A 3D model for simulating spatial and temporal fluctuations in grape berry temperature
Introduction
Increasing temperatures and temperature variability associated with a changing climate have become a major concern for grape producers due to the sensitivity of grape quality to climate, particularly in wine grape production (Jones, 2007, Mira de Ordua, 2010, Pathak, Maskey, Dahlberg, Kearns, Bali, Zaccaria, 2018, Van Leeuwen, Darriet, 2016, White, Diffenbaugh, Jones, Pal, Giorgi, 2006). Short-term temperature extremes associated with heat waves, along with longer-term shifts in seasonal temperature patterns are known to create significant challenges in managing grape quality. Diurnal fluctuations in solar irradiance and air temperature have been shown to affect amino acid and phenylpropanoid berry metabolism at hourly time scales (Reshef et al., 2019). Elevated temperatures during daily or weekly time periods have been shown to decrease anthocyanin concentration around véraison (Gouot et al., 2018). Furthermore, the duration of the elevated temperatures not only has an effect on berry composition but also on berry skin appearance. Exposed berries can be damaged by sunburn, and even a few minutes of high temperature exposure can result in cellular damage (Hulands, Greer, Harper, et al., 2014, Krasnow, Matthews, Smith, Benz, Weber, Shackel, 2010, Wahid, Gelani, Ashraf, Foolad, 2007). Moderate temperatures can also result in berry injury or death after long-term exposure (Wahid et al., 2007).
Grape producers have begun to implement a number of canopy design and management strategies in an attempt to mitigate the negative effects of elevated berry temperatures, including the use of shade cloth (Greer, Weston, Weedon, 2010, Martínez-Lüscher, Chen, Brillante, Kurtural, 2017), trellis design (Kliewer, Wolpert, Benz, 2000, Nicholas, Durham, 2012), and cluster height (Reynolds, Heuvel, 2009, Reynolds, Wardle, Naylor, 1996). However, grape berry microclimate is complex and highly heterogeneous due to interactions between the vine architecture and the environment, making it difficult to understand and predict the integrated effects of mitigation efforts. Experimental field trials are complicated by the fact that measurement of light and temperature at the berry level is labor-intensive and expensive (Zorer et al., 2013). Furthermore, the relatively slow development of grapevine systems means that field trials are costly and may require many years of data collection.
Because it is not feasible to independently vary every parameter that determines berry temperature in field experiments (e.g., radiation load, bunch exposure, climate, topography, latitude, trellis system), crop models provide a means for understanding, and ultimately optimizing, how grapevine design and management practices can be used to mitigate elevated berry temperatures. Previous process-based models have been developed to predict berry radiative fluxes (Pieri, 2010, Zorer, Moffat, Strever, Hunter, 2013) and berry temperatures from environmental parameters (Cola et al., 2009). However, in these models the calculation of absorbed radiation and the parameters to represent specific geometrical canopy structure are often simplified. Therefore, the models cannot account for the vertical and horizontal variability within the cluster or canopy, making it difficult to represent different design or management choices such as using altered trellis designs or pruning practices. Previous work has developed models for individual grape (Smart and Sinclair, 1976) and apple fruits (Saudreau, Sinoquet, Santin, Marquier, Adam, Longuenesse, Guilioni, Chelle, 2007, Thorpe, 1974), and the work of Saudreau et al. (2011) successfully developed a 3D model of apple fruit temperature. However, to the authors’ knowledge, previously developed 3D grapevine structural models (e.g., Iandolino, Pearcy, Williams, 2013, Louarn, Lecoeur, Lebon, 2008) have yet to be coupled with a physically-based berry temperature model.
This work develops and tests a new 3D model for grape berry temperature based on the Helios modeling framework (Bailey, 2019). The berry temperature model was validated using a unique data set that spans four different canopy geometries. The spatially-explicit nature of the model allows for robust representation of varying canopy architectures and their effect on berry temperature. The objective of this study was to accurately simulate the spatial and temporal grape berry temperature fluctuations from different vineyard designs, such that model predictions are robust to changes in vineyard configuration such as row spacing, trellis system, and row orientation.
Section snippets
Model of 3D vineyard geometry
The 3D geometry of the ground, woody tissues, leaves, and grape berries were represented using a mesh of triangular and rectangular elements within the Helios 3D modeling framework (Bailey, 2019). The procedural plant model generator in Helios allows the user to specify average and random geometric parameter values in order to create a given canopy geometry. Grape berries were represented in 3D as tessellated spheres composed of triangular elements, the ground surface was represented as a
Field experiment materials and methods
To validate the 3D model, field experiments were conducted in four Vitis vinifera L. cv. Cabernet Sauvignon vineyards from Sept 19th to Oct 10th (post-véraison to harvest) during the 2018 and 2019 seasons. Two study vineyards were located in Davis, CA (38.53194 N, 121.7528 W) and two others were located in Napa, CA (38.41694 N, 122.4071 W), with each vineyard having a different trellis type. At the research site in Davis, the vines were on a flat terrain, and in Napa the vines were terraced
Ambient berry microclimate
An average characterization of weather conditions during the roughly 3-week period in which the weather stations were deployed is provided in Table 3. A more detailed graphical depiction of the measured air temperature, air relative humidity, wind speed, and of the calculated specific humidity time series data for the different experimental vineyard designs over the chosen validation period is shown in Fig. 2.
During the 3-week period, the daily average air temperature was similar in VSP and
Canopy architecture and berry microclimate
The experimental data collected in this study corresponded to four field sites with different climatic and geographic conditions, and vineyard designs. The average within-canopy ambient microclimate is driven both by the local weather/climate at the site and by the canopy architecture. While it is difficult to directly compare the two Davis experiments (VSP and Wye) because they were conducted during different years, the two Napa plots (Goblet and Unilateral) experienced virtually the same
Conclusion
During periods in which berries are in the shade or during the night time, it is appropriate to assume that the berry temperature is equal to the ambient air temperature. Accurate prediction of large, intermittent increases in berry temperature during periods of solar exposure not only requires a correct application of the berry energy balance, but also accurate representation of the 3D vine structure which determines the transition between sunlit and shaded conditions. Applying the energy
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Financial support of this work was provided by the USDA National Institute of Food and Agriculture Hatch project 1013396. The authors wish to acknowledge Harlan Estate for their gracious collaborative and financial support of the Napa field site experiments.
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