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The Role of Crop Systems Simulation in Agriculture and Environment

Author

Listed:
  • K.J. Boote

    (University of Florida, USA)

  • J.W. Jones

    (University of Florida, USA)

  • G. Hoogenboom

    (University of Georgia, USA)

  • J.W. White

    (USDA-ARS, Arizona, USA)

Abstract

Simulation of crop systems has evolved from a neophyte science into a robust and increasingly accepted discipline. Our vision is that crop systems simulation can serve important roles in agriculture and environment. Important roles and uses of crop systems simulation are in five primary areas: 1) basic research synthesis and integration, where simulation is used to synthesize our understanding of physiology, genetics, soil characteristics, management, and weather effects, 2) strategic tools for planning and policy to evaluate strategies and consequences of genetic improvement or resource management, 3) applications for management purposes, where crop systems simulations are used to evaluate impacts of weather and management on production, water use, nutrient use, nutrient leaching, and economics, 4) real time decision support to assist in management decisions (irrigation, fertilization, sowing date, harvest, yield forecast, pest management), and 5) education in class rooms and farms, to explain how crop systems function and are managed.

Suggested Citation

  • K.J. Boote & J.W. Jones & G. Hoogenboom & J.W. White, 2010. "The Role of Crop Systems Simulation in Agriculture and Environment," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 1(1), pages 41-54, January.
    • Handle: RePEc:igg:jaeis0:v:1:y:2010:i:1:p:41-54
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    Citations

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    Cited by:

    1. Mahboobe Ghobadi & Mahdi Gheysari & Mohammad Shayannejad & Hamze Dokoohaki, 2023. "Analyzing the Effects of Planting Date on the Uncertainty of CERES-Maize and Its Potential to Reduce Yield Gap in Arid and Mediterranean Climates," Agriculture, MDPI, vol. 13(8), pages 1-17, July.
    2. Liu, H.L. & Yang, J.Y. & Tan, C.S. & Drury, C.F. & Reynolds, W.D. & Zhang, T.Q. & Bai, Y.L. & Jin, J. & He, P. & Hoogenboom, G., 2011. "Simulating water content, crop yield and nitrate-N loss under free and controlled tile drainage with subsurface irrigation using the DSSAT model," Agricultural Water Management, Elsevier, vol. 98(6), pages 1105-1111, April.
    3. Araya, A. & Prasad, P.V.V. & Gowda, P.H. & Sharda, V. & Rice, C.W. & Ciampitti, I.A., 2021. "Evaluating optimal irrigation strategies for maize in Western Kansas," Agricultural Water Management, Elsevier, vol. 246(C).
    4. Araya, A. & Kisekka, Isaya & Gowda, Prasanna H. & Prasad, P.V. Vara, 2017. "Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM," Agricultural Systems, Elsevier, vol. 150(C), pages 86-98.
    5. Montoya, F. & Camargo, D. & Domínguez, A. & Ortega, J.F. & Córcoles, J.I., 2018. "Parametrization of Cropsyst model for the simulation of a potato crop in a Mediterranean environment," Agricultural Water Management, Elsevier, vol. 203(C), pages 297-310.
    6. Rahn, Eric & Vaast, Philippe & Läderach, Peter & van Asten, Piet & Jassogne, Laurence & Ghazoul, Jaboury, 2018. "Exploring adaptation strategies of coffee production to climate change using a process-based model," Ecological Modelling, Elsevier, vol. 371(C), pages 76-89.
    7. A. Araya & P. V. V. Prasad & P. H. Gowda & M. Djanaguiraman & A. H. Kassa, 2020. "Potential impacts of climate change factors and agronomic adaptation strategies on wheat yields in central highlands of Ethiopia," Climatic Change, Springer, vol. 159(3), pages 461-479, April.
    8. Salazar, M.R. & Hook, J.E. & Garcia y Garcia, A. & Paz, J.O. & Chaves, B. & Hoogenboom, G., 2012. "Estimating irrigation water use for maize in the Southeastern USA: A modeling approach," Agricultural Water Management, Elsevier, vol. 107(C), pages 104-111.
    9. Singh, Sukhbir & Boote, Kenneth J. & Angadi, Sangamesh V. & Grover, Kulbhushan K., 2017. "Estimating water balance, evapotranspiration and water use efficiency of spring safflower using the CROPGRO model," Agricultural Water Management, Elsevier, vol. 185(C), pages 137-144.
    10. Escarabajal-Henarejos, D. & Molina-Martínez, J.M. & Fernández-Pacheco, D.G. & García-Mateos, G., 2015. "Methodology for obtaining prediction models of the root depth of lettuce for its application in irrigation automation," Agricultural Water Management, Elsevier, vol. 151(C), pages 167-173.
    11. Aftab Wajid & Khalid Hussain & Ayesha Ilyas & Muhammad Habib-ur-Rahman & Qamar Shakil & Gerrit Hoogenboom, 2021. "Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments," Agriculture, MDPI, vol. 11(11), pages 1-22, November.
    12. Yang, Meijian & Wang, Guiling & Lazin, Rehenuma & Shen, Xinyi & Anagnostou, Emmanouil, 2021. "Impact of planting time soil moisture on cereal crop yield in the Upper Blue Nile Basin: A novel insight towards agricultural water management," Agricultural Water Management, Elsevier, vol. 243(C).

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