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Evaluating and improving APSIM's capacity in simulating long-term corn yield response to nitrogen in continuous- and rotated-corn systems

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  • Baum, Mitchell E.
  • Sawyer, John E.
  • Nafziger, Emerson D.
  • Huber, Isaiah
  • Thorburn, Peter J.
  • Castellano, Michael J.
  • Archontoulis, Sotirios V.

Abstract

Process-based models are increasingly used to explain and predict crop yields and long-term changes in soil organic matter (SOM) and hence should be regularly evaluated for their accuracy. Currently, there is a knowledge gap of how well process-based models can estimate the economic optimum nitrogen rate (EONR) across environments and years.

Suggested Citation

  • Baum, Mitchell E. & Sawyer, John E. & Nafziger, Emerson D. & Huber, Isaiah & Thorburn, Peter J. & Castellano, Michael J. & Archontoulis, Sotirios V., 2023. "Evaluating and improving APSIM's capacity in simulating long-term corn yield response to nitrogen in continuous- and rotated-corn systems," Agricultural Systems, Elsevier, vol. 207(C).
    • Handle: RePEc:eee:agisys:v:207:y:2023:i:c:s0308521x23000343
    DOI: 10.1016/j.agsy.2023.103629
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    1. Della Nave, Facundo N. & Ojeda, Jonathan J. & Irisarri, J. Gonzalo N. & Pembleton, Keith & Oyarzabal, Mariano & Oesterheld, Martín, 2022. "Calibrating APSIM for forage sorghum using remote sensing and field data under sub-optimal growth conditions," Agricultural Systems, Elsevier, vol. 201(C).
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    1. Mitchell E. Baum & John E. Sawyer & Emerson D. Nafziger & Michael J. Castellano & Marshall D. McDaniel & Mark A. Licht & Dermot J. Hayes & Matthew J. Helmers & Sotirios V. Archontoulis, 2025. "The optimum nitrogen fertilizer rate for maize in the US Midwest is increasing," Nature Communications, Nature, vol. 16(1), pages 1-10, December.

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