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ORYZA2000: modeling lowland rice

Author

Listed:
  • Bouman, B.A.M.
  • Kropff, M.J.
  • Wopereis, M.C.S.
  • ten Berge, H.F.M.
  • van Laar, H.H.

Abstract

ORYZA2000: modeling lowland rice is the next in a series of (lowland) rice growth simulation models developed by IRRI and Wageningen University and Research Centre (WUR) in the early to mid-1990s in the project "Simulation and Systems Analysis for Rice Production (SARP)." It is an update and integration of the models ORYZA1 for potential production, ORYZA_W for water-limited situations, and ORYZA-N for nitrogen-limited production. Since the release of these models, new insights into crop growth and water-balance processes have been gained, new scientific subroutines developed, and programming standards and tools improved. These developments warranted a new release in the ORYZA series. Besides the scientific and programming updates, ORYZA2000 contains new features that allow a more explicit simulation of crop management options, such as irrigation and nitrogen fertilizer management. It can also be used in application-oriented research such as the design of crop ideotypes and the analysis of yield gaps to the optimization of crop management, the ex ante analysis of the effects of climate change on crop growth, and agroecological zonation.

Suggested Citation

  • Bouman, B.A.M. & Kropff, M.J. & Wopereis, M.C.S. & ten Berge, H.F.M. & van Laar, H.H., 2001. "ORYZA2000: modeling lowland rice," IRRI Books, International Rice Research Institute (IRRI), number 281825.
    • Handle: RePEc:ags:irricg:281825
    DOI: 10.22004/ag.econ.281825
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    Citations

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    Cited by:

