The factsheet, published by Pensoft Publishers on behalf of the three consortia, opens with a headline that captures the shared ambition of all three projects: technology-driven early detection of biotic stressors threatening European plant health. It is more than a summary document. By presenting each project’s core objective side by side, and by highlighting the thematic lines, technological solutions and methodological approaches the projects have in common, the factsheet offers policymakers, researchers and stakeholders a concise map of where Europe’s digital plant-protection effort stands and where it is heading. The shared vision uniting the three initiatives is that artificial intelligence, remote sensing and citizen engagement can transform how Europe identifies and responds to pest outbreaks.

Each project brings a distinct focus to the partnership. FORSAID concentrates on Europe’s forests, developing a comprehensive framework for the detection, monitoring and management of ten EU-regulated biotic stressor species. The four-year project brings together seventeen partner organisations from ten countries, and it places artificial intelligence and digital technologies at the core of its strategy for mapping the future of forest pest control. Forest ecosystems are particularly vulnerable to regulated pests because once an invasive organism establishes itself in a woodland landscape, eradication is often technically impossible and containment becomes the only realistic option. Early detection is therefore the difference between a manageable incursion and a landscape-scale catastrophe.

CERBERUS addresses the other side of the European agricultural spectrum: Mediterranean crops. The project is building a multi-layer early detection and monitoring system that integrates remote and proximal sensing, ground-based automation and artificial intelligence. Its data streams come from three distinct sources — space, the field and the public — and they feed into the management of both quarantine pests and commonly managed pests across vineyards, olive groves and citrus orchards. The system’s outputs include AI-driven risk maps and spraying recommendations, a combination designed to reduce pesticide use while maintaining effective crop protection. That dual goal reflects a broader pressure on European agriculture, where regulatory targets for pesticide reduction must be reconciled with the economic realities of farming in regions already stressed by climate change.

STELLA completes the triad with a holistic digital platform known as the STELLA Pest Surveillance System, or PSS. The system is designed to support the early warning and early detection of regulated pests, drawing on AI-supported innovations in satellite and UAV-based sensing, in-situ sensor technologies and crowdsourcing. What distinguishes STELLA’s approach is the pairing of detection capability with a response strategy: the project explicitly aims to help stop outbreaks before they can spread, rather than simply documenting them after the fact. In plant health, that distinction matters enormously, because the window between the arrival of a pest and its irreversible establishment can be measured in weeks.

Although FORSAID concentrates on forest pest control while CERBERUS and STELLA focus on agricultural crops, the factsheet demonstrates that the three projects have far more in common than a shared funding call. All three are tackling comparable challenges with overlapping tools. AI-driven risk modelling, remote sensing from satellites and drones, and citizen science monitoring appear in all three portfolios, adapted to different crops and ecosystems. This convergence is not accidental. The Horizon Europe call that funded the projects was designed to build a portfolio of complementary capabilities, and the factsheet makes visible how those capabilities interlock — from the algorithms that interpret sensor data to the networks of observers who report suspicious symptoms in the field.

The collaboration is not confined to documents. The common ground between the projects has already brought their younger generation of researchers together. In June 2025, PhD students and postdoctoral researchers from all three consortia met for a first joint Young Scientist Meeting, where they discussed forming dedicated working groups on citizen science, communication, remote sensing and pest surveillance. For early-career researchers, whose careers often unfold within the boundaries of a single project, such cross-consortia meetings create the professional networks and shared methodological vocabulary that outlast any individual grant. The working groups under discussion signal an intent to institutionalise that exchange rather than leave it to chance encounters at conferences.

Since that meeting, the partnership between FORSAID and STELLA has moved from discussion into the field. In May 2026, the two projects carried out joint fieldwork on the Greek island of Euboea, deploying drone-based remote sensing to evaluate tree health in forests affected by canker stain disease. The campaign illustrates the practical value of the sister-project model: STELLA’s expertise in UAV-based sensing and FORSAID’s forest-focused analytical framework could be combined on a single site, testing how detection pipelines developed for different regulated pests perform when applied to a shared, real-world outbreak. Euboea’s canker-stain-affected forests provided exactly that test case, and the results are expected to inform both projects’ ongoing methodological development.

The technological core shared by all three projects deserves a closer look, because it represents a genuine shift in how plant health surveillance is conceived. Traditional pest monitoring relies heavily on physical inspection by trained surveyors, a labour-intensive process that inevitably leaves vast areas unsurveyed between visits. The approach championed by FORSAID, CERBERUS and STELLA layers multiple observation systems on top of one another. Satellites provide broad, repeated coverage of vegetation condition across entire regions. Drones and UAVs add high-resolution imagery over specific sites flagged by the satellite layer. Ground sensors and automated field platforms capture micro-level signals that aerial systems cannot resolve. Finally, crowdsourcing and citizen science enlist farmers, foresters and the general public as distributed observers, extending the human sensing network far beyond what any institutional survey programme could staff. Artificial intelligence sits at the centre of this stack, fusing heterogeneous data streams into risk maps and alerts that decision-makers can act on.

As all three projects move deeper into their implementation phases, this spirit of collaboration is expected to grow further. The joint factsheet serves both as an introduction to the combined work of FORSAID, CERBERUS and STELLA and as an invitation to explore what a united, technology-driven plant health protection response can achieve across Europe. For a continent whose forests and farms are under increasing pressure from invasive pests and pathogens, the message of the factsheet is straightforward: no single project, technology or institution can provide the early detection Europe needs, but a coordinated portfolio of AI, remote sensing and citizen engagement — spanning forests and farmland alike — can build a surveillance fabric dense enough to catch outbreaks while they are still small enough to stop.

Subject of Research: Technology-driven early detection and monitoring of plant pests and pathogens in European forests and Mediterranean agriculture

Article Title: Safeguarding European plant health: New joint factsheet outlines synergy between Horizon Europe projects FORSAID, CERBERUS and STELLA

Article References: Safeguarding European plant health: New joint factsheet outlines synergy between Horizon Europe projects FORSAID, CERBERUS and STELLA. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: plant health, pest detection, FORSAID, CERBERUS, STELLA, Horizon Europe, artificial intelligence, remote sensing, citizen science, forest pests, Mediterranean agriculture, early warning systems