Increasing temperatures and heat wave intensity have become a major concern for wine grape farmers due to their effect on grape production and quality. As a result, growers are exploring approaches to protect berries while maintaining grape quality and optimum yield. Some approaches include reducing grape exposure by natural shading through management of pruning, using row orientation, or changing the trellis type and row spacing. However, given the extremely large number of interacting variables that determine berry temperature (e.g., radiation load, bunch exposure, topography, latitude, climate), it is not feasible to independently vary all of these parameters in field experiments, thus making it difficult to determine optimal strategies at a given location. Crop models have the potential to complement experimental efforts by allowing for controlled study of the interactions between these numerous variables in order to determine optimal strategies for reducing the effect of excess temperature on crop productivity.
Given the significant rise of berry temperature when exposed to direct sunlight, this research first evaluated widely used assumptions for modeling solar radiation interception in plant canopies, namely assumptions of vegetation homogeneity and isotropy. Because of their simple, tractable form, 1D models of light interception that assume homogeneity or isotropy are used across a broad range of disciplines. However, it is relatively well-known that with varying levels of vegetation sparseness and preferential leaf orientations, the implicit assumptions of vegetation homogeneity and isotropy in simple 1D models are frequently violated. Yet, it is not well understood at what point this leads to high model errors. Results of this work provided quantitative guidance as to when a simple 1D model can be appropriately used to estimate light interception. For canopies in which plant spacing was much smaller than the canopy height, the 1D homogeneous and isotropic model produced small errors. However, for discontinuous and anisotropic canopies, errors significantly increased with increasing the sparseness of the canopy.
Results of this initial study suggested that a 3D model was needed to accurately quantify grapevine light interception and to predict the complex interactions between vine architecture and microclimate at the berry level. In doing so, strategies for mitigating unfavorable grape berry temperatures could be identified and evaluated. This research developed and validated a 3D model for grape berry temperature, supported by field and laboratory experiments. The model accurately simulated the spatial and temporal fluctuations of grape berries in vineyards with different climates, topographies, and trellises. Furthermore, the effects of shade cloth on berry temperature were incorporated in the model and validated against experimental data. By using this modeling approach, different vineyard designs and their effect on berry temperature weresimulated. The results provided quantitative guidance on the effect of different vineyard designs and management strategies that have the potential to reduce the effect of excess temperature in a warming climate. For instance, on flat terrain, NE-SW row orientation provided the best compromise of berry light and temperature balance between opposing sides of the vine while avoiding excessive berry temperatures, while N-S rows provided good daily symmetry but had a risk of fruit overexposure and high temperatures in the afternoon. Slopes with southern or western exposure increased imbalance and risk of high berry temperatures, which in some cases could not be well-managed by shade cloth.
