Simulated dataset of corn response to nitrogen over thousands of fields and multiple years in Illinois

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 methodol-ogy is the best to balance environmental and economic out-comes. 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 plat-form based on crop simulations run over millions of farming scenarios over extensive geographies. The database was cal-ibrated and validated using data from more than four hun-dred 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 character-istics and provide thorough descriptions of the model setup. (C) 2021 The Author(s). Published by Elsevier Inc.

Automated summary

Nitrogen (N) fertilizer recommendations for corn in the US Midwest have been a long-standing puzzle, and the lack of long-term data is a major challenge. To address this, researchers have developed an analytical platform based on crop simulations, calibrated and validated with data from hundreds of trials. This dataset is valuable for N management, machine leaching, and environmental policy analysis.