Project description

The major challenge addressed is the systemic mismanagement of nitrogen (N) fertilizer in agricultural fields leading to problems such as leaching of nitrates into groundwater and emission of harmful greenhouse gases. Digital technologies are commercialized in agriculture (available from the early 1990s) but have failed with N fertilization. Despite agriculture is the least digitized sector (as highlighted at the last World Economic Forum) to make a reliable recommendation, researchers need to extract and simplify complex science into practical and relevant information enabling advisors and farmers to use such information to make N recommendations for individual fields.

But severe bottlenecks in research, development and application of precision agriculture cause key research to be disconnected. With this project we propose to develop a framework that explores and fills the gaps within the system. We focus on ways to a strategic and tactical N management that maximizes farmers’ income and minimize N leaching and greenhouse emissions.

The main outcome of the project is a research infrastructure (On-Farm Experimentation and On-Farm Research) encouraging involvement of key stakeholders that will generate the data needed for this better understanding. Currently, more than 30,000 farmers worldwide take part in On-Farm Experimentation and On-Farm research meaning that there is real effectiveness in engaging, scaling and creating value for farmers. The project will show a way in which farmers can substantially lower the environmental footprints while maintaining economic viability. This research infrastructure will also be used beyond this proposed project to include other agronomic issues (e.g. agrochemicals, weeds management) and for educational purposes for the new BSc and MSc degrees at Aarhus University targeting Green Transition and the creating of a living lab for educational purposes.

The objectives of the proposed project are: a) Developing a N management system that minimizes N losses in arable farming. This is achieved by combining sensing of soil and crop at high spatial and temporal resolution with crop-soil models; b) Strengthening collaboration among soil and plant research on precision agriculture within Denmark aimed at supporting the green transition; c) Capacity building through establishing a long-term on-farm experimentation platform that supports research, teaching and stakeholder interactions.

The main novelty of the project is that observations and modeling are combined using a digital twin (DT) approach. A DT provides not only a real-time, up-to-date view of the state of crop and soil, but also allows to make predictions about future states of the system under different management options.

The main measurable success criteria are: i) improved and validated measurements of our proposed frameworks; ii) establishment of research infrastructure for precision agriculture (and linkages with the On-Farm Experimental international network); iii) students (PhD, MSc) graduation, publication, and presentation at conferences.

The main outcomes are: i) a comprehensive and system-based approach to site-specific crop N management to reduce N losses while maintaining harvested yield and crop quality; ii) more frequent and efficient interactions with key stakeholders; iii) better documentation of environmental footprints; iv) enhance interdisciplinary collaboration within and beyond Denmark. The outcomes will achieve a desired change that in the long-term vision (beyond the life of the proposed project) enables farmers and policymakers to use data and modelling tools to support the implementation of farming practices that improve crop production and quality, while reducing environmental and climate impacts.