Yufeng He, Yu Wang, Douglas Friedel, Meagan Lang, Megan Matthews

Photosynthesis and crop growth are inseparable processes that govern plant carbon assimilation and allocation. An accurate model description of these processes can bridge dynamics at the leaf and canopy levels, assisting in identifying potential photosynthetic improvements that can be converted into increased yield. Integrating multiscale biophysical processes and achieving computational effectiveness for seasonal simulations, however, are challenging. Here, we present a fully coupled modelling framework that integrates a metabolic model of C3 photosynthesis (ePhotosynthesis) and a semi-mechanistic crop growth model (BioCro). We replaced the leaf-level Farquhar photosynthesis model in BioCro with the ePhotosynthesis model that mechanistically describes the photosystem electron transport processes and the C3 carbon metabolism including the Calvin–Benson–Bassham cycle and the photorespiratory pathway. The coupled BioCro-ePhotosynthesis model was calibrated to represent a soybean cultivar and developed to be operationally fast for seasonal simulations. As an example of model application, we conducted a global sensitivity analysis of 26 enzymes under an average daytime intercepted radiation of 400 µmol m⁻² s⁻¹, identifying 2 enzymes, phosphoglycerate kinase (PGK) and phosphoribulokinase (PRK), which had the largest impact on the leaf-level assimilation. Increasing PGK and PRK by 2-fold was predicted to increase the leaf-level assimilation by 8.3 % and the final seed yield by 6.75 % ± 0.5 % over 4 years of observed field climate data. The coupled BioCro-ePhotosynthesis model provides a seamless and efficient integration between the leaf-level metabolism and the field-level yield over a full growing season. The coupled model could be further applied to investigate non-steady-state photosynthetic processes such as non-photochemical quenching.