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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 #398345

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: CLASSIM: A relational database driven crop model interface

Author
item Timlin, Dennis
item Fleisher, David
item TOKAY, MAURA - Science Systems And Applications, Inc
item Paff, Kirsten
item SUN, WENGUANG - University Of Nebraska
item BEEGUM, SAHILA - University Of Nebraska
item LI, SANAI - Us Forest Service (FS)
item WANG, ZHUANGJI - University Of Maryland
item Reddy, Vangimalla

Submitted to: Smart Agricultural Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/28/2023
Publication Date: 6/29/2023
Citation: Timlin, D.J., Fleisher, D.H., Tokay, M., Paff, K.E., 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.
DOI: https://doi.org/10.1016/j.atech.2023.100281

Interpretive Summary: Simulation models of important agronomic crops such as corn, soybean and potato are valuable tools for examining the interactions of cultivar characteristics, the environment, and management practices on crop growth and development. An interface for the models is necessary to make these complex tools accessible to end-users who lack the expertise needed to assemble and manage the data sets and files needed to use the models. Interfaces increase access to complex scientific tools for the public in general and would provide benefit for those users. We developed an interface called CLASSIM which is a graphical user interface (GUI) for a suite of models developed by USDA-ARS that simplifies the model input/output. Output is provided in tables and graphs to allow visualization and analysis of model outputs. Crop models are vital tools for studying the effects of climate change on agriculture and possible adaptation strategies, so having user friendly GUIs is essential for making these tools accessible to the broad range of individuals and groups working to understand how climate, management, and genetics affects agricultural productivity and resource use.

Technical Abstract: Crop models are valuable tools for examining the interactions of cultivar characteristics, the environment, and management practices, and how they affect crop growth and development. Model interfaces are necessary to make these complex tools accessible to end-users who lack the expertise needed to work with the models directly, but who would benefit from the information generated by the models. As crop models vary in terms of input and output structures, there is not one universal interface, so different crop model suites require their own interface. CLASSIM is a graphical user interface (GUI) for a suite of models developed by USDA-ARS that simplifies the model input/output system and uses a database structure to facilitate input/output data storage and retrieval, making data entry and storage easier. Output is provided in tables and graphs to allow visualization and analysis of model outputs. Two-dimensional contour plots of soil processes are provided to visualize output from the two-dimensional finite element model that simulates soil processes. The relational databases used to store the data allow access using Structured Query Language (SQL) in many different programs for more advanced analysis and visualization. CLASSIM also allows users to set up single- and multiple-season runs for maize, cotton, soybean, potato, and fallow treatments, and is expected to be expanded to more crops in the future. Crop models are vital tools for studying the effects of climate change on agriculture and possible adaptation strategies, so having user friendly GUIs is essential for making these tools accessible to the broad range of researchers working to solve the challenge of climate change.