Submitted to: Remote Sensing and Modeling Applications for Natural Resource Management
Publication Type: Abstract Only
Publication Acceptance Date: March 15, 2002
Publication Date: March 15, 2002
Citation: Kim, S., Timlin, D.J., Gitz, D.C., Pachepsky, L., Baker, J.T., Reddy, V. 2002. Development of a mechanistic crop simulation model for corn: a proposal [abstract]. Remote Sensing and Modeling Applications for Natural Resource Management. P. 59.
Corn (Zea mays L.) is the third most important food crop globally; only wheat and rice are ahead of corn in terms of total global production. Corn is different from other major grain crops because it uses C4 photosynthetic pathway. Several simulation models have been developed for corn. Most of those models, however, did not implement the physiological processes mechanistically based on up-to-date knowledge of plant physiology and ecology. We set out a study to develop a mechanistic crop simulation model for corn, which will be integrated into a suite of crop simulation models encompassing wheat, rice, soybean, cotton, peanuts and potato. We reviewed the existing corn models. Then we selected those models which have been widely adopted for simulating corn growth and development including CERES- Maize and EPIC to compare their predictions under various environmental scenarios such as elevated CO2 and temperature regimes. Based on the review wof the existing corn models and other relevant models in various areas of plant and soil sciences, we present a blueprint of the projected corn simulation model. The necessity of a mechanistic model for corn to account for the crop productivity under elevated CO2, temperature and water stress conditions is discussed. Modular structure of the proposed model, incorporation of a biochemical model of C4 photosynthesis, implementation of 2DSOIL as a module to simulate water and nutrient uptake, and interfacing with GUICS system are covered among others. Experimental protocol for calibration and validation of the proposed model is discussed.