Location: Plant Physiology and Genetics ResearchTitle: Putting mechanisms into crop production models) Author
Submitted to: Plant Cell and Environment
Publication Type: Peer reviewed journal
Publication Acceptance Date: 1/10/2012
Publication Date: 5/22/2013
Citation: Boote, K.J., Jones, J.W., White, J.W., Asseng, S., Lizaso, J. 2013. Putting mechanisms into crop production models. Plant Cell and Environment. 36(9):1658-1672. Interpretive Summary: In agriculture, one often seeks to predict the potential effects of weather, soil conditions and crop management on crop development, yield or other aspects of crop production, including possible impacts of crop production of the environment. Computer-based crop simulation models predict how processes affecting growth, water use and nitrogen use affect crops. A brief history of crop simulation is given, with emphasis on the level of detail used to describe key plant processes. These models have developed over the past 20-30 years, but they have not been sufficiently tested for responses to climate change factors of temperature and atmospheric CO2, despite an increasing amount of recent new data. Often, lack of resources has limited efforts to improve the realism of the described mechanisms as well as testing of the models for responses to CO2 and temperature. Improvements are needed in the prediction of transpiration response to CO2, in effects of high temperatures on time of events such as flowering and maturity, and in describing root growth and nutrient uptake. Because the crop models consider a wide range of processes and environmental factors throughout a crop’s life cycle, the models have excellent potential to help researcher’s link information from genetics to plant performance. The paper provides a timely review of the development of crop models and suggests avenues for model improvement and for novel applications that could further improve how crop models are used. If acted upon, the suggestions could bring widespread improvements in crop models and how they are used, bringing multiple benefits to producers in terms of more robust cultivars and better strategies to deal with problems such as climatic uncertainty.
Technical Abstract: Crop simulation models dynamically predict processes of carbon, nitrogen, and water balance on daily or hourly time-steps to the point of predicting yield and production at crop maturity. A brief history of these models is reviewed, and their level of mechanism for assimilation and respiration, ranging from hourly leaf-to-canopy assimilation to daily radiation-use-efficiency is discussed. These models have developed over the past 20-30 years and have not been sufficiently tested for responses to climate change factors of temperature and CO2, despite an increasing amount of recent new data. There is inertia as well as insufficient resources focused on improving the mechanisms in these models or the testing of the models for responses to CO2 and temperature. Improvements are needed in the prediction of transpiration response to CO2, in elevated temperature effects on phenology and reproductive fertility, and in simulation of root growth and nutrient uptake under stressful edaphic conditions. Because the crop models integrate over multiple processes throughout the full season and already consider environmental factors, the models have excellent potential as tools to link to genes and QTL markers, thus being useful for predicting and understanding why genotype by environment effects occur.