When organic chemistry contributes to the understanding of metabolism mechanisms

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.

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The advance in maturation of wine grapes is an important climate change risk related effect that could affect warm regions like Portuguese Douro Wine Region. Indeed, the climate analysis over the past years registered a decrease in the precipitation, significant higher average temperatures, and a more frequent occurrence of extreme weather events, including heat waves. In these conditions the length from anthesis until maturation is shortened and the uncoupling of technical and phenolic maturity results in berries with higher sugar concentration (and lower acidity), but lower anthocyanins, tannins, and total phenolic concentration, which produce unbalanced wines.
In this work, an innovative strategy of crop forcing, based on forcing vine regrowth after a second pruning of green shoots, was tested, aimed at delaying ripening until the temperature becomes lower and, therefore, preventing acidity loss and increasing anthocyanin-to-sugar ratio. The experiments were conducted in 2019 and 2020 in a commercial vineyard of ‘Touriga Nacional’ located in the Douro Region. Crop forcing was conducted 15 (CF1) to 30 (CF2) days after fruit set. Vines pruned with conventional methods were used as control (CF0). Results confirmed that fruit ripening was shifted from the hot season (August/September), until a cooler period (October through early-November). At harvest, grapevine berries from CF1 and CF2 presented lower pH and higher acidity, than control, with no significant differences in colour intensity and phenolic levels composition. Sugar content was lower in CF2-treated vines in both seasons. However, in CF-treated vines the number and size of clusters were significantly lower (up to 88% reduction) than in control plants. A metabolomics analysis of mature berries from CF-treated vines and control is underway. Crop forcing was indeed effective in producing a more balance berry composition but severely reduced grapevine yield,

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.