Versatile and user-centered concept for temporally and spatially adapted nitrogen application based on multiple parameters

Crop nitrogen (N) demand is defined by various physiological, management and environmental factors that interact with each other and involve temporal and spatial dynamics. Variable rate N application (VRNA) intends to address this but the underlying algorithms often remain rather rigid and deterministic, are partly subject to high uncertainties and largely leave the agronomic expert’s knowledge and experience unnoticed. A novel generic system architecture was conceptualized to overcome these limitations and respond to the complexity of N management in a straightforward and both, reactive and proactive manner. Having a fuzzy expert system as methodical core, the approach mainly relies on human input to grasp the circumstances at a specific N application and address the required parameter interactions. As a holistic concept, it further aims at a high versatility in terms of considered input data and utilization with different sensor and application technology, as well as a digitized VRNA process chain involving graphical user interfaces to simplify procedures for data presentation, decision making, application and documentation. Bringing the presented concept into a prototypic implementation considering real-time crop N sensor and mapped soil data, its consistency was verified. At the same time, potential functionalities, as well as limitations were illustrated and technical requirements on specific subsystems were clarified by the prototype. The possible risks that stand in the way of high benefits due to a strong focus on expert knowledge can be countered by using digital tools and heading towards hybridization with other VRNA approaches. •Novel generic system architecture for digitized site-specific N management.•Multi-parametric and differentiated strategies employing a fuzzy expert system.•High versatility in terms of used data sources and application technology.•Prototypical implementation using realistic scenarios to proof the concept’s validity.•Graphical user interfaces for system setup, task management and in-field execution.