A functional-structural plant model that simulates whole- canopy gas exchange of grapevine plants (Vitis vinifera L.)...

Scaling from single-leaf to whole-canopy photosynthesis faces several complexities related to variations in light interception and leaf properties. To evaluate the impact of canopy strucuture on gas exchange, we developed a functional-structural plant model to upscale leaf processes to the whole canopy based on leaf N content. The model integrates different models that calculate intercepted radiation, leaf traits and gas exchange for each leaf in the canopy. Our main objectives were (1) to introduce the gas exchange model developed at the plant level by integrating the leaf-level responses related to canopy structure, (2) to test the model against an independent canopy gas exchange dataset recorded on different plant architectures, and (3) to quantify the impact of intra-canopy N distribution on crop photosynthesis.

The model combined a 3D reconstruction of grapevine (Vitis vinifera) canopy architecture, a light interception model, and a coupled photosynthesis and stomatal conductance model that considers light-driven variations in N distribution. A portable chamber device was constructed to measure whole-plant gas exchange to validate the model outputs with data collected on different training systems. Finally, a sensitivity analysis was performed to evaluate the impact on C assimilation of different N content distributions within the canopy.

By considering a non-uniform leaf N distribution within the canopy, our model accurately reproduced the daily pattern of gas exchange of different canopy architectures. The gain in photosynthesis permitted by the non-uniform compared with a theoretical uniform N distribution was about 18 %, thereby contributing to the maximization of C assimilation. By contrast, considering a maximal N content for all leaves in the canopy overestimated net CO2 exchange by 28 % when compared with the non-uniform distribution.

The model reproduced the gas exchange of plants under different training systems with a low error (10 %). It appears to be a reliable tool to evaluate the impact of a grapevine training system on water use efficiency at the plant level.