Leveraging long-term field experiments and other datasets to develop AI-ready decision support systems for sustainable soil management

Expected Outcome: Activities under this topic will help progress towards the objectives and targets of the Mission Soil and the EU Soil Strategy for 2030 . Activities should also contribute to the implementation of the Soil Monitoring and Resilience Directive after its adoption. Project results are expected to contribute to all the following expected outcomes: enhanced adoption of impactful sustainable soil management solutions and strategies supported by AI-powered decision support systems by land managers; harmonised, standard, robust, interoperable and accessible methods, protocols and logical architecture for long-term field experiments (LTEs) data collection and integration (including with other datasets) are in place; scientists, policymakers, and land managers gain enhanced access to comprehensive, high-quality soil data, enabling better research, informed decision-making, and effective land management practices. Scope: Long-term field experiments (LTEs) can be defined as “agricultural experiments for monitoring soil and crop properties under changing climate conditions and different management with a minimum duration of 20 years” [1] , [2] . LTEs are typically owned or managed by public research institutions. Long-term field experiments provide valuable information on soil health and sustainable soil management practices and can be considered critical infrastructure for agricultural research. However, LTEs present some limitations or needs to maximize their impact. There is a need for standardized methods in collecting and reporting soil data to ensure consistency and comparability across different studies and regions. Opportunities exist to integrate soil data from long-term field experiments with other data sources (including the Mission Soil projects results, but not only) to provide a more comprehensive understanding of soil health dynamics and trend, as well as response to policies and management strategies. Enhancing the accessibility and interoperability of soil data across platforms and sources can facilitate collaborative research and accelerate advancements in soil health management. More high-resolution temporal and spatial data are needed to capture short-term soil dynamics and site-specific variations that can influence broader interpretations of soil health trends. On the other hand, independent advisory services on soil health for land managers often face challenges such as limited access to comprehensive data, variability in expertise, and the inability to provide tailored recommendations specific to diverse local conditions. Thes…