Austria Develops AI Tools to Detect a Vineyard Disease Before It Spreads

The system uses drones, tractor cameras and trap analysis to spot flavescence dorée, which reached Lower Austria this year.

Tuesday, September 15, 2026

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Austria Develops AI Tools to Detect a Vineyard Disease Before It Spreads

Austria’s Agency for Health and Food Safety, known as AGES, said it is developing artificial intelligence tools to detect flavescence dorée, a grapevine disease that can destroy vineyards within a few years and spread across an entire growing area in a single season.

The agency said the project is focused on earlier and more practical detection of both the disease and the insect that spreads it, the American grapevine leafhopper. The work combines drone images from high-risk areas with a tractor-mounted imaging system and open-source software designed to identify infections during routine field work. AGES is also testing an automated system to detect adult leafhoppers on sticky traps, a step the agency said could sharply reduce the amount of manual analysis needed in monitoring programs.

Flavescence dorée is caused by phytoplasmas, bacteria-like organisms that lack cell walls and depend on host plants to survive. In wild plants, they often cause few visible symptoms. In grapevines, AGES said, they can be far more destructive and may kill a vine within a few years. The disease affects vineyards because the American grapevine leafhopper feeds on infected vines, picks up the phytoplasmas, and then transmits them when it feeds again on healthy plants.

That transmission cycle makes the insect central to the spread of the disease. AGES said the leafhopper lives almost exclusively in vineyards. Once it is present in an infected area, it can help move the pathogen quickly through a vineyard, turning what starts as a small outbreak into a much larger problem before symptoms are fully understood.

AGES described flavescence dorée as a major threat to viticulture in Austria. The agency said the disease was first detected in Styria in 2009. Since then, it has continued to move north. AGES said that spread accelerated after a new strain of the pathogen emerged in 2018. The disease is now present throughout Burgenland and was detected for the first time this year in Lower Austria.

The insect vector has also expanded its range in Austria over time. AGES said the American grapevine leafhopper was first found in the country in southern Styria in 2004, then in Burgenland in 2010, and in Lower Austria the following year. Those findings have made long-term surveillance of both the disease and the insect a central part of plant protection work.

The agency said it has been deeply involved in monitoring from the start and is the only laboratory in Austria that can definitively confirm flavescence dorée with accredited methods. That role is important because symptoms in the field are not always clear. According to AGES, visible signs can vary by grape variety and may be impossible to distinguish with the naked eye from another phytoplasma-related disease, stolbur, which is widespread in Austrian vineyards.

That overlap has made routine monitoring more difficult. A vine with yellowing or other stress symptoms may not be easy to classify in the field without laboratory confirmation. By trying to automate parts of the search process and improve the precision of visual detection, AGES is aiming to help plant protection services and growers find likely cases sooner and direct testing to the most urgent areas.

The research project uses aerial drone images to compare AI-based analysis systems under different topographic conditions. AGES said the work is evaluating operational use, robustness, and the systems’ ability to locate and identify likely disease cases in varied terrain. The ground-based system is being built for practical use on tractors during normal farm operations. The agency said that approach is meant to lower costs and allow near real-time detection in the vineyard instead of relying only on later review of samples and images.

AGES said the automated detection of adult leafhoppers on sticky traps is another part of the effort. That tool is intended to reduce the workload tied to manual counting and identification while extending monitoring more directly to the farm level. In practice, that could allow growers and local authorities to identify infestation hot spots inside a vineyard or across a wider region faster than with traditional methods alone.

The timing of detection matters because control options are limited once the disease is established. AGES said flavescence dorée cannot be effectively controlled in the field. When infestation is confirmed, infected vines must be removed to eliminate sources of infection. If damage passes a certain threshold, the entire vineyard may have to be grubbed up. That makes early intervention especially important, since a delayed response can raise both economic losses and the risk of spread to neighboring plots.

Under Austrian plant protection rules, suspected cases must be reported to the official provincial plant protection service. Authorities then decide what eradication or containment measures are required. The new detection tools are being developed as support for those services as well as for winegrowers, not as a replacement for official diagnosis.

The work also matters beyond plant health policy. Grapevines are the basis of the wine business, and a disease that forces vines or whole vineyards to be removed can affect grape supply, production planning, and investment decisions across the beverage sector. Better surveillance and faster identification of outbreaks could, if the systems work as intended in daily use, help limit losses, cut the burden of analysis, and shorten the time between the first signs of trouble and official action.

AGES said its goal is to improve the early detection of infestation hot spots and make control measures more targeted. In a vineyard economy where visual inspection is labor-intensive and disease symptoms can be confused with other disorders, the agency’s use of AI reflects a broader push to move plant monitoring from reactive testing toward continuous and operational screening in the field.

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