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Soil & Crop Modeling

The Hybrid-Maize model can be purchased and downloaded from the ADEC eStore. Supplementary climate data for CO, IA, KS, MO, MN, MT, NE, ND, SD and WY is also available from the eStore

Project Goal
Improve simulation of biomass production and carbon sequestration in maize and soybean systems under high yielding conditions.

Project Description
Ecosystem carbon models are powerful tools for predicting the response of carbon (C) cycling to climate change and for identifying crop and soil management practices that promote C sequestration under current and projected climate change. Existing crop and ecosystem models are not robust in predicting maize and soybean growth and C dynamics in high inputs and high yielding systems. Specifically, they tend to underestimate crop grain yield as well as stover biomass. They also do not accurately reflect climatic effects on crop growth that are likely to become critical components of future climate change scenarios.

Through funding of this project and other sources, we have developed a new maize growth model, Hybrid-Maize (Yang et al, 2004, Field Crops Research, 87, 131-154). Hybrid-Maize utilizes the best components of the existing maize models and incorporates findings from recent field studies. It is more robust than current maize models in high yielding environments and is more responsive to climatic variables (e.g., temperature) that are of great concern for climate change. The model is very user friendly and is highly suitable to research, extension and education.

With funding from other sources, we are also evaluating existing soybean simulation models in an attempt to make improvements as required. Both the Hybrid Maize model and improved soybean models will then be coupled with the CENTURY ecosystem C model to estimate field-level C sequestration. Model results will be compared to C sequestration measured by the eddy flux tower systems, and as estimated by high resolution mapping of soil C stocks over time.

At present the Hybrid-Maize model is being integrated into the Modeling Application System Integrative Framework (MASIF) by Drs. S. Gage and G. Safir at the Michigan State University in an effort to assess C sequestration potential throughout the North Central USA. The Hybrid-Maize model will also be used to identify crop management factors (maturity group, plant density, planting date, etc.), physiological processes and maize crop genetic traits that have greatest impact on maize productivity under changing temperature scenarios. With this information we would be able to predict more accurately impact of climatic change on net primary productivity, biomass partitioning, soil C and greenhouse gas emissions in continuous maize and maize-soybean systems.

Model Screen Shots

All inputs required for a simulation run are specified on the front page.  Irrigation schedule and soil properties are only required in rainfed/Irrigated mode.

Numerical simulation outputs.

Bar chart presentation of simulation results.

Simulated crop growth dynamics.


Haishun Yang is a research assistant professor. His specialty is system analysis, simulation modeling of crop growth and soil C dynamics, and development of decision-support software.

Ken Cassman

Achim Dobermann is professor of soil science and nutrient management at the University of Nebraska-Lincoln. From 1992 to 2000, he was a soil scientist at the International Rice Research Institute and led a multi-national research program on developing new concepts and tools for site-specific nutrient management in irrigated rice systems. Prof. Dobermann conducts research on nutrient cycling, soil variability, geospatial and crop modeling, soil greenhouse gas emissions, and approaches for site-specific nutrient management in major cereal production systems of Asia and North America. He has published two books and more than 60 papers in international scientific journals.

Dan Walters

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