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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Publications at this Location » Publication #363554

Research Project: Experimentally Assessing and Modeling the Impact of Climate and Management on the Resiliency of Crop-Weed-Soil Agro-Ecosystems

Location: Adaptive Cropping Systems Laboratory

Title: Evaluation of different crop models for simulating rice development and yield in the U.S. Mississippi Delta

Author
item LI, S - Non ARS Employee
item Fleisher, David
item Timlin, Dennis
item Reddy, Vangimalla
item WANG, Z - University Of Maryland
item McClung, Anna

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2020
Publication Date: 12/2/2020
Citation: Li, S., Fleisher, D.H., Timlin, D.J., Reddy, V., Wang, Z., McClung, A.M. 2020. Evaluation of different crop models for simulating rice development and yield in the U.S. Mississippi Delta. Agronomy. https://doi.org/10.3390/agronomy10121905.
DOI: https://doi.org/10.3390/agronomy10121905

Interpretive Summary: Warming temperatures in the Mississippi Delta region are negatively influencing the yield and quality of rice grain. Because the United States is the fourth largest rice exporter in the world, information on how different rice varieties are affected by these changes in the production environment is needed. Over 20 years of experimental data from four states in this region were used as part of a statistical analysis to evaluate the influence of different climate factors, including rainfall, temperatures, and sunlight, on rice. The accuracy of two mathematical models that can predict rice growth was then tested using this data. Experimental yields were found to be more sensitive to changes in temperature and reduced solar radiation, because of increased rainfall amounts, during the past ten years as compared to the prior decade. Using a portion of this experimental data, the two models were found to be good predictors of rice development once they were calibrated. However, these same models were not able to mimic negative impacts of very warm, or very cold temperatures on rice development. These conditions were observed to occur with more frequency. Modifying these models in the future with this new knowledge will result in improved decision support tools that scientists, crop consultants, and rice growers can then use to make more informed management decisions to maintain their farms and the export industry.

Technical Abstract: The United States is one of the top rice exporters in the world, but there is concern that warming temperatures may affect grain yield and quality. The majority of production occurs within the Mississippi Delta region where rice farms typically use highly intensified production systems. Exploring the response of U.S. rice varieties in this region to changing climate conditions is necessary to identify environmental constraints to crop yields and identify adaptation strategies. We first evaluated historical relationships between rice yield and climate factors using 34 years of observed data centered at four regional locations. Next, the feasibility of CERES-Rice and ORYZA crop models to quantify the responses of two cultivars using this same dataset was evaluated. Re-parameterizing cardinal temperatures in ORYZA to match U.S. conditions resulted in improved model accuracy and reduced systematic error where the correlation coefficient between observed and simulated growth duration increased by 0.24 and root mean square error reduced by 0.75-2.2 days. After calibration, the two models subsequently showed similar performance with respect to predicting rice yield for most varieties, locations, and years. Larger differences between predicted and observed yields were found for those years with either high rainfall, and thus lower solar radiation, and/or those years with extreme temperature episodes such as cold temperatures during vegetative stages and high temperatures during reproductive development. Simulated yields from ORYZA were within -3% of observed values compared to 15% as simulated by CERES-Rice for those years. The response of rice growth and development to extreme climate events and warmer night temperatures will need to be further developed and improved in ORYZA and CERES-Rice so that these models can be utilized to evaluate climate impacts and adaptation strategies for the U.S. rice production regions.