Monferace a new “old style” for Grignolino wine, an autochthonous Italian variety: unity in diversity

Measurement of carbon isotope discrimination in berry juice sugars at maturity (δ13C) provides an integrated assessment of water use efficiency (WUE) during the period of berry ripening, and when collected over multiple seasons can be used as an indication of drought stress response. Berry juice δ13C measurements were carried out on 48 different varieties planted in a common garden experiment in Bordeaux, France from 2014 through 2021 and were paired with midday and predawn leaf water potential measurements on the same vines in a subset of six varieties. The aim was to discriminate a large panel of varieties based on their stomatal behaviour and potentially identify hydraulic traits characterizing drought tolerance by comparing δ13C and hydroscapes (the visualisation of plant stomatal behaviour as a response to predawn water potential). Cluster analysis found that δ13C values are likely affected by the differing phenology of each variety, resulting in berry ripening of different varieties taking place under different stress conditions within the same year. We accounted for these phenological differences and found that cluster analysis based on specific δ13C metrics created a classification of varieties that corresponds well to our current empirical understanding of their relative drought tolerances. In addition, we analysed the water potential regulation of the subset of six varieties (using the hydroscape approach) and found that it was well correlated with some δ13C metrics. Surprisingly, a variety’s water potential regulation (specifically its minimum critical leaf water potential under water deficit) was strongly correlated to δ13C values under well-watered conditions, suggesting that base WUE may have a stronger impact on drought tolerance than WUE under water deficit. These results give strong insights on the innate WUE of a very large panel of varieties and suggest that studies of drought tolerance should include traits expressed under non-limiting conditions.

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.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Anthocyanin potential of grape berries is an important quality factor in wine production. Anthocyanin concentration and profile differ among varieties but it also depends on the environmental conditions, which are expected to be greatly modified by climate change in the future. These modifications may significantly modify the biochemical composition of berries at harvest, and thus wine typicity. Among the diverse approaches proposed to reduce the potential negative effects that climate change may have on grape quality, genetic diversity among clones can represent a source of potential candidates to select better adapted plant material for future climatic conditions. The effects of individual and combined factors associated to climate change (increase of temperature, rise of air CO2 concentration and water deficit) on the anthocyanin profile of different clones of Tempranillo that differ in the length of their reproductive cycle were studied. The aim was to highlight those clones more adapted to maintain specific Tempranillo typicity in the future. Fruit-bearing cuttings were grown in controlled conditions under two temperatures (ambient temperature versus ambient temperature + 4ºC), two CO2 levels (400 ppm versus 700 ppm) and two water regimes (well-watered versus water deficit), both in combination or independently, in order to simulate future climate change scenarios. Elevated temperature increased anthocyanin acylation, whereas elevated CO2 and water deficit favoured the accumulation of malvidin derivatives, as well as the acylation and tri-hydroxylation level of anthocyanins. Although the changes in anthocyanin profile observed followed a common pattern among clones, such impact of environmental conditions was especially noticeable in one of the most widely distributed Tempranillo clones, the accession RJ43.

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.