Introduction: Wine cultivation is well established in several European countries, but changing climate conditions put pressure on it, and rising temperatures have enabled the expansion of viticulture into new regions. The changing environmental and regional conditions in which viticulture is practised create new challenges, including those related to disease and pest management, as well as the availability of skilled labour during the harvest and pruning seasons. Additionally, as in the whole agronomic sector, there is an increasing demand for sustainable farming practices. Technological advances, such as those of artificial intelligence (AI), precision farming, and robotics, can help solve these challenges. Methodologies: We use agricultural robots to automate the data collection process and the practical field validation of newly developed AI algorithms. Output: • Toolbox for automated synthetic vineyard generation enabling rapid modification of 3D vineyard models, scenes, and other configurations. • Hyperspectral imaging dataset of Brix and acidity values of grapes with hyperspectral scans in lab and field conditions. • Dataset of a calibrated LiDAR camera sensor setup with robot odometry data and robot behavior in a vineyard. Impact: Precision viticulture and robotics begin with accurate data collection and robust sensor- data processing. High-quality datasets enable researchers, manufacturers, and technology providers across different wine-growing countries to develop and validate new, practical solutions to regional problems. Thereby, benchmarking datasets are fostering cross-border innovation by facilitating the development and comparison of results. What I can offer: As ILVO we offer a large agronomic knowledge-base, vineyards for primary data collection and early testing, and robotic solutions for automating data collection and conducting field tests. What I need: We like to interact with other research groups that see potential in these datasets, in order to refine dataset requirements and support AI research as much as possible. We are interested in dataset exchange to validate newly developed AI algorithms in different countries and field conditions.

Source: Annual AgData Use Case Summit 2026 booklet.