Viticulture is one of the most important socioeconomic sectors in Portugal. From a global perspective, Portugal is currently the 11th-largest wine producer and the 9th wine exporter in the world [1
]. Portugal accounts for approximately 194,000 ha of vineyard area and with a wine production around 6.7 × 106
]. Almost half of this production is exported, accounting for nearly 2% of national export income [2
]. The country is divided into 14 viticultural regions (12 in the mainland and 2 in the islands), with 25 Denominations of Origin (DOs). Douro/Porto, Vinhos-Verdes, Alentejo, and Lisboa are the main regions in terms of wine production. Although the Alentejo wine region is the most productive [3
], the Douro/Porto wine region has the largest vineyard area and is the main region in terms of production, accounting for ca. 25% of all wine produced in Portugal [2
The Douro/Porto wine region, also known as Douro Demarcated Region (DDR), has unique features, where vineyards are traditionally grown on terraces over steep slopes along the mountainous Douro valley and in an almost monocultural system, resulting in a UNESCO (United Nations Educational, Scientific and Cultural Organization) human heritage vineyard landscape. A large number of grapevine varieties (Vitis vinifera
L.) are grown in the region, being many of them native. The complex physiographic and pedoclimatic characteristics of the DDR not only provide a wide range of terroirs for grapevine growth [4
], but also make wine production very costly in terms of labour force and vineyard management [5
]. Given the heterogeneous conditions in which grapevines are grown within the DDR, it is imperative to better understand the climatic influences on grapevine development in order to improve vineyard management in such a diverse region. In effect, monitoring the phenological phases and timings are some of the most useful information for planning the necessary viticultural practices in each developmental stage. This knowledge may promote more adjusted cultural practices, eventually optimizing production and quality at harvest.
It is known that grapevine development and growth are mainly driven by meteorological and climatic factors [6
]. Therefore, factors such as temperature, solar radiation and precipitation may have a great influence on phenology, yields, and grape berry quality and attributes [7
]. In particular, temperature is a fundamental factor in controlling grapevine phenological development and ripening [9
]. Phenology models have been developed for a wide range of species, including grapevines, and using observational data from many different countries and regions [14
]. Several previous studies have been performed in order to model the main phenological stages of grapevines, e.g., enabling a classification of varieties for technical proposes [15
], to predict phenophases or to assess the impact of climate change on phenology [16
Many different models have been developed during the last 60 years to simulate grapevine phenology. The modelling of budbreak was explored by several authors assuming different hypothesis [17
]: taking or not into account the dormancy period, interactions between dormancy and post-dormancy periods, starting at a fixed date (e.g., January 1st, February 15th, March 15th). These models were tested for many different varieties under different climatic conditions. For flowering and veraison, the conventional linear growing degree-days model (GDD) was initially proposed by Amerine and Winkler [23
]. This simple temperature accumulation model uses daily mean temperatures, with a fixed base temperature of 10 °C, and onsets temperature accumulation at April 1st. Others models have been calibrated and tested to simulate flowering and veraison, such as the linear model proposed by Duchene, et al. [24
], with a formulation similar to the Winkler model, and the curvilinear model of Wang and Engel, later adapted by García de Cortázar-Atauri, et al. [25
]. The latter model was improved by incorporating an optimal temperature (25 to 30 °C) and an upper critical threshold temperature (40 °C). The GFV model (Grapevine Flowering and Veraison model) was proposed by Parker, et al. [26
] and Parker, et al. [27
]. This model is similar to GDD, but with a 0 °C base temperature and starting temperature accumulation on March 1st. This last model was developed to classify different grapevine varieties within them. Finally, Molitor, et al. [28
] developed a high-resolution model to simulate all the phenological stages described in the BBCH (Biologische Bundesanstalt
, Bundessortenamt und CHemische Industrie
) scale using a capped model. As such, the performance of several phenology models should be tested at a regional level, as there is no best model for all varieties and conditions.
Phenological models may also be coupled with climate change scenarios to project the potential impacts of future climates on phenological timings and grapevine development [21
]. Projected increases in temperature are expected to drive earlier development stages and, as a result, a general advancement of grapevine phenology [24
]. Those changes will affect the ripening period, commonly occurring in the warmest part of summer, and may lead to aromas and acidity losses [38
]. Consequently, currently planted varieties, which are grown under quite specific conditions today, may no longer thrive in the same place under modified environmental conditions in the future [39
]. Therefore, it is critical to understand to what extent temperature may influence the timings of the reproductive and vegetative cycles, as well as identifying varietal differences in phenology and maturity [26
]. While several studies have assessed the phenological timings in many regions worldwide, a comprehensive study of phenology in the DDR was not undertaken so far, due to the overall lack of phenological and meteorological data. Hence, the present study attempts to overcome this drawback, by presenting the first grapevine phenological study for the DDR.
Along the previous lines, the aims of the present study are twofold: 1) to identify suitable phenological models for three main phenological timings (budburst, flowering, and veraison) of two leading grapevine varieties (cv. Touriga Franca
and cv. Touriga Nacional
) currently grown in the DDR; 2) to assess the climate change impacts on these phenological timings and varieties. The datasets and methodologies are described in Section 2
. The results are presented in Section 3
. Section 4
will provide a discussion and a summary of the main conclusions.
