Introduction Proximal soil sensing systems (PSSS) can only demonstrate their full potential a) if they are applied in the field (in-situ) and b) if calibration function exist, which convert sensor readings into relevant information for soil management. However, due to limitations of the existing sensors and their measurement principles as well as the various sources of noise during in-situ measurements are making calibration in PSSS very difficult. Methodologies The overarching aim is to provide means to evaluate the performance of single or multiple PSSS with regard to site-specific variable-rate applications (e.g. variable-rate liming, fertilization, irrigation, seeding, variable- depth tillage, seeding). • Use mobile in-situ sensor data (e.g. GCR, EMI, pH, VNIR, gamma). • Connect to best management practices (fertilization etc.). • Evaluate utility of the sensors (uncertainty and sensitivity analysis). Output • Database containing sensor data, reference, meta-data and algorithms. • Algorithms (in Python) covering the whole workflow (import, calibration, recommendation), e.g. site- specific liming. Impact Based on data and algorithms provided, the users should be enabled to: • Select the most suitable sensors for a particular task. • Test and select sensor data (pre-)processing algorithms. • Test and select sensor data fusion algorithms. • Test and select sensor calibration algorithms. • Make cost benefit calculations. What I Can Offer • Mobile in situ PSSS datasets acquired under practical field conditions (GCR, EMI, VNIR, pH, gamma). • Reference data. • Recommendation algorithms for P, K, Mg and lime according to the best management practices in Germany • Calibration algorithms • Experience with field-based soil sensing and site-independent calibration approaches. • Benchmarking opportunities for evaluating mobile soil sensing technologies. What I Need • Data (sensor + reference) • Recommendation algorithms according to best management practices / national law. • Funding of future research on PSSS

Source: Annual AgData Use Case Summit 2026 booklet.