There is a critical need to reduce the nitrogen (N) footprint from corn-based cropping systems while maintaining or increasing yields and profits. Digital agriculture technologies for site-specific N management have been demonstrated to improve nitrogen use efficiency (NUE). However, adoption of these technologies remains low. Factors such as cost, complexity, unknown impact and large data inputs are associated with low adoption. Grower’s hands-on experience coupled with targeted research can be used to promote adoption and quantify the impact of these technologies.

In this work, we evaluated commercially available crop model-based tools for directing variable rate applications in irrigated and rainfed fields in Nebraska. During the 2021 growing season, we conducted 11 on-farm randomized strip trials comparing crop model-based N tools versus the grower’s traditional management. Additionally, in a subset of these trials, N blocks with increasing amounts of N were applied in the field within contrasting management zones. These N blocks were used at the end of the season to estimate the economic optimal N rate (EONR).

Our objectives were to (a) evaluate the impact of commercially available crop model-based N tools on yield, NUE and profit, and (b) to compare crop model-based N recommendations against the grower’s typical N management and the observed EONR. Multi-spectral images, soil N, N uptake, soil available water and soil temperature were measured in a subset of the trials for further crop model testing. The performance of these tools will be evaluated by different soil, weather, and management conditions. Quantifying the impact of crop model-based N tools on corn production is a key step towards increasing adoption among growers and to ensure economic and environmental benefits.