Horizon scanning is a foresight methodology designed to uncover and assess emerging issues before they become full-blown emergencies. In the plant health context, it functions as the initial step in a surveillance pipeline, gathering signals from thousands of sources and distilling them into actionable intelligence for risk managers. The EU system, run by EFSA in collaboration with the European Commission’s Joint Research Centre (JRC) and the French Agency for Food, Environmental and Occupational Health and Safety (ANSES), produces monthly reports known as newsletters. As of 2024, this activity has generated 130 such reports, covering both pests already regulated under EU law and, crucially, unknown or unlisted species that no legislation yet anticipates.

The technological engine behind the monitoring phase is MedISys, the Medical Information System developed by the JRC. Originally built for public health surveillance, MedISys is a fully automatic, event-based system that in 2024 was scanning more than 3,200 scientific and media sources worldwide every day. Manually curated categories, keyed to the scientific and multilingual common names of individual pests, allow the platform to retrieve articles about specific organisms, while generic keywords such as pest, plant disease, crop and yield losses cast a wider net for the discovery of entirely new threats. Articles flagged by the machine are then reviewed and validated by a team of experts before being selected for the monthly newsletter, which is published in the EFSA Journal and presented to the Plant Health section of the EU Commission’s PAFF Committee.

The second stage of the pipeline is a rapid screening procedure called PeMoScoring, short for pest and monitoring scoring. Eligible pests must be capable of damaging plant species of economic relevance to the EU, must be able to enter the territory through at least one import commodity that is not banned or by natural spread from outside the EU, and must not be newly described species. PeMoScoring evaluates 15 criteria grouped into five items: host range, entry, establishment, spread and impact. Each criterion is posed as a question with predefined response options whose scores were calibrated against reference pests, ensuring consistency across assessments. The answers combine into a final net phi value ranging from minus one to plus one, with a threshold separating negative results, meaning insufficient evidence of risk, from positive results that signal a potential threat and can trigger further action by risk managers.

To evaluate how well this machinery has performed, the team compiled every article published in the newsletters between 2017 and 2024 into a database, recording the pest’s biological category, scientific name, regulatory status, article topic, source, PeMoScoring outcome and, where applicable, the country of detection and host plant. The dataset revealed that the 130 reports covered 1,153 pests, of which 836 were not listed in EU regulation or EPPO lists and 317 were regulated. Insects and mites accounted for the highest number of regulated species cited, while fungi and oomycetes stood out as the category in which unlisted species were more frequently reported than regulated ones.

The source analysis yielded instructive patterns. Although the majority of unique sources were media outlets, with 617 compared to 301 scientific sources, the bulk of the articles actually came from the scientific literature: 1,978 articles from journals versus 1,380 from media. For regulated pests, media coverage dominated in the insects and mites category, whereas viruses, viroids and phytoplasmas appeared more often in peer-reviewed publications. For unlisted pests, the scientific literature was generally the richer source, particularly for fungi and oomycetes and for viruses. Notably, a large share of articles came from sources consulted only once, suggesting that casting a wide net across many outlets, even shallowly, increases the volume of relevant intelligence without sacrificing quality.

Topic classification showed that new observations, encompassing first findings, interceptions, new host plants, new pests and new vectors, were by far the most common group, followed by management and then assessment, the latter two being associated predominantly with regulated pests. Among the subtopics, first findings were mainly reported in scientific publications, while new findings, defined as detections of a pest in a different region within the same country, were primarily reported in the media. For regulated insects and mites, the pattern was striking: 97 percent of articles reporting new findings originated from media sources. Of the 392 new pests reported during the exercise, only 27 were mentioned again in subsequent articles, and crops accounted for 67.5 percent of host plant citations, with forests, ornamentals and wild plants making up the remainder.

The PeMoScoring results demonstrate the system’s real filtering power. From 2017 to 2024, 233 pests were scored, with 119 receiving positive results and 114 negative ones. Twenty-seven of the positive pests were proposed for pest categorisation, EFSA’s more elaborate assessment of whether regulatory measures may be required, and 20 of those 27 categorisations returned a positive outcome, with three negative and four inconclusive. On average, it took about three years for a PeMo-positive case to undergo pest categorisation. The proportion of positive scores has declined since 2021, which the authors suggest may reflect improving protective measures, since diagnosis and control options feed into the scoring evaluation.

Perhaps the most vivid illustration of the system’s value is the case of Fusarium oxysporum f. sp. cubense tropical race 4, the soil-borne fungus behind Panama disease in bananas. TR4 scored positive in PeMoScoring as early as July 2017, when its known distribution was limited to eastern Asia and the Middle East, even though bananas are not widely cultivated in the EU. A pest categorisation followed in 2022, concluding that the pathogen met the criteria for consideration as a potential Union quarantine pest. Since then, TR4 has spread to Türkiye, Oceania and, significantly, Latin America, with detections in Colombia in 2019, Peru in 2021 and Venezuela in 2023. In 2024 the pathogen was added to the EPPO A2 list, and the International Plant Protection Convention issued new prevention guidelines covering e-commerce pathways.

Media signals have also proven decisive for other invaders. Reports of the invasive fire ant Solenopsis invicta in Sicily surfaced well before the formal scientific publication, underscoring the potential of integrating citizen science and social media into surveillance. The February 2022 newsletter, meanwhile, carried the first observation of the fungus Neofusicoccum mediterraneum in Italy, a new report of Citrus concave gum-associated virus in the United States, and evidence that barley serves as a host for Chinese wheat mosaic virus. None of these were listed in the EU Plant Health Regulation, yet the procedure triggered a request from the Swedish Board of Agriculture for tailored risk assessments, showing how scanning outputs translate directly into preparedness actions.

Looking forward, the authors argue that the vast dataset accumulated over seven years could support a shift from consequence-to-event tracking toward an event-to-consequence approach, and ultimately toward artificial-intelligence systems capable of pinpointing critical information automatically. A preliminary driver-based study of newsletters published between June 2021 and September 2022 confirmed that global trade is the main driver of pest emergence, and other research points to traits such as polyphagy, heat tolerance, high dispersal capacity and genetic diversity as markers of future risk. Workshops are now being organised to build a plant health horizon scanning community across institutions, and the newsletter data are available through an interactive EFSA dashboard. Limitations remain, including delays caused by constraints in data publication and web scraping, but the overall verdict is clear: seven years of systematic horizon scanning have measurably strengthened Europe’s capacity to anticipate, rather than merely react to, the next plant health threat.

Subject of Research: Horizon scanning methodology for early detection of emerging plant pest threats in the European Union

Article Title: Unravelling potential plant health threats for the European Union: application of horizon scanning methodology

Article References: Ribaya, M., López-Mercadal, J., Campese, C., Sarakatsani, E., & Tramontini, S. (2025). Unravelling potential plant health threats for the European Union: application of horizon scanning methodology. Web Ecology, 25(2), 189-200. https://doi.org/10.5194/we-25-189-2025

Image Credits: AI Generated

DOI: 10.5194/we-25-189-2025

Keywords: horizon scanning, plant health, EFSA, invasive pests, PeMoScoring, MedISys, biosecurity, plant pathogens, risk management, Fusarium TR4, early warning systems, European Union

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