Chinese localization of wine aroma descriptors

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Water status impact in viticulture has been widely explored, as it strongly affects grapevine physiology and grape chemical composition. It is considered as a key component of vitivinicultural terroir. Most of the studies concerning grapevine water status have focused on either physiological traits, or berry compounds, or traits involved in wine quality. Here, the response of grapevine to water availability during the ripening period is assessed through non-targeted metabolomics analysis of grape berries by ultra-high resolution mass spectrometry. The grapevine water status has been assessed during 2 consecutive years (2019 & 2020), through carbon isotope discrimination on juices from berries collected at maturity (21.5 brix approx.) for 2 Vitis vinifera cv. Pinot noir (PN) and Chardonnay (CH). A total of 220 grape juices were collected from 5 countries worldwide (Italy; Argentina; France; Germany; Portugal). Measured δ13C (‰) varied from -28.73 to -22.6 for PN, and from -28.79 to -21.67 for CH. These results also clearly revealed higher water stress for the 2020 vintage. The same grape juices have been analysed by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) and Liquid Chromatography coupled to Mass Spectrometry (LC-qTOF-MS), leading to the detection of up to 4500 CHONS containing elemental compositions, and thus likely tens of thousands of individual compounds, which include fatty acids, organic acids, peptides, phenolics, also with high levels of glycosylation. Multivariate statistical analysis revealed that up to 160 elemental compositions, covering the whole range of detected masses (100 –1000 m/z), were significantly correlated to the observed gradients of water status. Examples of chemical markers, which are representative of these complex fingerprints, include various derivatives of the known abscisic acid (ABA), such as phaesic acid or abscisic acid glucose ester, which are significantly correlated with higher water stress, regardless of the variety. Cultivar-specific behaviours could also be identified from these fingerprints. Our results provide an unprecedented representation of the metabolic diversity, which is involved in the water status regulation at the grape level, and which could contribute to a better knowledge of the grapevine mitigation strategy in a climate change context.

The OIV[i] defines terroir as a concept referring to an area in which collective knowledge of the interactions between the physical and biological environment (soil, topography, climate, landscape characteristics and biodiversity features) and vitivinicultural practices develops, providing distinctive wine characteristics. Those are perceptible in the taste of wine, which drives consumer preference and, therefore, wine’s value in the marketplace. Geographical indications (GI) are recognized regulatory constructs formalizing and protecting the nexus between wine taste and the terroir generating it. Despite considering updates, GIs do not consider the nexus as a dynamic one and do not anticipate change, namely of climate. Being climate a fundamental feature of terroir, it strongly impacts wine characteristics, such as taste. According to IPCC[ii], many widespread, rapid and unprecedented changes of climate occurred, some being irreversible over hundreds to thousands of years. Climatic shifts and atmospheric-driven extreme events have been widely reported worldwide. Recent climatic trends are projected to strengthen in upcoming decades, whereas extremes are expected to increase in frequency and intensity, forcing wines away from GI definitions. Geographical shifts of viticultural suitability are projected, often moving into regions and countries different from current ones. Some authors propose adaptation in viticulture, winemaking and product innovation. We show evidence of climate changing wine characteristics in the Douro valley, home of 270-year-old Port GI. We discuss herein resist or adapt stances for when climate changes the nexus between terroir and wine characteristics. Using the MED-GOLD[iii] dashboard, a tool allowing for easy visual navigation of past and future climates, we demonstrate how policymakers can identify future moments, throughout the 21st century under different emission scenarios, when GI specifications will likely need updates (e.g., boundaries, varieties) to reduce climate-change impacts.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

In a collective marketing strategy, the Protected Designation of Origin (PDO) can be used as a quality indicator. To highlight terroir specificities, it is useful to know how the wines are positioned on the local, national or international market from a sensory point of view. This is especially true for a comparison of varietal wines (e.g. Sauvignon blanc). We focus on the case of two closed Loire Valley PDO (France): Quincy and Reuilly. Three distinct tastings were organized. Firstly, at the local level comparing the 2 PDO (11 and 9 wines, 17 professional assessors); secondly at a regional level adding 3 closed PDO: Menetou-Salon, Sancerre and Pouilly-Fumé (3 wines per PDO, 16 assessors) and thirdly at an international level comparing these 5 PDO with Sauvignon Blanc wines coming from South Africa, New Zealand and Chile (1 to 3 wines per PDO, 19 assessors). All the wines were from the 2019 vintage and were considered to have a traditional elaboration process without contact with oak. A sensory descriptive analysis was performed using an aroma wheel allowing to combine a Check-All-That-Apply methodology, often used in sensory benchmarking, with a hierarchical structuration of the attributes. The aim is to facilitate data acquisition in a professional context without common training, to consider the hierarchical relationships among the attributes during the data analysis and to be able to characterize wines with a large range of sensorial variability. We use univariate, multivariate and clustering analyses. Similarities and differences between Quincy and Reuilly PDO wines and other Sauvignon blanc wines were identified. Specific attributes can distinguish the two PDO and different proximities exist with other local PDO, while clear differences were observed compared to international wines. Our study contributes to propose and discuss a method to do a wine sensory benchmarking highlighting sensory specificities linked to origin.