534-14 Evaluating the MaizSim Model in Simulating Potential Corn Growth.

Poster Number 209

See more from this Division: A03 Agroclimatology & Agronomic Modeling
See more from this Session: Climate and Crop Processes (Posters)

Monday, 6 October 2008
George R. Brown Convention Center, Exhibit Hall E

Yang Yang1, David Fleisher2, Dennis Timlin3, Bruno Quebedeaux4 and Vangimalla Reddy2, (1)Crop Systems and Global Change, USDA-ARS, Beltiville, MD
(2)USDA-ARS, Crop Systems and Global Change Lab., Beltsville, MD
(3)USDA-ARS-CSGCL, USDA-ARS, Beltsville, MD
(4)Plant Science Bldg., Rm. 2130, Univ. of Maryland, College Park, MD
Abstract:
Models that simply calculate crop growth rate as the product of intercepted light and radiation use efficiency may not be able to adequately simulate plant growth under stress conditions. We developed a new corn model MaizSim. In MaizSim, photosynthesis is mechanistically related to environmental conditions such as intercepted light, CO2 concentration etc. as well as plant physiological status such as stomatal conductance and plant water/nitrogen status. The new model is able to simulate energy balance, mass balance (including water, carbon and nitrogen balance) of corn and thus possesses the potential to simulate plant processes more realistically under either water or nitrogen stress. In this study, we evaluate MaizSim simulation of seasonal growth under conditions where water and nitrogen supply were not limiting crop growth. The change of leaf area index (LAI), above ground biomass, biomass of different organ and nitrogen content/concentration of above ground organs were collected for two years from six different fields. The collected data was used to evaluate the seasonal simulation of crop growth, carbon partitioning and nitrogen uptake. Future efforts will be concentrated on developing a dynamic carbon partitioning module that is able to simulate biomass partitioning between shoot and root and among different organs under stress.

See more from this Division: A03 Agroclimatology & Agronomic Modeling
See more from this Session: Climate and Crop Processes (Posters)