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This article in AJ

  1. Vol. 106 No. 3, p. 1025-1040
     
    Received: Sept 02, 2013
    Published: March 28, 2014


    * Corresponding author(s): sarchont@iastate.edu
    sarchont@gmail.com
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doi:10.2134/agronj2013.0421

Evaluating APSIM Maize, Soil Water, Soil Nitrogen, Manure, and Soil Temperature Modules in the Midwestern United States

  1. Sotirios V. Archontoulis *,
  2. Fernando E. Miguez and
  3. Kenneth J. Moore
  1. Dep. of Agronomy, Iowa State Univ., Agronomy Hall, Ames, IA 50011

Abstract

The Agricultural Production Systems sIMulator (APSIM) is a cropping systems modeling platform that is used worldwide to address research questions related to agricultural systems. We explored whether APSIM performs well in the Midwest, so that the associated model capabilities would be available for application in this region. Our approach included calibration and testing of several APSIM models (maize [Zea mays L.], soil water, soil N, surface organic matter, manure, and soil temperature) and evaluation of model predictions against independent datasets. During calibration we developed local crop and soil parameters so that the model captured sufficiently well dynamics of soil water (root mean square error, RMSE = 0.032 mm mm–1), soil temperature (RMSE = 2.1°C), soil inorganic N dynamics (RMSE = 12.6 kg N ha–1), contrasting soil net N mineralization patterns under fresh and composted swine manure applications (RMSE = 13.6 kg N ha–1), crop phenology (RMSE = 1.52 d), leaf area index (RMSE = 0.60 m2 m–2), leaf N concentration (RMSE = 0.28 kg 100 kg–1), canopy N uptake (RMSE = 9.0 kg N ha–1), biomass production (RMSE = 0.77 Mg ha–1) and grain yield (RMSE = 0.53 Mg ha–1). The calibration protocol followed in this study is discussed in detail. The calibrated model was evaluated against independent data on grain yield (RMSE = 0.65 Mg ha–1), biomass production (RMSE = 1.1 Mg ha–1) and LAI (RMSE = 1.14 m2 m–2), showing very acceptable performance, especially in addressing yield-N relationships. Therefore APSIM proves to be a reliable model that can be used as a research and decision tool to enhance Midwestern production systems.

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