Agriculture is undergoing rapid digitalisation, yet farms continue to face increasing environmental and societal pressures related to soil health, including cleaner water, improved soil quality, better carbon storage, and enhanced biodiversity. A detailed understanding of soil variability is essential for effective decision-making, but current market solutions for soil mapping are often too costly, too complex, or insufficiently aligned with farmers’ needs.
The SQAT project aims to develop an integrated smart soil mapping service that combines multiple technologies to generate high-resolution soil property maps and a range of demand-driven application products, such as variable-rate application maps. The SQAT approach merges in-situ sampling and sensing, deployed on an autonomous robotic platform, with a Copernicus-based artificial intelligence soil mapping engine. This integrated system significantly reduces costs while increasing productivity compared to existing solutions.
The robotic sensing toolbox includes NIR sensors, an automated sampling drill, a penetrometer, and an innovative chamber for in-situ wet chemical analysis (“Lab in the Field”). Based on the produced maps, the project co-develops, tests, and validates five smart farming applications: variable-rate liming/fertilisation/seeding, variable-depth tillage, and carbon farming MRV.
Seven SMEs from across the soil data value chain participate in the project, each leading a use case in different European regions. With a strong market orientation from the outset, the project aims to ensure that results can be commercialised by the end of the project, while actively engaging farmers, agri-service providers, and other stakeholders in the development and adoption of SQAT-enabled smart farming applications.
