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This article in AJ

  1. Vol. 103 No. 4, p. 1276-1283
    Received: Feb 8, 2011

    * Corresponding author(s): kcassman1@unl.edu


Maize-N: A Decision Tool for Nitrogen Management in Maize

  1. T. D. Setiyonoa,
  2. H. Yangb,
  3. D. T. Waltersa,
  4. A. Dobermannc,
  5. R. B. Fergusona,
  6. D. F. Robertsd,
  7. D. J. Lyone,
  8. D. E. Clayf and
  9. K. G. Cassman *a
  1. a Dep. of Agronomy and Horticulture, Univ. of Nebraska, Lincoln, NE 68583
    b Monsanto Company, 800 N. Lindbergh Blvd., St. Louis, MO 63167
    c IRRI, DAPO Box 7777, Metro Manila, Philippines 1301
    d Dep. of Plant and Soil Sciences, Mississippi State Univ., Starkville, MS 39762
    e Panhandle Research and Extension Center, Univ. of Nebraska-Lincoln, Scottsbluff, NE 69361
    f Drought Center, South Dakota State Univ., Brookings, SD 57007


Nitrogen fertilizer efficiency has a large influence on profit, energy efficiency, N losses to the environment, and greenhouse gas emissions in maize (Zea mays L.) production. Our purpose was to develop a robust decision-support tool to help inform N fertilizer recommendations and to compare performance of this tool relative to existing recommendation approaches. Maize-N is a simulation model for estimating economically optimum N fertilizer rates (EONR) for maize. The model estimates the EONR based on uptake efficiency of the applied N, expected yield response, market prices of grain and N fertilizer, and mechanistic components of soil N mineralization. Uptake efficiency and expected yield response are derived from a database of yield response to applied N from field experiments in the United States, Asia, and South America. The model is responsive to: (i) soil properties and indigenous soil N supply capacity, (ii) local climatic conditions and yield potential, (iii) crop rotation (including type and yield of previous crop), (iv) tillage method and timing of tillage operations, and (v) fertilizer formulation, application method, and timing. Validation of Maize-N across N management regimes and environments in the western U.S. Corn Belt indicated reasonable agreement between observed and measured values of EONR (RMSE of 21 kg N ha−1), which compares favorably with RMSE values of 33 to 61 kg N ha−1 for other methods based on empirical relationships derived from regional field tests in Kansas, Missouri, Nebraska, South Dakota, and Iowa.

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Copyright © 2011. Copyright © 2011 by the American Society of Agronomy, Inc.