Sustainability Through Innovation

In this new project, the bar is set higher. In addition to drones, researchers will now also use satellite images, ground sensors, and camera footage to detect plant diseases. By combining various technologies, it is expected that it will become possible to accurately identify which plants require protection — and, importantly, which do not.

The ultimate goal is for growers to easily integrate this technology into their operations, allowing diseases to be detected at an earlier stage and enabling crop protection products to be applied more efficiently, sustainably, and with high precision. This could potentially result in significant cost savings and reduce the risk of crop losses.

New Drones

The current drones fly relatively slowly and low over fields to ensure the quality of the collected images, which must be accurate down to the millimeter. In the next phase of the project, researchers will explore how this process can be accelerated to map larger areas more efficiently.

By utilizing new data collection techniques and combining these results with other data sources, the researchers hope to gather information faster and more efficiently.

Additionally, the use of so-called ‘drone boxes’ is being investigated. These automated systems enable drones to perform scheduled flights without a pilot. The drones are kept on standby in a protected ‘box’ near the fields and can take off at any desired moment for real-time data collection.

“The first phase has brought us further and provided more insights than we had dared to hope, thanks in part to the collaboration with all stakeholders. I believe that technological knowledge in floriculture, with its complex business and sustainability challenges, can not only contribute to solutions but also create new revenue models for the region,” said Theo de Vries, Director of Unmanned Valley. “Winning a prestigious technology award highlights that our approach is successful and that our results are gaining attention even beyond the floriculture sector.”

Data from Space

The quality of satellite images has improved significantly in recent years. This development offers valuable large-scale insights that can play a meaningful role in precision agriculture. In addition, satellites provide crucial data on environmental factors such as weather conditions and soil moisture. Satellite data presents new opportunities to accelerate the practical application of this project’s results for growers.

Expansion

The new research will expand significantly compared to the initial project. In addition to drone and satellite data, researchers will explore other effective methods for collecting relevant data for the AI model. This includes cameras on tractors, agricultural robots, and ground sensors.

By combining these data sources, the goal is to eventually predict the development and spread of diseases.

While the initial focus was on detecting Botrytis in tulips and hyacinths, the scope is now being broadened. Researchers will now assess which other crops and diseases the model can be adapted for, making the technology widely applicable both within and beyond the floriculture sector.

The Agriculture of the Future

The coming year will focus on gathering new data. Researchers will be frequently present in the fields as soon as spring arrives. The newly collected data will be used to further refine the model. In addition, efforts will be made to translate the technology into practical solutions so that growers can easily apply the models with their existing equipment.

The RS4F team expects to present the results around December 2025.

End of Press Release