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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Rangeland Resources & Systems Research » Research » Publications at this Location » Publication #369434

Research Project: Adaptive Grazing Management and Decision Support to Enhance Ecosystem Services in the Western Great Plains

Location: Rangeland Resources & Systems Research

Title: Modeling the effects of crop rotation and tillage on sugarbeet yield and soil nitrate using RZWQM2

Author
item ANAR, M - North Dakota State University
item LIN, Z - North Dakota State University
item Ma, Liwang
item CHATTERJEE, A - North Dakota State University
item YUJA, S - North Dakota State University
item TEBOH, J - North Dakota State University
item OSTLIE, E - North Dakota State University

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/6/2020
Publication Date: 3/1/2021
Citation: Anar, M.J., Lin, Z., Ma, L., Chatterjee, A., Yuja, S., Teboh, J.M., Ostlie, E. 2021. Modeling the effects of crop rotation and tillage on sugarbeet yield and soil nitrate using RZWQM2. Transactions of the ASABE. 64(2):461-474. https://doi.org/10.13031/trans.13752.
DOI: https://doi.org/10.13031/trans.13752

Interpretive Summary: Sugarbeet has great potential as an alternative to corn for biofuel, but its production is significantly affected by crop rotation and tillage. The ability to simulate these effects will help in making proper management decisions. In this study, the CSM-CERESBeet, CSM-CERES-Maize, CROPSIM-Wheat, and CROPGRO-Soybean models included in the Root Zone Water Quality Model (RZWQM2) were calibrated and evaluated against the experimental field data of crop yield, soil water, and soil nitrate from the North Dakota State University Carrington Research Extension Center from 2014 to 2016. The models performed reasonably well in simulating crop yield, soil water, and nitrate. Simulation results also identified wheat as the most favorable previous-year-crop for sugarbeet. Among the tillage operations, moldboard plow performed better compared to other tillage methods in terms of yield production. As sugarbeet production may be expanded into nontraditional planting areas in the Red River Valley due to potential demand for biofuel production, our findings will help to assess the associated environmental impacts and identify suitable crop rotations and management scenarios in the region.

Technical Abstract: Sugarbeet (Beta vulgaris) is considered to be one of the most viable alternatives to corn for biofuel production as it may be qualified as “advanced” biofuel feedstock under the Energy Independence and Security Act (EISA) of 2007. Since its production is significantly affected by crop rotation and tillage, simulation of these effects will help in making proper management decisions. In this study, the CSM-CERESBeet, CSM-CERES-Maize, CROPSIM-Wheat, and CROPGRO-Soybean models included in the Root Zone Water Quality Model (RZWQM2) were calibrated and evaluated against the experimental field data of crop yield, soil water, and soil nitrate from the North Dakota State University Carrington Research Extension Center from 2014 to 2016. The models performed reasonably well in simulating crop yield, soil water, and nitrate, with relative root mean squared errors ranging from 0.055 to 2.773, and d-index of agreement between 0.541 and 0.997. Simulation results also identified wheat as the most favorable previous-year-crop for sugarbeet. Among the tillage operations, moldboard plow performed better compared to other tillage methods in terms of yield production. As sugarbeet production may be expanded into nontraditional planting areas in the Red River Valley due to potential demand for biofuel production, our findings will help to assess the associated environmental impacts and identify suitable crop rotations and management scenarios in the region.