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 Advancing rice science through crop modeling


Crop modeling and systems analysis have become important tools in modern agricultural research. A crop model synthesizes our insights into the physiological and ecological processes that govern crop growth and development in logical algorithms and mathematical equations. ORYZA is a crop model for rice, which embodies more than 30 years of global research.

IRRI has been involved in crop modeling since the 1970s, and has participated in the Simulation and Systems Analysis for Rice Production (SARP) Project from mid-80s to mid-90s. Though this project, in collaboration with the Wageningen University and Research Centre (WUR) and 16 national agricultural research and extension systems in Asia, the generic crop growth model MACROS was released, which was followed by the ORYZA model series for rice. Since then, modeling efforts at IRRI have continued with the extension and application of the ORYZA series.

It has been conceived and developed by the International Rice Research Institute (IRRI) and Wageningen University and Research Center (WUR)


The continuous challenge to meet global food demand is at the heart of IRRI’s mission. ORYZA is driving many of the innovations led by the Institute to develop and disseminate technologies to improve the resilience of rice-based farming systems and the sustainability of rice production at scale.

How does it work?

ORYZA can test our understanding of crop performance by comparing simulation results with experimental observations, thus making the gaps in our knowledge explicit. Experiments can then be designed to fill these gaps. Once a model is validated, it can be used to help analyze and interpret field experiments. It can also be used in application-oriented research such as the design of crop ideotypes, the analysis of yield gaps, the optimization of crop management, the ex-ante analysis of the effects of climate change on crop growth, and agro ecological zonation. ORYZA continues to serve as an ideal tool for research in addressing:

  • optimization of water and nitrogen management
  • identification of constraining factors on yield within site-specific conditions
  • assessment of the climate change effects on production
  • evaluation of varietal performance and effects of traits on target environments
  • understanding and exploring the interaction of Genotype (G), Environment (E), and Management (M) 
  • extrapolation of observed data over wider temporal and spatial scales assisting decision-making
    Integrated with an analytics platform and GIS science, simulation outputs from the model have been used as inputs to policy briefs to promote sustainable rice production.

Next Steps

The ORYZA model has been extended to rice production systems under constraining environments including abiotic stresses such as drought, salinity, and high temperature. ORYZA V3, the latest model assists in the development of climate-ready rice varieties adapted to drought, salinity, submergence, and anaerobic germination . As rice research advances and the digitalization of agriculture becomes the norm, ORYZA will evolve to keep pace with the emerging research needs and technologies. While ORYZA contributes to the collection and processing of big data, current efforts aim to increase its capabilities on genomics and sequencing, as well as adapting the current algorithm to operate in a spatial context, at multiple scales and using GIS/remote sensing data.

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