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Predicting rice yield under drought

Integrated growth and metabolic models predict the metabolism of rice growth under normal and water-limited conditions.

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Around 50% of the world’s population depend on rice for their daily nourishment. In this regard, the improvement in yield of rice grain is one of the most important areas in the field of rice research.

Rice is one of the most drought-susceptible plants due to its small root system, thin cuticular wax, and swift stomatal closure. A better understanding of drought-induced changes in rice are essential for guiding sustainable rice production under climate change.

Chun Yue Maurice Cheung, Assistant Professor of Science at Yale-NUS College in Singapore and Rahul Shaw, Postdoctoral fellow at Radboud University in The Netherlands collaborated on a project to examine the effect of drought on rice growth, yield, and metabolic processes.

“To date, there has not be much progress directly relating climate-related parameters, such as ground water potential, to be used as constraints in a genome-scale metabolic model,” says Cheung. “These parameters are present in crop growth models, so we integrated two model types – flux balance analysis and plant growth – to study metabolic adaptions to changes in climate.”

Flux balance analysis models focus on internal cellular behavior by predicting the activities of metabolic processes such as nutrient and energy conversion mechanisms. The authors updated and used the existing rice genome-scale metabolic model (GSM) Os2384. Plant growth models calculate the carbon assimilation rates of canopy structure and the production of organ-specific biomass over the timescale of a few months as driven by environmental factors such as drought. The authors used WOrld FOod STudies (WOFOST) for this study. The integration of these models input day-specific biomass constraints for each organ from the plant growth model into the genome-scale metabolic model to determine daily metabolic changes involved in rice growth from seedling to seed development under normal and water-limited conditions (Figure 1).

Integration of crop growth model and flux balance multi-organ model.

The simulations showed that plants with water-limited stress had lower growth rates and a shorter growth period, which resulted in lower overall biomass than normal condition. The lower biomass, in turn, reduced N and C assimilation, transport and storage, resulting in reduced yield.

Plant biomass (leaf, stem, and seed) over the growing period under normal (solid lines) and water-limited (dashed lines) conditions.

To uncover the mechanisms of these changes, the authors assessed the metabolic dynamics. Most of the metabolic differences were observed between the two conditions during reproduction and grain-filling, indicating that these are the stages that are most sensitive to water stress.

“Analysis of metabolism over different growth stages of whole plant development and its comparison between control and stress conditions allows researchers to further understand plant metabolic plasticity and adaptations to a changing climate, and potentially identify targets for improvement,” says Cheung.

This approach can be generalized to any species with available crop growth models and constraint-based metabolic models.

All scripts and models used in this study are open access and freely available at: github.com/mauriceccy/rice-crop-fba-model   

Spanish translation by Lorena Marchant

Rachel Shekar

Rachel (she/her) is a Founding and Managing Editor of in silico Plants. She has a Master’s Degree in Plant Biology from the University of Illinois. She has over 15 years of academic journal editorial experience, including the founding of GCB Bioenergy and the management of Global Change Biology. Rachel has overseen the social media development that has been a major part of promotion of both journals.

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