Adaptation to climate change by determining grapevine cultivar differences using temperature-based phenology models

Abstract

Grapevine phenology is advancing with increased temperatures associated with climate change. This may result in higher fruit sugar concentrations at harvest and/or earlier compressed harvests and changes in the synchrony of sugar with other fruit metabolites. One adaptation strategy that growers may use to maintain typicity of wine style is to change cultivars. This approach may enable fruit to develop under temperature conditions similar to those typically associated with that wine style. We demonstrate that Grapevine Flowering Véraison (GFV) and the Grapevine Sugar Ripeness (GSR) models can be implemented as a means of testing the suitability of alternative cultivars as an adaptation strategy to climate change.Previous viticulture temperature-based models were reviewed and compared with the GFV and GSR models. The results from the original GFV and GSR models were combined to evaluate the classification of the 20 most represented cultivars. The GFV and GSR models were tested for three new historic and contrasting datasets: 31 cultivars in the VitAdapt collection, Bordeaux; Chardonnay, Champagne; and Sauvignon blanc, Marlborough. Errors of predictions were less than a week for flowering and véraison, and within 7-10 days for the time to reach relevant target sugar concentrations for these datasets. Future GFV and GSR projections for Chardonnay resulted in an advance at a rate of one to two days per decade for flowering and véraison, and two to five days per decade for time to 170 g/L sugar concentration for RCP 4.5 and 8.5 respectively.Therefore, the GFV and GSR models are highly accurate and easy-to-use temperature-based phenological models for predicting flowering, véraison and time to target sugar concentrations when tested under new conditions. The models can be applied for characterising new cultivars, and assessing thermal time to flowering, véraison and different sugar targets. They can be used to assess cultivar performance in winegrowing areas worldwide under current or future climate conditions. The classifications therefore enable growers and researchers to compare the phenology of cultivars in a region today and to consider adaptation options: selecting later ripening cultivars or choosing alternative sites in the context of climate change.

Effects of sunlight exclusion on leaf gas exchange, berry composition, and wine flavour profile of Cabernet-Sauvignon from the foot of the north side of Mount Tianshan and a semi-arid continental climate

“…If grapes ripen too early, they can have high sugar levels and low acidity, which will lead to excessive alcohol and lack of freshness in the resulting wines. Late ripening can result in unripe grapes and wines marked by green flavours (Parker et al, 2020). We did not harvest on the same day, because the development stages of the two treatments were significantly different.…”

Heat Unit Requirements of “Flame Seedless” Table Grape: A Tool to Predict Its Harvest Period in Protected Cultivation

“…Plants 2021, 10, x FOR PEER REVIEW 5 of 1412 July 2009, while the berries reached the maturation index established for harvesting at 16 July 2009; that is, four days later than predicted. If we used the typical meteorological year instead of the average year, then the prediction ability was greatly improved since harvest was forecast at 15 July 2009; that is only one day before harvesting.…”

“…On the contrary, global warming projections indicate the anticipation of the phenological events and that plants will fulfill their heat requirements in a shorter period [ 11 ]. Climate changes also makes more difficult forecasting harvest dates [ 12 ] and planning the cultivation techniques [ 13 ]. An accurate estimation of heat requirements based on cardinal temperatures regardless the time required for its fulfillment can be helpful in this context [ 14 ].…”

Projected Wine Grape Cultivar Shifts Due to Climate Change in New Zealand

“…In the most recent validation (Parker et al, 2020b ), the model was tested for the period 2004–2020 and it was found the goodness-of-fit (root mean squared error) was 6.67, 4.67, and 9.67 days for flowering, véraison and time to 200 g/l sugar concentrations respectively which was within prediction ranges of the original calibrations and validations of cultivars by the models (Parker et al, 2011 , 2013 , 2020a ). In addition, the temperature relationships for the GSR and GFV models have been successfully validated beyond the original model development datasets (Verdugo-Vásquez et al, 2019 ; Parker et al, 2020b ; Ramos and de Toda, 2020 ; Wang et al, 2020 ) including other cool climate areas such as Champagne (Parker et al, 2020a ) and areas in China (Wang et al, 2020 ). They have also been applied in combination with future climate change projections (van Leeuwen et al, 2019 ; de Rességuier et al, 2020 ; Parker et al, 2020b ; Ramos and de Toda, 2020 ).…”

“…In addition, the temperature relationships for the GSR and GFV models have been successfully validated beyond the original model development datasets (Verdugo-Vásquez et al, 2019 ; Parker et al, 2020b ; Ramos and de Toda, 2020 ; Wang et al, 2020 ) including other cool climate areas such as Champagne (Parker et al, 2020a ) and areas in China (Wang et al, 2020 ). They have also been applied in combination with future climate change projections (van Leeuwen et al, 2019 ; de Rességuier et al, 2020 ; Parker et al, 2020b ; Ramos and de Toda, 2020 ). Together, these tests and applications of the GSR and GFV models illustrate the models' broad applicability to new sites and different climates.…”