    1. Stella, Tommaso & Bregaglio, Simone & Confalonieri, Roberto, 2016. "A model to simulate the dynamics of carbohydrate remobilization during rice grain filling," Ecological Modelling, Elsevier, vol. 320(C), pages 366-371.
    2. Belder, P. & Bouman, B. A.M. & Spiertz, J.H.J., 2007. "Exploring options for water savings in lowland rice using a modelling approach," Agricultural Systems, Elsevier, vol. 92(1-3), pages 91-114, January.
    3. Timsina, Jagadish & Dutta, Sudarshan & Devkota, Krishna Prasad & Chakraborty, Somsubhra & Neupane, Ram Krishna & Bishta, Sudarshan & Amgain, Lal Prasad & Singh, Vinod K. & Islam, Saiful & Majumdar, Ka, 2021. "Improved nutrient management in cereals using Nutrient Expert and machine learning tools: Productivity, profitability and nutrient use efficiency," Agricultural Systems, Elsevier, vol. 192(C).
    4. Bouman, B.A.M. & Peng, S. & Castaneda, A.R. & Visperas, R.M., 2005. "Yield and water use of irrigated tropical aerobic rice systems," Agricultural Water Management, Elsevier, vol. 74(2), pages 87-105, June.
    5. Confidence Duku & Adam H. Sparks & Sander J. Zwart, 2016. "Spatial modelling of rice yield losses in Tanzania due to bacterial leaf blight and leaf blast in a changing climate," Climatic Change, Springer, vol. 135(3), pages 569-583, April.
    6. Zuidema, Pieter A. & Leffelaar, Peter A. & Gerritsma, Wouter & Mommer, Liesje & Anten, Niels P.R., 2005. "A physiological production model for cocoa (Theobroma cacao): model presentation, validation and application," Agricultural Systems, Elsevier, vol. 84(2), pages 195-225, May.
    7. Sasai, Takahiro & Nakai, Saori & Setoyama, Yuko & Ono, Keisuke & Kato, Soushi & Mano, Masayoshi & Murakami, Kazutaka & Miyata, Akira & Saigusa, Nobuko & Nemani, Ramakrishna R. & Nasahara, Kenlo N., 2012. "Analysis of the spatial variation in the net ecosystem production of rice paddy fields using the diagnostic biosphere model, BEAMS," Ecological Modelling, Elsevier, vol. 247(C), pages 175-189.
    8. Silva, João Vasco & Pede, Valerien O. & Radanielson, Ando M. & Kodama, Wataru & Duarte, Ary & de Guia, Annalyn H. & Malabayabas, Arelene Julia B. & Pustika, Arlyna Budi & Argosubekti, Nuning & Vithoon, 2022. "Revisiting yield gaps and the scope for sustainable intensification for irrigated lowland rice in Southeast Asia," Agricultural Systems, Elsevier, vol. 198(C).
    9. Timsina, J. & Wolf, J. & Guilpart, N. & van Bussel, L.G.J. & Grassini, P. & van Wart, J. & Hossain, A. & Rashid, H. & Islam, S. & van Ittersum, M.K., 2018. "Can Bangladesh produce enough cereals to meet future demand?," Agricultural Systems, Elsevier, vol. 163(C), pages 36-44.
    10. Boling, A.A. & Tuong, T.P. & van Keulen, H. & Bouman, B.A.M. & Suganda, H. & Spiertz, J.H.J., 2010. "Yield gap of rainfed rice in farmers' fields in Central Java, Indonesia," Agricultural Systems, Elsevier, vol. 103(5), pages 307-315, June.
    11. Gao, Ya & Xu, Xu & Sun, Chen & Ding, Shibo & Huo, Zailin & Huang, Guanhua, 2021. "Parameterization and modeling of paddy rice (Oryza sativa L. ssp. japonica) growth and water use in cold regions: Yield and water-saving analysis," Agricultural Water Management, Elsevier, vol. 250(C).
    12. Jones, M.R. & Singels, A., 2015. "Analysing yield trends in the South African sugar industry," Agricultural Systems, Elsevier, vol. 141(C), pages 24-35.
    13. Blango, Mohamed M. & Cooke, Richard A.C. & Moiwo, Juana P., 2019. "Effect of soil and water management practices on crop productivity in tropical inland valley swamps," Agricultural Water Management, Elsevier, vol. 222(C), pages 82-91.
    14. Miltiadis Iatrou & Christos Karydas & George Iatrou & Ioannis Pitsiorlas & Vassilis Aschonitis & Iason Raptis & Stelios Mpetas & Kostas Kravvas & Spiros Mourelatos, 2021. "Topdressing Nitrogen Demand Prediction in Rice Crop Using Machine Learning Systems," Agriculture, MDPI, vol. 11(4), pages 1-17, April.
    15. Tao Li & Olivyn Angeles & Ando Radanielson & Manuel Marcaida & Emmali Manalo, 2015. "Drought stress impacts of climate change on rainfed rice in South Asia," Climatic Change, Springer, vol. 133(4), pages 709-720, December.
    16. Gao, Ya & Sun, Chen & Ramos, Tiago B. & Huo, Zailin & Huang, Guanhua & Xu, Xu, 2023. "Modeling nitrogen dynamics and biomass production in rice paddy fields of cold regions with the ORYZA-N model," Ecological Modelling, Elsevier, vol. 475(C).
    17. Li, Yan & Zhou, Qingguo & Zhou, Jian & Zhang, Gaofeng & Chen, Chong & Wang, Jing, 2014. "Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions," Ecological Modelling, Elsevier, vol. 291(C), pages 15-27.
    18. Hayashi, Keiichi & Llorca, Lizzida & Rustini, Sri & Setyanto, Prihasto & Zaini, Zulkifli, 2018. "Reducing vulnerability of rainfed agriculture through seasonal climate predictions: A case study on the rainfed rice production in Southeast Asia," Agricultural Systems, Elsevier, vol. 162(C), pages 66-76.
    19. Timsina, J. & Buresh, R.J. & Dobermann, A. & Dixon, J. (ed.), 2011. "Rice-maize systems in Asia: current situation and potential," IRRI Books, International Rice Research Institute (IRRI), number 164490.
    20. Boling, A.A. & Bouman, B. A.M. & Tuong, T.P. & Murty, M.V.R. & Jatmiko, S.Y., 2007. "Modelling the effect of groundwater depth on yield-increasing interventions in rainfed lowland rice in Central Java, Indonesia," Agricultural Systems, Elsevier, vol. 92(1-3), pages 115-139, January.
    21. Ding, Yimin & Wang, Weiguang & Zhuang, Qianlai & Luo, Yufeng, 2020. "Adaptation of paddy rice in China to climate change: The effects of shifting sowing date on yield and irrigation water requirement," Agricultural Water Management, Elsevier, vol. 228(C).

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