Synthesis of the contribution of the Giesco (group of international experts of vitivinicultural systems for cooperation) to the study of terroirs

Grape harvest time is one of the most fundamental aspects that affect grape quality and thus wine quality. Many factors influence the decision of harvest; among them technological and phenolic maturity of grape. Technological ripeness is mainly related to sugar concentration, titratable acidity and pH. Conventional methods for chemical analysis of grapes are normally sample-destructive, time-consuming, include laborious sample preparation steps, and generate chemical waste, thereby limiting their utility in online/in-line quality monitoring. Moreover, destructive analyses can be performed only on a limited number of fruit pieces and, thus, their statistical relevance could be limited. This study evaluated the ability of a lab-scale hyperspectral imaging (HYP-IM) technique to predict titratable acidity, organic acid and sugar content of grapes. Samples of Cabernet franc and Chenin blanc grapes were consecutively collected six times at weekly intervals after veraison. The images were recorded thanks to the hyperspectral imaging camera Pica L (Resonon) in a spectral range from 400 to 1000 nm. Statistics were performed using Microsoft Xlstat software. Successively, the berries were analyzed for their sugar (glucose and fructose) and organic acid (malic and tartaric acid) content and titratable acidity according to usual methods.

This study investigates the chemical and sensory profiles of white wines produced from disease-resistant hybrid grape cultivars (DRHGCs) compared to traditional Vitis vinifera L. cultivars in South Tyrol, Italy.

Alteration of sap pH is one of the first chemical changes that occurs within the xylem vessels of plants exposed to drought. Xylem sap acidification accompanied by the accumulation of soluble sugars has been recently documented in several species (Sharp and Davis, 2009; Secchi and Zwieniecki, 2016). Here, Vitis vinifera plants of the anysohydric cultivar Barbera were exposed to either short (no irrigation; SD) or to prolonged drought (continual reduction of 10% water; PD). When comparable severe stress was reached, the potted grapes were re-watered. SD was characterized by fast (2–3 days) stomatal closure and high abscisic acid (ABA) accumulation in xylem sap (>400 μg L−1) and in leaf. In PD plants, the rise in ABA levels was considerably diminished.

The postharvest dehydration of grapes is a traditional practice to obtain wines with unique traits (e.g. sweet, dry/reinforced). The modern facilities (dehydrating rooms) used for this purpose are equipped with systems for artificially controlling the inside environment parameters, to obtain the desired dehydration kinetic and preserve the grapes from grey mold (Botrytis cinerea) infection, However, the conditioning systems are extremely energy-demanding and the identification and practical applications of solutions effective in controlling/reducing the postharvest decay would reduce the costs of the operation of the dehydration facilities. To this end, we explored the potential of ozone-based treatments on harvested grapes and preliminarily tested if the treatment could impact the normal behavior and metabolism of grapes during the traditionally slow dehydration practice.

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.