UC Davis

Nitrogen (N) fertilizer recommendations for corn (Zea mays L.) in the US Midwest have been a puzzle for several decades, without agreement among stakeholders for which methodology is the best to balance environmental and economic outcomes. Part of the reason is the lack of long-term data of crop responses to N over multiple fields since trial data is often limited in the number of soils and years it can explore. To overcome this limitation, we designed an analytical platform based on crop simulations run over millions of farming scenarios over extensive geographies. The database was calibrated and validated using data from more than four hundred trials in the region. This dataset can have an important role for research and education in N management, machine leaching, and environmental policy analysis. The calibration and validation procedure provides a framework for future gridded crop model studies. We describe dataset characteristics and provide thorough descriptions of the model setup.