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Modeling growth, development and yield of Sugarbeet using DSSAT

Author

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  • Anar, Mohammad J.
  • Lin, Zhulu
  • Hoogenboom, Gerrit
  • Shelia, Vakhtang
  • Batchelor, William D.
  • Teboh, Jasper M.
  • Ostlie, Michael
  • Schatz, Blaine G.
  • Khan, Mohamed

Abstract

Sugarbeet (Beta vulgaris) is considered as one of the most viable feedstock alternatives to maize for biofuel production since herbicide resistant sugarbeet was deregulated by the United States Department of Agriculture in 2012. So far, only a few sugarbeet simulation models have been developed and these models are limited to application for local regions. The Decision Support System for Agrotechnology Transfer (DSSAT) provides a common framework for a cropping system study and currently has crop modules for >40 crops. However, DSSAT currently does not include a model for sugarbeet. In this study, the Crop and Environment REsource Synthesis (CERES) Beet model was modified and incorporated into the current version of the Cropping System Model (CSM) to simulate growth, development, and yield of sugarbeet. The PEST optimizer was used for parameter estimation, transferability evaluation, and predictive uncertainty analysis. The sugarbeet model was evaluated with two sets of experimental data collected in two different regions and under different environmental conditions; one in Romania (Southeastern Europe) during 1997–1998 and the other in North Dakota, US (North America) during 2014–2016. After model calibration for specific cultivars, the CSM-CERES-Beet model performed well for the simulation of leaf area index, leaf number, leaf or top weight, and root weight for both datasets (NSE = 0.144–0.976, rRMSE = 0.127–1.014). Uncertainty analysis revealed that the calibrated CSM-CERES-Beet consistently over-predicted leaf number with false confidence, although measured leaf number also showed a significant variability. The model was successfully applied for predicting yield for six different sugarbeet cultivars grown in North Dakota during the 2014 to 2016 growing seasons. CSM-CERES-Beet could be applied for predicting sugarbeet yield for different soil and climatic conditions and various management scenarios for the Red River Valley in the US and other regions with environmental conditions favorable for sugarbeet production.

Suggested Citation

  • Anar, Mohammad J. & Lin, Zhulu & Hoogenboom, Gerrit & Shelia, Vakhtang & Batchelor, William D. & Teboh, Jasper M. & Ostlie, Michael & Schatz, Blaine G. & Khan, Mohamed, 2019. "Modeling growth, development and yield of Sugarbeet using DSSAT," Agricultural Systems, Elsevier, vol. 169(C), pages 58-70.
    • Handle: RePEc:eee:agisys:v:169:y:2019:i:c:p:58-70
    DOI: 10.1016/j.agsy.2018.11.010
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    1. Hettinga, W.G. & Junginger, H.M. & Dekker, S.C. & Hoogwijk, M. & McAloon, A.J. & Hicks, K.B., 2009. "Understanding the reductions in US corn ethanol production costs: An experience curve approach," Energy Policy, Elsevier, vol. 37(1), pages 190-203, January.
    2. Vandendriessche, H. J., 2000. "A model of growth and sugar accumulation of sugar beet for potential production conditions: SUBEMOpo I. Theory and model structure," Agricultural Systems, Elsevier, vol. 64(1), pages 1-19, April.
    3. Foteinis, Spyros & Kouloumpis, Victor & Tsoutsos, Theocharis, 2011. "Life cycle analysis for bioethanol production from sugar beet crops in Greece," Energy Policy, Elsevier, vol. 39(9), pages 4834-4841, September.
    4. Hunt, L. A. & White, J. W. & Hoogenboom, G., 2001. "Agronomic data: advances in documentation and protocols for exchange and use," Agricultural Systems, Elsevier, vol. 70(2-3), pages 477-492.
    5. Vandendriessche, H. J., 2000. "A model of growth and sugar accumulation of sugar beet for potential production conditions: SUBEMOpoII. Model performance," Agricultural Systems, Elsevier, vol. 64(1), pages 21-35, April.
    6. Yang, J.M. & Yang, J.Y. & Liu, S. & Hoogenboom, G., 2014. "An evaluation of the statistical methods for testing the performance of crop models with observed data," Agricultural Systems, Elsevier, vol. 127(C), pages 81-89.
    7. Baey, Charlotte & Didier, Anne & Lemaire, Sébastien & Maupas, Fabienne & Cournède, Paul-Henry, 2014. "Parametrization of five classical plant growth models applied to sugar beet and comparison of their predictive capacity on root yield and total biomass," Ecological Modelling, Elsevier, vol. 290(C), pages 11-20.
    8. Timsina, J. & Humphreys, E., 2006. "Performance of CERES-Rice and CERES-Wheat models in rice-wheat systems: A review," Agricultural Systems, Elsevier, vol. 90(1-3), pages 5-31, October.
    9. Ma, L. & Hoogenboom, G. & Ahuja, L.R. & Ascough II, J.C. & Saseendran, S.A., 2006. "Evaluation of the RZWQM-CERES-Maize hybrid model for maize production," Agricultural Systems, Elsevier, vol. 87(3), pages 274-295, March.
    10. Li, Zhuo Ting & Yang, J.Y. & Drury, C.F. & Hoogenboom, G., 2015. "Evaluation of the DSSAT-CSM for simulating yield and soil organic C and N of a long-term maize and wheat rotation experiment in the Loess Plateau of Northwestern China," Agricultural Systems, Elsevier, vol. 135(C), pages 90-104.
    11. Miyake, Saori & Smith, Carl & Peterson, Ann & McAlpine, Clive & Renouf, Marguerite & Waters, David, 2015. "Environmental implications of using ‘underutilised agricultural land’ for future bioenergy crop production," Agricultural Systems, Elsevier, vol. 139(C), pages 180-195.
    12. Khaembah, E.N. & Brown, H.E. & Zyskowski, R. & Chakwizira, E. & de Ruiter, J.M. & Teixeira, E.I., 2017. "Development of a fodder beet potential yield model in the next generation APSIM," Agricultural Systems, Elsevier, vol. 158(C), pages 23-38.
    13. Rinaldi, Michele & Ventrella, Domenico & Gagliano, Caterina, 2007. "Comparison of nitrogen and irrigation strategies in tomato using CROPGRO model. A case study from Southern Italy," Agricultural Water Management, Elsevier, vol. 87(1), pages 91-105, January.
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