A new chemiluminescence method related to molecules derived from Botrytis cinerea for characterization of Aszu wines from Tokaj, from Hungary

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.

Majority of California’s vineyards rely on supplemental irrigation to overcome abiotic stressors. In the context of climate change, increases in growing season temperatures and crop evapotranspiration pose a risk to adaptation of viticulture to climate change. Vineyard cover crops may mitigate soil erosion and preserve water resources; but there is a lack of information on how they contribute to vineyard resiliency under tillage systems. The aim of this study was to identify the optimum combination of cover crop sand tillage without adversely affecting productivity while preserving plant water status. Two experiments in two contrasting climatic regions were conducted with two cover crops, including a permanent short stature grass (P. bulbosa hybrid), barley (Hordeum spp), and resident vegetation under till vs. no-till systems in a Ruby Cabernet (V. vinifera spp.) (Fresno) and a Cabernet Sauvingon (Napa) vineyard. Results indicated that permanent grass under no-till preserved plant available water until E-L stage 17. Consequently, net carbon assimilation of the permanent grass under no-till system was enhanced compared to those with barley and resident vegetation. On the other hand, the barley under no-till system reduced grapevine net carbon assimilation during berry ripening that led to lower content of nonstructural carbohydrates in shoots at dormancy. Components of yield and berry composition including flavonoid profile at either site were not adversely affected by factors studied. Switching to a permanent cover crop under a no-till system also provided a 9% and 3% benefit in cultural practices costs in Fresno and Napa, respectively. The results of this work provides fundamental information to growers in preserving resiliency of vineyard systems in hot and warm climate regions under context of climate change.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

Wine quality is strongly linked to climate. Quality scores are often driven by climate variation across different winegrowing regions and years, but also influenced by other aspects of terroir, including variety. While recent work has looked at the relationship between quality scores and climate across many European regions, less work has examined New World winegrowing regions. Here we used scores from three major rating systems (Wine Advocate, Wine Enthusiast and Wine Spectator) combined with daily climate and phenology data to understand what drives variation across wine quality scores in major regions of the Western US, including regions in California, Oregon and Washington. We examined effects of variety, region, and in what phenological period climate was most predictive of quality. As in other studies, we found climate, based mainly on growing degree day (GDD) models, was generally associated with quality—with higher GDD associated with higher scores—but variety and region also had strong effects. Effects of region were generally stronger than variety. Certain varieties received the highest scores in only some areas, while other varieties (e.g., Merlot) generally scored lower across regions. Across phenological stages, GDD during budbreak was often most strongly associated with quality. Our results support other studies that warmer periods generally drive high quality wines, but highlight how much region and variety drive variation in scores outside of climate.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).