Under a federal cooperative agreement, two Nebraska Water Center researchers are assisting the USDA Agricultural Research Service to improve crop models for corn, soybean, cotton, rice, and potato.
As crop models are improved, producers can find more accurate data to aid their on-farm decision making. The team has been updating widely used crop simulation models to simulate photosynthesis, transpiration, and soil processes at more frequent time steps. The updates described in the new publications also allow for adaptation of the model based on climate change factors, including atmospheric CO2 and changes in average temperature.
Two Agronomists recruited for next generation crop modeling
The Nebraska Water Center is recruiting two agronomists to work with the Central Platte and Lower Loup NRDs to apply corn and soybean models for management decisions. With funding from the USDA-ARS Adaptive Cropping Systems Laboratory in Beltsville, MD, we are working together to link corn, soybean, potato, rice, and cotton growth models to soil and estimate yield as functions of nutrient, moisture, and temperature stresses. The models are being extended to estimate leaching losses of nutrients and greenhouse emissions as functions of management practices, fertilization, and water application. Field testing for corn, soybean, and potato occurred for the last two growing seasons.
New publication outlines improvements to cotton modeling
A Nebraska Water Center research team is making advancements in crop modeling. Post-doctoral research associates Sahila Beegum and Wenguang Sun worked in conjunction with the USDA’s Agricultural Research Service (USDA-ARS) in Maryland to publish the most recent update. Titled Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes, this paper was published in May in Scientific Reports, a Nature Publication.
Cotton crop simulation models were first developed in the 1970’s through the creation of equations that describe growth and development. The initial models included factors for evapotranspiration, soil water balance, and nitrogen balance. Several models came out of the initial work done in the 1970’s, but GOSSYM is one of the more widely used models because of its effectiveness in on-farm decision making and management practices.
The previous version of GOSSYM uses a two-dimensional soil model that simulated below-ground processes daily. The previous version of GOSSYM also calculates photosynthesis daily.
The new model can also simulate photosynthesis, transpiration, and soil processes at sub-daily time steps, which was not a feature of the previous version of GOSSYM. The updates made to GOSSYM that are described in this publication also allow for adaptation of the model based on climate change factors, including atmospheric CO2 and changes in average temperature.
Beegum, Sun, and the team are improving crop models for more than just theoretical uses.
“Improved crop models help in better estimating crop growth, development, and yields under varying environmental and management conditions.” Beegum said. “These models can assist in optimizing irrigation and nutrient application for crops. They incorporate capabilities for simulating CO2 production, transport, and soil respiration, allowing farmers to simulate carbon dynamics and soil CO2 respiration. This is particularly important due to increasing CO2 levels, which require accurate estimation of soil carbon storage and CO2 respiration. These models can be applied to both continuous and rotation cropping systems and can be scaled up for larger spatial analysis. The graphical user interface makes it much easier for farmers and researchers to use these models.”
Beegum, Sun, and the team are continuing to improve crop modeling beyond cotton crops and GOSSYM. The next phase of research includes improving crop models for maize and soybeans.
Beegum said, “Our primary focus is on enhancing simulation models that capture soil-plant-atmospheric interactions. We have made enhancements to the soil, photosynthesis, and transpiration processes within the soybean and cotton models. Furthermore, we have developed a carbon dioxide production and transport model for agricultural regions and integrated it into the maize, soybean, and cotton crop models. These improved models are now available in the form of a graphical user interface (GUI), which simplifies their usage for farmers and researchers.”
As crop models are improved, producers can find more accurate data to aid their on-farm decision making. By adding CO2 and other climatic factors to the existing, widely used models, the research team is empowering producers and policy makers to make decisions and develop adaptation strategies based on data.
Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes https://doi.org/10.1038/s41598-023-34378-3
- The radiation use efficiency-based photosynthesis model in GOSSYM has been replaced with a Farquhar biochemical model of photosynthesis, supplemented by the Ball-Berry leaf energy balance transpiration model.
- The simulation of below-ground processes in GOSSYM, which previously used RHIZOS, has been improved by replacing it with 2DSOIL, a mechanistic two-dimensional finite element soil process model.
- The newly developed model facilitates accurate cotton crop simulations under varying conditions of soil, water, temperature, carbon dioxide, and nutrient levels, and it can simulate all these processes at an hourly time step.
New publications in next generation crop modeling
- Beegum, S., Reddy, V., & Reddy, K. R. (2023). Development of a cotton fiber quality simulation module and its incorporation into cotton crop growth and development model: GOSSYM. Computers and Electronics in Agriculture, 212, 108080. https://doi.org/10.1016/j.compag.2023.108080
- Beegum, S., Sun, W., Timlin, D., Wang, Z., Fleisher, D., Reddy, V. R., & Ray, C. (2023). Incorporation of carbon dioxide production and transport module into a Soil-Plant-Atmosphere continuum model. Geoderma, 437, 116586. https://doi.org/10.1016/j.geoderma.2023.116586
- Beegum, S., Truong, V., Bheemanahalli, R., Brand, D., Reddy, V., & Reddy, K. R. (2023). Developing functional relationships between waterlogging and cotton growth and physiology towards waterlogging modeling. Frontiers in Plant Science, 14. https://doi.org/10.3389/fpls.2023.1174682
- Sun, W., Fleisher, D., Timlin, D., Ray, C., Wang, Z., Beegum, S., & Reddy, V. (2023). Projected long-term climate trends reveal the critical role of vapor pressure deficit for soybean yields in the US Midwest. Science of The Total Environment, 878, 162960. https://doi.org/10.1016/j.scitotenv.2023.162960
- Timlin, D., Fleisher, D., Tokay, M., Paff, K., Sun, W., Beegum, S., Li, S., Wang, Z., & Reddy, V. (2023). CLASSIM: A Relational Database Driven Crop Model Interface. Smart Agricultural Technology, 100281, https://doi.org/10.1016/j.atech.2023.100281
- Beegum, S., Timlin, D., Reddy, K. R., Reddy, V., Sun, W., Wang, Z., ... & Ray, C. (2023). Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes. Scientific Reports, 13(1), 7314 https://doi.org/10.1038/s41598-023-34378-3
- Sun, W., Fleisher, D., Timlin, D., Ray, C., Wang, Z., Sahila, B., & Reddy, V. (2023). Does drought stress eliminate the benefit of elevated CO2 on soybean yield? Using an improved model to link crop and soil water relations. Agricultural and Forest Meteorology, 343, 109747. https://doi.org/10.1016/j.agrformet.2023.109747
- Beegum, S., Walne, C. H., Reddy, K. N., Reddy, V., & Reddy, K. R. (2023). Examining the Corn Seedling Emergence–Temperature Relationship for Recent Hybrids: Insights from Experimental Studies. Plants, 12(21), 3699. https://doi.org/10.3390/plants12213699