Bridging chlorophyll content and vertical nitrogen distribution for accurate canopy photosynthesis simulation

Abstract

Accurate simulation of canopy photosynthesis is essential for predicting dry matter accumulation and crop yield. However, most current crop models overlook the effect of vertical distribution of leaf nitrogen and chlorophyll content on photosynthetic capacity at different canopy layers, resulting in greater uncertainties and weaker mechanistic explanation. Here, we developed a novel canopy photosynthesis model that establishes a bridge between chlorophyll content and photosynthetic nitrogen (PN, defined as total leaf nitrogen minus non-photosynthetic nitrogen) across different canopy heights, and then employs chlorophyll content as a reliable proxy forsimulating photosynthesis. The model was calibrated and validated using data from five field experiments under diverse treatments. Results indicate that leaves at higher canopy positions, receiving more light, contain higher nitrogen content and chlorophyll to support greater photosynthetic rates. The nitrogen extinction coefficient (K_N), which characterizes the decline in available of leaf nitrogen, decreases exponentially with increasing LAI, varying among canopy depths, cultivars and growth stages. Chlorophyll shows a stronger correlation with photosynthesis compared to leaf nitrogen. By capturing these dynamics, the model enhances the accuracy of photosynthesis prediction by 60%, particularly correcting the overestimation of canopy photosynthesis and dry matter accumulation during post-flowering. These findings advance the understanding and modelling of canopy-scale photosynthesis in crop models and provide insights for better integration with chlorophyll-related remote sensing data.