AGES has been closely involved in the monitoring of flavescence dorée from the outset:

AGES is the only laboratory in Austria capable of definitively confirming the disease using accredited methods. This is because, depending on the grape variety, the symptoms are not always clear-cut: for example, the symptoms cannot be distinguished with the naked eye from another disease caused by phytoplasmas (Stolbur). This disease is widespread in Austrian viticulture and makes monitoring activities extremely difficult.

The disease was first detected by AGES in Styria in 2009. Since then, it has spread inexorably northwards, mainly because a new strain of the pathogen emerged in 2018: it is now present throughout Burgenland, and this year it was also detected for the first time in Lower Austria.

AGES has also been carrying out specialised monitoring for a very long time to track the occurrence and spread of the American grapevine leafhopper. In 2004, the American grapevine leafhopper was first detected in Austria in southern Styria; in Burgenland in 2010; and in Lower Austria the following year.

If flavescence dorée is suspected, the official provincial plant protection service must be notified. The competent authorities will then take the necessary measures to eradicate or contain the disease. As the disease cannot be effectively controlled in the field, infested vines – and, once a certain damage threshold is exceeded, even the entire vineyard – must be grubbed up to remove the sources of infection from the vineyard.

Video: Sampling

A current research project by AGES aims to develop, evaluate and implement, in a practical context, AI-based detection tools for flavescence dorée and the American grapevine leafhopper. The aim is to provide effective support to plant protection services and winegrowers in the surveillance, monitoring and control of these pests. 

To this end, aerial drone imagery from high-risk areas is being used to compare AI-based analysis systems in terms of operational capability, robustness, and localisation and detection accuracy under various topographical conditions. For practical application, a ground-based, tractor-mounted imaging system with AI-supported open-source software is also being developed, enabling cost-effective real-time detection during regular farm operations. A further AI application for the automated detection of adult grapevine leafhoppers on sticky traps significantly reduces the analytical workload and extends monitoring to the farm level.

The aim is to improve the early detection of infestation hotspots within a region or a vineyard area, to apply control measures in a more targeted manner and, in doing so, to make a significant contribution to the protection of viticulture.