When grape growers try to optimize yield and quality in their crops, the structure of the canopy is a key determining factor. Training systems for vines produce canopy architectures that can be customized for different growing conditions. Modelling the effects on gas exchange of these canopy structures involves using leaf-level data, but accounting for heterogeneities that exist throughout the canopy. Previous modelling has largely neglected these variations.
In a recent article published in Annals of Botany, Jorge A. Prieto and colleagues developed a functional-structural plant model that scales up processes from the leaf level to the whole-canopy level in order to evaluate how canopy structure affects gas exchange. The researchers combined a 3D canopy architecture model, a light interception model, and a model accounting for photosynthesis and stomatal conductance that integrates light-related variation in the distribution of nitrogen in the canopy. They then tested the model using plants with different training systems grown in chambers, evaluating whole-plant gas exchange.
The ability of this model to account for a non-uniform distribution of both light and leaf nitrogen across the canopy allowed it to reliably predict overall daily gas exchange in different canopy architectures with a low level of error. Models considering only the maximum photosynthetic capacity for all leaves over-estimated net carbon dioxide exchange by nearly one third. Though not uncommon, extrapolating the data from individual leaves to the whole canopy can be very misleading. “Functional–structural plant models are increasingly being used to understand complex interactions between plant architecture and physiological processes in many species at different scales,” write the authors. They note that “a key challenge when working with models at the plant scale is their validation with independent field data, especially for fruit perennials. Yet very few attempts have been performed to validate gas exchange models at the plant scale.”
Certain assumptions were made in order to simplify the model, including uniform air temperature, relative humidity, wind speed, and carbon dioxide levels within the canopy. The time step of the model was also set at one hour to keep calculation times manageable, though this means that very rapid changes, such as sun flecks, were not accounted for. In some cases, such as wind variability within the canopy, more data is needed before these factors can be modelled realistically. “These studies open the way to evaluating at the whole-canopy level the possibilities of adapting vineyard management to environmental constraints such as water deficit or high temperature that are usually observed in many viticultural regions worldwide,” write the authors.