Modeling the economic and environmental effects of corn nitrogen management strategies in Illinois

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Eco-efficient use of nitrogen (N) fertilizer in Corn (Zea Mays L.) requires timely information about the supply of N from the soil and the response to N by the crop. These are complex processes, and multiple N management strategies (NMS) have been proposed over time. In this work, we used APSIM (Agricultural Production Systems sIMulator) to simulate the response of Corn's Yield to N for ca. 4200 fields in the state of Illinois in different weather scenarios. Ten different N management strategies were evaluated using environmental and economic indicators. They were created by combining different sources of trial data, different types of prediction models, different predictor variables measured on the fields, and different technologies to apply fertilizer in the field. This study provides knowledge that is unattainable through field experimentation, leveraging current knowledge on the mechanisms that drive the yield response to N to help farmers, researchers, and policymakers to select strategies in line with their objectives. Our results showed that an N management strategy that incorporates year-to-year variability in the predictions and uses data from trials spread in the region achieved the highest eco-efficiency. Such strategy would reduce the mean N-leaching by 12.7% without changing profits compared with the N management strategy most used by extension services in the area. Nitrogen measurements obtained by soil sampling were the most important predictor and could not be replaced by other less laborious variables. Variable-rate technology did not provide significant economic or environmental value in the area.

Original languageEnglish (US)
Article number108000
JournalField Crops Research
StatePublished - Feb 1 2021


  • Crop modeling
  • Decision support
  • Environmental impact
  • Machine learning
  • N-leaching
  • Nitrogen
  • Nitrogen management

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Soil Science


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