Climate variability and its effects in the Penedès vineyard region (NE Spain)

Heatwaves or extreme heat events can be particularly harmful to agriculture. Grapevines grown in the Douro winemaking region are particularly exposed to this threat, due to the specificities of the already warm and dry climatic conditions. Furthermore, climate change simulations point to an increase in the frequency of occurrence of these extreme heat events, therefore posing a major challenge to winegrowers in the Mediterranean type climates. The current study focuses on the application of the STICS crop model to assess the potential impacts of heatwaves in grapevine yields over the Douro valley winemaking region. For this purpose, STICS was applied to grapevines using high-resolution weather, soil and terrain datasets over the Douro. To assess the impact of heatwaves, the weather dataset (1989-2005) was artificially modified, generating periods with anomalously high temperatures (+5 ºC), at certain onset dates and with specific durations (from 5 to 9 days). The model was run with this modified weather dataset and results were compared to the original unmodified runs. The results show that heatwaves can have a very strong impact on grapevine yields, strongly depending on the onset dates and duration of the heatwaves. The highest negative impacts may result in a decrease in the yield by up to -35% in some regions. Despite some uncertainties inherent to the current modelling assessment, the present study highlights the negative impacts of heatwaves on viticultural yields in the Douro region, which is critical information for stakeholders within the winemaking sector for planning suitable adaptation measures.

The work shows the results of a year of experimentation (2020) in a Syrah variety vineyard in La Roda (Castilla-La Mancha, Spain). The trial approach was on a randomized block design with two factors: Irrigation (I) and Pruning (P).
Irrigation schedules were adjusted to apply amounts close to 1,500 m3/ha. With this provision, 2 different irrigation treatments were proposed: I1) Start of irrigation from pea-sized grape to post-harvest (providing at least 20 % of the total amount of irrigation water to be provided post-harvest); I2) Start of irrigation from pea-sized grape to harvest (usual irrigation practice in the study area). Pruning was proposed with two treatments, one at the end of January (P1), which is pruning on a conventional date; and P2) pruning carried out at the beginning of budding. In total, 4 repetitions were designed with 4 elementary plots, each one of them representing one of the proposed treatments (I1P1; I1P2; I2P1; I2P2). In total, 16 plots were worked on and each elementary plot consisted of 30 strains, distributed in 3 lines.
The productive response was evaluated with the yield results of the harvest harvested at 23 ºBrix. The qualitative response was measured in the musts through the indices of technological (acidity, pH and potassium) and phenolic maturity and aromatic compounds in free and glycosylated fractions. The treatments tested had, in general, an effect on the different variables analyzed.

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.

Wine terroir describes the collectively recognized relation between a geographical area and the distinctive organoleptic characteristics of the wines produced in it. The overriding objective in terroir studies is therefore to provide scientific proof relating the properties of terroir components to wine quality and typicity. In scientific circles, the role of climate (macro-, meso- and micro-) on grape and wine characteristics is well documented and accepted as the most critical. Moreover, there has been increasing interest in recent years about new elements with possible importance in shaping wine terroir like berry/leaf/soil microbiology or even aromatic plants in proximity to the vineyard conferring flavors to the grapes. However, the actual effect of these factors is also dependent on complex interactions with plant material (variety/clone, rootstock, vine age) and with human factors.
The contribution of soil, although a fundamental component of terroir and extremely popular among wine enthusiasts, remains a much-debated issue among researchers. The role of geology is probably the one mostly associated by consumers with the notion of terroir with different parent rocks considered to give birth to different wine styles. However, the relationship between wine properties and the underlying parent material raises a lot of controversy especially regarding the actual existence of rock-derived flavors in the wine (e.g. minerality). As far as the actual soil properties are concerned, the effect of soil physical properties is generally regarded as the most significant (e.g sandy soils being associated with lighter wines while those on clay with colored and tannic ones) mostly through control of water availability which ultimately modifies berry ripening conditions either directly by triggering biosynthetic pathways, or indirectly by altering vigor and yield components. The role of soil chemistry seems to be weakly associated to wine sensory characteristic, although N, K, S and Ca, but also soil pH, are often considered important in the overall soil effect.
Recently, in the light of evidence provided by precision agriculture studies reporting a high variability of vineyard soils, the spatial scale should also be taken into consideration in the evaluation of the soil effects on wines. While it is accepted that soil effects become more significant than climate on a local level, it is not clear whether these micro-variations of vineyard soils are determining in the terroir effect. Moreover, as terroir is not a set of only natural factors, the magnitude of the contribution of human-related factors (irrigation, fertilization, soil management) to the soil effect still remains ambiguous. Lastly, a major shortcoming of the majority of works about soil effects on wine characteristics is the absence of connection with actual vine physiological processes since all soil effects on grape and wine chemistry and sensorial properties are ultimately mediated through vine responses.
This article attempts to breakdown the main soil attributes involved in the terroir effect to suggest an improved understanding about soil’s true contribution to wine sensory characteristics. It is proposed that soil parameters per se are not as significant determining factors in the terroir effect but rather their mutual interactions as well as with other natural and human factors included in the terroir concept. Consequently, similarly to bioclimatic indices, composite soil indices (i.e. soil depth, water holding capacity, fertility, temperature etc), incorporating multiple soil parameters, might provide a more accurate and quantifiable means to assess the relative weight of the soil component in the terroir effect.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.