Toward a Dynamic Photosynthesis Model to Guide Yield Improvement in C4 Crops.

Abstract

The most productive C4 food and biofuel crops, such as maize, sorghum, and sugarcane, all utilize NADP-ME type C4 photosynthesis. Despite high productivities, these crops fall well short of the theoretical maximum solar conversion efficiency of 6%. Understanding the basis of these inefficiencies is key to bioengineering and breeding strategies to increase sustainable productivity of these C4 crops. Photosynthesis is studied predominantly at steady-state in saturating light. In field stands of these crops, light is continually changing, and often with rapid fluctuations. While light may change in a second, adjustment of photosynthesis may take many minutes, leading to inefficiencies. We measured the rates of CO2 uptake and stomatal conductance of maize, sorghum and sugarcane under fluctuating light regimes. The gas exchange results were combined with a new dynamic photosynthesis model to infer the limiting factors under non-steady-state conditions. The dynamic photosynthesis model was developed from an existing C4 metabolic model for maize, extended to include: 1) post-translational regulation of key photosynthetic enzymes and their temperature responses; 2) a dynamic stomatal conductance; and 3) leaf energy balance. Testing the model outputs against measured rates of leaf CO2 uptake and stomatal conductance of the three C4 crops, inferred that Rubisco activase, the PPDK regulatory protein and stomatal conductance are the major limitations to the efficiency of NADP-ME type C4 photosynthesis during dark-to-high light transitions. We propose that the level of influence of these limiting factors make them targets for bioengineering improved photosynthetic efficiency of these key crops.