Modeling Temperature Responses of Leaf Growth, Development, and Biomass in Maize with MAIZSIM

• Published in: Agronomy journal 2012-11, Vol.104 (6), p.1523-1537
• Main Authors: Kim, Soo‐Hyung, Yang, Yang, Timlin, Dennis J., Fleisher, David H., Dathe, Annette, Reddy, Vangimalla R., Staver, Kenneth
• Format: Article
• Language: English
• Subjects: Agronomy. Soil science and plant productions; albedo (reflectance); Biological and medical sciences; biomass; C4 photosynthesis; canopy; carbon; climate; climate change; corn; crop models; crop yield; crops; Delaware; field experimentation; food security; Fundamental and applied biological sciences. Psychology; growth chambers; heat sums; leaf area; leaf development; leaves; Maryland; nitrogen content; nonlinear models; nutrient partitioning; phenology; plant-water relations; planting; prediction; soil; temperature; Zea mays
• ISSN: 0002-1962; 1435-0645
• DOI: 10.2134/agronj2011.0321

Mechanistic crop models capable of representing realistic temperature responses of key physiological processes are necessary for enhancing our ability to forecast crop yields and develop adaptive cropping solutions for achieving food security in a changing climate. Leaf growth and phenology are critical components of crop growth and yield that are sensitive to climate impacts. We developed a novel modeling approach that incorporates a set of nonlinear functions to augment traditional thermal time methods (e.g., growing degree days) for simulating temperature responses of leaf expansion and phenology in maize or corn (Zea mays L.). The resulting leaf expansion and phenology models have been implemented into a new crop model, MAIZSIM, that simulates crop growth based on key physiological and physical processes including C4 photosynthesis, canopy radiative transfer, C partitioning, water relations, and N dynamics for a maize plant. Coupled with a two‐dimensional soil process model, 2DSOIL, MAIZSIM was applied to simulate leaf growth, phenology, biomass partitioning, and overall growth of maize plants planted at two field sites on the Eastern Shore of Maryland and in Delaware for 3 yr of data. The model parameters were estimated using data from outdoor sunlit growth chambers and the literature. No calibration was performed using the field data. The MAIZSIM model simulated leaf area, leaf addition rate, leaf numbers, biomass partitioning and accumulation with reasonable accuracy. Our study provides a feasible method for integrating nonlinear temperature relationships into crop models that use traditional thermal time approaches without sacrificing their current structure for predicting the climate change impacts on crops.