Project
Modelling rice adaptation to drought stress
Drought is a complex stress for crops. They react with changes in photosynthesis, morphology (e.g. root size and leaf thickness) and other crop traits. These changes, which are sometimes reversible, have a long-term impact on crop productivity. Photosynthesis responds rapidly to drought, faster than morphology, for example. Signals arising from the photosynthetic apparatus drive chloroplast-level acclimation and have systemic consequences that affect morphology and other crop traits. Thus, drought-induced changes in photosynthesis have both direct and indirect effects on crop productivity.
Unraveling the photosynthesis process
Photosynthesis is a relatively well understood complex process. It displays flexibility and adaptability over many scales of integration which gives rise to a diversity of phenotypes in response to acclimation to specific environments. These features have made it a popular subject for systems biology studies and there are many models describing the steady-state behaviour of photosynthesis. The real world environment of photosynthesis is, however, not stable and displays fluctuations in basic properties (such as irradiance, temperature, and drought) over a range of time scales from the second range upwards. Current steady-state photosynthesis models cannot account for the effects of fluctuating drought on photosynthesis.
Interaction between models and experiments
We want to develop a robust mathematical model that quantitatively describes the dynamics of physiological acclimation and adaptation of rice photosynthesis to drought (scaling from chloroplasts to the whole leaf). This model, together with the effects on morphological and other traits, will be integrated into a dynamic crop growth model, to perform multi-scale modelling. This modelling project will run in parallel with already funded experimental projects so that modelling and experimentation interact in an iterative manner. The model-based simulation study will allow scaling up from chloroplasts to leaf to crop for in silico analysis of relations between photo-oxidative response and crop production, thereby showcasing Crop Systems Biology studies.
Supervising team
X.Yin, J. Harbinson, P.C. Struik and J. Molenaar