Assessing macro-elements contents in vine leaves and grape berries of Vitis vinifera using near-infrared spectroscopy coupled with chemometrics

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.

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.

One of the major issues for the wine sector is the impact of climate change linked to the increasing temperatures which affects physicochemical parameters of the grape varieties planted in Bordeaux vineyard and consequently, the quality of wine. In some varietals, the attenuation of their fresh fruity character is accompanied by the accentuation of dried-fruit notes [1]. As a new adaptive strategy on climate change, some winegrowers have initiated changes in the Bordeaux blend of vine varieties [2]. This study intends to explore the fruitiness in wines produced from grape varieties adapted to the future climate of Bordeaux. 10 commercial single–varietal wines from 2018 vintage made from the main grape varieties in the Bordeaux region (Cabernet franc, Cabernet-Sauvignon and Merlot) as well as from indigenous grape varieties from the Mediterranean basin, such as Cyprus (Yiannoudin), France (Syrah), Greece (Agiorgitiko and Xinomavro), Portugal (Touriga Nacional) and Spain (Garnacha and Tempranillo), were selected among 19 samples using sensory descriptive analyses. Both sensory and instrumental analyses were coupled, to investigate their fruity aroma expression. For sensory analysis, samples were prepared from wine, using a semi preparative HPLC method which preserves wine aroma and isolates fruity characteristics in 25 specific fractions [3,4]. Fractions of interest with intense fruity aromas were sensorially selected for each wine by a trained panel and mixed with ethanol and microfiltered water to obtain fruity aromatic reconstitutions (FAR) [5]. A free sorting task was applied to categorize FAR according to their similarities or dissimilarities, and different clusters were highlighted. Instrumental analysis of the different FAR and wines demonstrated variations in their molecular composition. Results obtained from sensory and gas chromatography analysis enrich the knowledge of the fruity expression of red wines from “new” grape varieties opening up new perspectives in wine technology, including blending, thus providing new tools for producers.

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.

The use of rootstocks tolerant to soil water deficit is an interesting strategy to cope with limited water availability. Currently, several nurseries are breeding new genotypes, but the physiological basis of its responses under water stress are largely unknown. To this end, an ecophysiological assessment of the conventional 110-Richter (110R) and SO4, and the new M1 and M4 rootstocks was carried out in potted ungrafted plants. During one season, these Vitis genotypes were grown under greenhouse conditions and subjected to two water regimes, well-watered and water deficit. Water potentials of plants under water deficit down to < -1.4 MPa, and net photosynthesis (AN) <5 μmol m-2 s-1 did not cause leaf oxidative stress damage compared to well-watered conditions in any of the genotypes. The antioxidant capacity was sufficient to neutralize the mild oxidative stress suffered. Under both treatments, gravimetric differences in daily water use were observed among genotypes, leading to differences in the biomass of root, shoot and leaf. Under well-watered conditions, SO4 and 110R were the most vigorous and M1 and M4 the least. However, under water stress, SO4 exhibited the greatest reduction in biomass while M4 showed the lowest. Remarkably, under these conditions, SO4 reached the least negative stem water potential (Ψstem), while M1 reduced stomatal conductance (gs) and AN the most. In addition, SO4 and M1 genotypes also showed the highest and lowest hydraulic conductance values, respectively. Our results suggest that there are differences in water use regulation among genotypes, not only attributed to differences in stomatal regulation or intrinsic water use efficiency at the leaf level. Therefore, because no differences in canopy-to-root ratio were achieved, it is hypothesized that xylem vessel anatomical differences may be driving the reported differences among rootstocks performance. Results demonstrate that each Vitis rootstock differs in its ecophysiological responses under water stress.