Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: April 19, 2005
Publication Date: April 19, 2005
Citation: Kim, S., Timlin, D.J., Fleisher, D.H., Reddy, V. 2005. A simulation model for potential growth and development in corn [abstract]. Biological Systems Simulation Conference. p.1. Technical Abstract: A process-based simulation model that predicts potential growth and phenology in corn is presented. This model has been developed based on the design of Object-Oriented crop model (Acock and Reddy, 1997). Recent advances in maize and C4 physiology have been incorporated into the present model. In the present model, canopy carbon assimilation was simulated by sun-shade approach incorporating the C4 leaf photosynthesis model (von Caemmerer and Furbank, 1999) through coupling with models of stomatal conductance and energy balance (Kim and Lieth, 2003). Temperature response of leaf development was modeled using a simplified beta distribution function (Yan and Hunt, 1999) and anthesis was estimated according to Grant (1989b). Growth and senescence of individual leaves were modelled following Lizaso et al. (2003) and Tardieu et al. (1999). Assimilated carbohydrates were collected to a short-term carbon pool from which allocation to individual organs occurred based on the priorities described by Grant (1989a). Maintenance and growth respiration was accounted for before available carbons for dry matter accumulation were partitioned. Model behavior was reasonable and compared well with observations without extensive parameterization. Object-Oriented approach was useful for designing model structure and for modeling the relationships between organs. Incorporation of the coupled gas-exchange model will enable the present model to mechanistically predict the balance of carbon, water, and energy exchange. Currently we are working on linking this model with 2DSOIL (Timlin and Pachepsky, 1997) for implementing water, nitrogen, and other key element balances. The present model is at preliminary stage of development and must be validated with independent data from different locations and years before being used for applications.