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

German Mandrini, Sotirios V. Archontoulis, Cameron M. Pittelkow, Taro Mieno, Nicolas F. Martin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number107753
JournalData in Brief
Volume40
DOIs
StatePublished - Feb 2022

Keywords

  • APSIM
  • Crop modeling
  • Maize
  • Nitrogen fertilizer
  • Nitrogen leaching

ASJC Scopus subject areas

  • General

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