Agronomy Journal Journal of Natural Resources and Life Sciences Education
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Published online 3 May 2006
Published in Agron J 98:737-748 (2006)
DOI: 10.2134/agronj2005.0162
© 2006 American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA
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Right arrow Crop Physiology & Metabolism
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Right arrow Maize Management

Features, Applications, and Limitations of the Hybrid-Maize Simulation Model

Haishun Yang*, Achim Dobermann, Kenneth G. Cassman and Daniel T. Walters

Dep. of Agronomy and Horticulture, Univ. of Nebraska-Lincoln, P.O. Box 830915, Lincoln, NE 68583


Figure 1
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Fig. 1. Operational flow of the Hybrid-Maize model. GDD = growing degree days.

 

Figure 2
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Fig. 2. Screenshots of the input page (top) and one of the five output pages (bottom) of the Hybrid-Maize model.

 

Figure 3
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Fig. 3. Access to internal parameters in the Hybrid-Maize model software. Parameters are grouped on four pages: Management, Crop growth, Resp & Photosyn (for respiration and photosynthesis), Hybrid-specific parameters for the relationship between relative maturity (CRM) to total growing degree days (GDD), and Soil. All values can be changed by the user or restored to their original default values by clicking on the ‘Retrieve defaults’ button at lower left.

 

Figure 4
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Fig. 4. Approach used for in-season (real-time) yield prediction in the Hybrid-Maize model. In this example, a real-time simulation is conducted for 25 July 2004, using weather data for the period January 1985 to 25 July 2004. Input data has double lined borders and model output has single lined borders.

 

Figure 5
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Fig. 5. Screenshots of the summary ‘Results’ pages from four simulation runs of long-term yield potential at Lincoln, NE using different combinations of planting date and hybrid maturity: Simulation run 1, planting on 1 May with 1500 growing degree days (GDD) hybrid; Simulation run 2, planting on 15 May with 1500 GDD hybrid; Simulation run 3, planting on 1 May with 1590 GDD hybrid; Simulation run 4, planting on 15 May with 1590 GDD hybrid. Other input settings are shown in the top screen of Fig. 1.

 

Figure 6
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Fig. 6. Screenshot of the Hybrid-Maize ‘Water’ page showing predictions of irrigation water requirement (striped bars) for the year of median yield in the simulation described in the text. The darker bars are rainfall. Total irrigation and rainfall amounts are given on the ‘Results’ page (not shown).

 

Figure 7
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Fig. 7. In-season yield forecasting in 5-d intervals (points) for two fields in Nebraska in 2003: (a) Irrigated maize at Lincoln, (b) Rainfed maize grown at Mead. Dates of planting, silking and maturity are marked by the arrows in the graphs, and the long-term median yields and measured final yields are shown as horizontal lines. This is the resultant output from the model iterations illustrated in Fig. 4 and is displayed in the "Yield Trend" page.

 





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