Nitrogen fertilizer effi ciency has a large infl uence on profi t, energy effi ciency, N losses to the environment, and greenhouse gas emis- sions in maize (Zea mays L.) production. Our purpose was to develop a robust decision-support tool to help inform N fertilizer rec- ommendations 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. Th e model estimates the EONR based on uptake effi ciency of the applied N, expected yield response, market prices of grain and N fertilizer, and mechanistic components of soil N mineralization. Uptake effi ciency and expected yield response are derived from a database of yield response to applied N from fi eld experiments in the United States, Asia, and South America. Th e model is responsive to: (i) soil properties and indigenous soil N sup- ply capacity, (ii) local climatic conditions and yield potential, (iii) crop rotation (including type and yield of previous crop), (iv) till- age 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 fi eld tests in Kansas, Missouri, Nebraska, South Dakota, and Iowa.
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