Impact of grape maturity on esters content and sensory characters in wines fermented with yeast strains of different genetic backgrounds

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.

Monitoring vine water status is a major challenge for vineyard management because it influences both yield and harvest quality. It is also a challenge at the territorial scale for identifying periods of high water restriction or zones regularly impacted by water stress. This information is of major importance for defining collective strategies, anticipating harvest logistic or applying for irrigation authorisation. At this spatial scale, existing tools and methods for monitoring vine water status are few and often require strong assumptions (e.g. water balance model). This paper proposes to consider a collaborative collection of observations by winegrowers and wine industry stakeholders (crowdsourcing) as an interesting alternative. Indeed, it allows the collection of a large number of field observations while pooling the collection effort. However, the feasibility of such a project and its interest in monitoring vine water status at regional scale has never been tested.

The objective of this article is to explore the possibility of making a regional map of vine water status based on crowdsourcing observations. It is based on the study of the free mobile application ApeX-Vigne, which allows the collection of observations about vine shoot growth. This information is easy to collect and can be considered, under certain conditions, as a proxy for vine water status. This article presents the first results obtained from the nearly 18,000 observations collected by winegrowers and wine industry stakeholders during 2019, 2020 and 2021 seasons. It presents the vine shoot growth maps obtained at regional scale and their evolution over the three vintages studied. It also proposes an analysis of the factors that favoured the number of observations collected and those that favoured their quality. These results open up new perspectives for monitoring vine water status at a regional scale but above they provide references for other crowdsourcing projects in viticulture.

Increasing temperatures worldwide are expected to cause a change in spatial distribution of plant species along elevational gradients and there are already observable shifts to higher elevations as a consequence of climate change for many species. Not only naturally growing plants, but also agricultural cultivations are subject to the effects of climate change, as the type of cultivation and the economic viability depends largely on the prevailing climatic conditions. A shift to higher elevations therefore represents a viable adaptation strategy to climate change, as higher elevations are characterized by lower temperatures. This is especially important in the case of viticulture because a certain wine-style can only be achieved under very specific climatic conditions. Although there are several studies investigating climatic suitability within winegrowing regions or longitudinal shifts of winegrowing areas, little is known about how fast vineyards move to higher elevations, which may represent a viable strategy for winegrowers to maintain growing conditions and thus wine-style, despite the effects of climate change. We therefore investigated the change in the spatial distribution of vineyards along an elevational gradient over the past 20 years in the mountainous wine-growing region of Alto Adige (Italy). A dataset containing information about location and planting year of more than 26000 vineyard parcels and 30 varieties was used to perform this analysis. Preliminary results suggest that there has been a shift to higher elevations for vineyards in general (from formerly 700m to currently 850 m a.s.l., with extreme sites reaching 1200 m a.s.l.), but also that this development has not been uniform across different varieties and products (i.e. vitis vinifera vs hybrid varieties and still vssparkling wines). This is important for climate change adaptation as well as for rural development. Mountain areas, especially at mid to high elevations, are often characterized by severe land abandonment which can be avoided to some degree if economically viable and sustainable land management strategies are available.

Atmospheric carbon dioxide (CO2) concentration has continuously increased since pre-industrial times from 280 ppm in 1750, and is predicted to exceed 700 ppm by the end of 21st century. For most of C3 plant species elevated CO2 (eCO2) improve photosynthetic apparatus results in an increased plant biomass production. To investigate the effects of eCO2 on morphological leaf characteristics the two Vitis vinifera L. cultivars, Riesling and Cabernet Sauvignon, grown in the Geisenheim VineyardFACE (Free Air Carbon dioxide Enrichment) system were used. The FACE site is located at Geisenheim University (49° 59′ N, 7° 57′ E, 94 m above sea level), Germany and was implemented in 2014 comparing future atmospheric CO2-concentrations (eCO2, predicted for the mid-21st century) with current ambient CO2-conditions (aCO2). Experiments were conducted under rain-fed conditions for two consecutive years (2015 and 2016). Six leaves per repetition of the CO2 treatment were sampled in the field and immediately fixed in a FAA solution (ethanol, H2O, formaldehyde and glacial acetic acid). After 24 h leaf samples were transferred and stored in an ethanol solution. Subsequently, leaf tissue was dehydrated using ethanol series and embedded in paraffin. By using a rotary microtomesections of 5 µm were prepared and fixed on microscopic slides. Subsequent the samples were stained using consecutive staining and washing solutions. Afterwards pictures of the leaf cross-sections were taken using a light microscope and consecutive measurements were conducted with an open source image software. Differences found in leaf cross-sections of the two CO2 treatments were detected for the palisade parenchyma. Leaf thickness, upper and lower epidermis and spongy parenchyma remained less affected under eCO2 conditions. The observed results within grapevine leaf tissues can provide first insights to seasonal adaptation strategies of grapevines under future elevated CO2 concentrations.

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.