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This article in AJ

  1. Vol. 98 No. 3, p. 737-748
    Received: May 26, 2005

    * Corresponding author(s): hyang2@unl.edu
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Features, Applications, and Limitations of the Hybrid-Maize Simulation Model

  1. Haishun Yang *,
  2. Achim Dobermann,
  3. Kenneth G. Cassman and
  4. Daniel T. Walters
  1. Dep. of Agronomy and Horticulture, Univ. of Nebraska-Lincoln, P.O. Box 830915, Lincoln, NE 68583


The objective of this paper is to provide an overview of the Hybrid-Maize software (www.hybridmaize.unl.edu, verified 28 Feb. 2006), with emphasis on its practical applications based on our own experience and feedback from users. The Hybrid-Maize model is a computer program that simulates the growth and yield of a corn crop (Zea mays L.) under nonlimiting or water-limited (rainfed or irrigated) conditions. The scientific formulations of the model and its test and validation was published elsewhere. The model can be used to (i) assess the overall site yield potential and its variability based on historical weather data, (ii) evaluate changes in attainable yield using different combinations of planting date, hybrid maturity, and plant density, (iii) analyze yield in relation to silking and maturity in a specific year, (iv) assess soil moisture status and explore options for irrigation management, and (v) conduct in-season simulations to evaluate current crop status and predict final yield at maturity as a range of yield outcome probabilities based on historical climate data for the remainder of the growing season. Three examples are provided to demonstrate practical uses of the model. The software has a user-friendly graphic interface, and includes complete documentation of model formulations, validation, user manual, and context-sensitive help system. Settings of all internal parameters are transparent and modifiable by the user. Limitations of the software for practical uses, especially with regard to water stress and plant population, are also discussed.

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Copyright © 2006. American Society of AgronomyAmerican Society of Agronomy