4. Discussion and Conclusions
Phenological models are a key tool for viticulturists, as they provide valuable information for management and planning in vineyards [7
]. The accurate prediction phenological timings promotes best practices and the timely implementation of suitable measures to optimize grapevine yields and grape berry quality [56
]. Moreover, future projections of potential changes in the phenological timings may also deliver important information for medium-to-long term planning [60
]. Despite the aforementioned high economic value of the DDR, no previous studies were conducted for this region on phenological modelling and simulation. Unique datasets, combining phenological timings with weather station records, in the Douro wine region were used herein. The weather stations used were installed at the vineyard locations, which is of utmost importance for a proper phenological modelling [61
]. Furthermore, two of the most important grapevine varieties cultivated in the Douro wine region (TF and TN) were selected (cv. Touriga Franca
—TF and cv. Touriga Nacional
—TN). Despite the relatively large number of sites in the Douro valley (12 Quintas
), data is only available over a maximum period of 4 years. This dataset was thereby complemented with data from two other Portuguese wine regions (Lisboa
and Vinhos Verdes
) and for the same grapevine varieties (TF and TN). This approach led to more robust results, as the sample sizes for model calibration were significantly enlarged.
It was herein demonstrated that some specific phenological models are particularly suitable to the simulation of the two selected grapevine varieties. For all phenophases, specific parameter values were chosen within each model (e.g., Tb in GDD), either by selecting reference values, recommended from previous studies, or best-fit values. Although the recommended values did not always lead to the best performances in our study, no definite conclusions can be withdrawn, as only two varieties were selected herein and the corresponding sample sizes are relatively low. As a whole, the present study allowed the identification of the best phenological models (a set of eight models per phenophase), thus warranting their application both in an operational mode (real-time monitoring and short-term prediction) and in future climate change projections (long-term prediction). Nevertheless, more data will allow improving the selection of the best model and the accuracy of the predictions.
In general terms, the results highlight that the phenological models are better in simulating flowering or veraison than budburst. This may be due to the fact that dormancy and other relevant physiological processes are not sufficiently understood, but might be important drivers of budburst occurrence. As also described by García de Cortázar-Atauri, Brisson and Gaudillere [19
], no clear improvements were found concerning the incorporation of a dormancy period in the model structure. Moreover, the model performances are generally higher for TF than for TN, which may suggest that the latter is slightly less sensitive to thermal forcing, though this needs to be properly addressed by further research, including field experiments. Overall, the Bidabe-Wang and Sigmoid models showed the best results for budburst in TF, while the Bidabe-GDD and Sigmoid models present the highest performances in TN. For flowering, in both grapevine varieties (TF and TN), the very simple GDD model, with a base temperature of ca. 7 °C, revealed the best performances. Lastly, the Sigmoid model provided the best performances for veraison in both varieties. Hence, the GDD linear model is not always the best approach to model and simulate grapevine phenology, as the phenology–temperature relationship may be of non-linear nature. The present study results are comparable, in terms of model performance, to other studies in other winemaking regions worldwide [19
]. Although the aforementioned models provide the best approaches, it is important to bear in mind that they are bound to this particular phenology dataset.
Climate change projections of the phenophase timings, based on a two-member ensemble of state-of-the-art climate model chains, hinted at anticipations of the phenophase timings up to 10–12 days until the end of the twentieth first century, though with some dissimilarities amongst phenophases and varieties. In addition, there is a strong coherency between phenological models, as the results do not change significantly with the model choice, apart from a few exceptions, thus highlighting the robustness of the projections. Nonetheless, different grapevines varieties exhibit greater phenological sensitivity to temperature changes than others, which limits the extrapolation of the results found herein to other locations and varieties. These projections for the Douro are in agreement with observed trends worldwide, such as for Alsace (France), [Jones [66
]] for the California (USA) and Bock, et al. [67
] for Franconia (Germany). These shifts towards earlier phenophase onsets can potentially result in changes to the currently established wine characteristics and typicity. In effect, the expected warming may result in unbalanced wines, with high alcoholic content and excessively low acidity and altered colour and aroma [68
]. These impacts can be partially overcome through the adoption of suitable adaptation measures, such as selection of grapevine varieties that tend to produce berries with lower sugar contents and higher acidity levels in warm climates. Suitable selections of variety-clone-rootstock combinations are among the most effective medium-to-long term measures to cope with climate change. The cultivation of late maturation cultivars is also key to mitigate the anticipation of phenological stages in the vineyards. Short term measures, like irrigation, application of sun screens, changes in training systems, soil management and mulching application, may also be envisioned by producers and winemakers.
The present study aims at providing some initial insights that can be of use not only to future research, but also to regional stakeholders. In the near future, it is expected that the outcomes of this study will be implemented on a web platform, maintained by ADVID, which will deliver information on phenological timings to regional wine companies and grounded on a network of operational weather stations. Future research should also envision the improvement of the current models, such as by extending the phenological datasets with new data from other regions in Portugal or in other countries where the selected varieties also grow. Other grapevine varieties may also be considered in future studies, but there is a critical lack of information for them, particularly on the Douro native/autochthonous varieties, which may considerably hamper their simulation.