, spot spraying equipment, autonomous robots, artificial intelligence, sensors and digital decision-support tools. While these innovations promise higher efficiency and lower environmental impacts, farmers, advisors and training organizations all face the same challenge: how can they identify which innovations are truly worth adopting?

The AgriFood4Future project addresses this challenge by connecting innovation, vocational education and training (VET), demonstration activities and capacity building. Rather than simply showcasing new technologies, the project helps stakeholders understand how to assess innovations, interpret independent evidence and make informed decisions.

Learning through real-life experimentation

One of the key strengths of AgriFood4Future is its VET ecosystem, which brings together research organizations, vocational education providers, advisors, SMEs and farmers to create practical learning opportunities.

Within this ecosystem, ARVALIS and FR Cuma Ouest combine their complementary expertise to bridge the gap between innovation and its adoption on farms.

For more than ten years, the two organizations have collaborated to evaluate innovative agricultural equipment under real farming conditions. ARVALIS produces independent technical and economic references through its experimental farms and Digifermes® network, while FR Cuma Ouest transfers this knowledge to farmers through its machinery-sharing cooperatives (CUMAs), advisory services and field activities.

This work directly contributes to Task 3.3 – Open Innovation Test Farm Programme, coordinated jointly by ARVALIS and FR Cuma Ouest. Test farms allow innovative technologies to be assessed under realistic conditions before large-scale deployment, producing reliable evidence that can be used not only by farmers but also by trainers, advisors and vocational education providers.

From testing to demonstration: learning together

Generating evidence is only the first step. Farmers and future professionals also need opportunities to see technologies in action, discuss results and exchange experiences.

This is why VET partners, including ARVALIS and FR Cuma Ouest, regularly organize demonstrations, technical visits and exchanges with farmers, advisors and technology providers. These activities contribute to AgriFood4future Task 3.7 – COVE Networking, Demo Days and Site/Farm Visits by transforming test results into shared learning experiences across the European VET ecosystem.

For participants, these events are much more than technology demonstrations. They provide opportunities to compare solutions, ask practical questions, understand economic implications and learn directly from experts and fellow farmers before making investment decisions.

Two examples of innovation in practice

Cosmic ray neutron sensing probe (Finapp)

The Finapp CRNS (Cosmic Ray Neutron Sensing) probe is an innovative, non-invasive sensor that estimates soil moisture by measuring cosmic-ray neutrons above the ground. It provides continuous measurements over a large representative area and great depth, offering a more comprehensive picture of field water conditions.

Within the AF4F Open Innovation Test Farms programme, Arvalis evaluated the CRNS probe under real farming conditions to assess its performance in monitoring soil moisture. The first results are promising, confirming the reliability of the probe’s measurements and its potential to optimize irrigation monitoring. By providing accurate, real-time information on soil moisture dynamics, the technology can support farmers in optimizing irrigation timing and water application, improving water-use efficiency, reducing unnecessary irrigation, and contributing to more sustainable and resilient crop production.

Affordable RTK guidance systems 

RTK guidance systems enable tractors to return precisely to the same position in the field, opening new possibilities for precision mechanical weeding and innovative cropping systems. New affordable RTK solutions have recently entered the European market, offering lower-cost alternatives to traditional systems.

Within AgriFood4Future, Arvalis evaluates their positioning accuracy and field performance against established commercial references. These independent assessments help farmers, advisors and trainers understand the strengths and limitations of emerging technologies before recommending or investing in them.

Building the skills needed to adopt innovation

Reliable technical results alone are not enough to accelerate innovation. Farmers, advisors and SMEs also need the skills to interpret data, evaluate costs and benefits, and identify the solutions best suited to their own context.

To address this need, AgriFood4Future complements the Open Innovation Test Farms with dedicated capacity-building activities. Task 4.3 delivers a training programme for agricultural advisors, strengthening their ability to assess, validate, and promote innovative technologies while supporting farmers in their adoption. In parallel, Task 4.4 provides a Capacity-building and Technical Assistance Programme for agri-food SMEs and farmers, helping them develop the knowledge and practical skills required to make informed decisions on innovation uptake.

Together, these activities transform the independent technical evidence generated by the Test Farms into practical learning resources, reinforcing advisory services, strengthening decision-making capacities, and accelerating the adoption of innovative and sustainable agricultural technologies.

Towards a Sustainable Expansion of Open Innovation Test Farms

While AgriFood4Future has demonstrated the potential of the Open Innovation Test Farms approach, extending this model to other countries and regions remains an important objective for the future. The experience gained during the project has highlighted that successful replication requires the progressive establishment of key enabling conditions, including suitable infrastructure, dedicated human resources, effective innovation networks, and complementary support structures. Addressing these aspects will be essential to facilitate the transfer and long-term sustainability of the model in diverse agri-food contexts.