Piloting grape ripening in a global warming scenario: feasible techniques are available

Several trunk diseases cause decline and premature dieback of grapevines. In vineyards, these pathogens gain entry into plants through unprotected wounds. Wounds are also frequently infected during the propagation stages. The pathogens survive in infected plants in a latent form and cause disease in older grapevines or in plants that are

Red grape pomace, a waste from wine production, can be valorised by extracting polyphenols, high-added value compounds used in cosmetics or oenology. For use at an industrial level, using green extraction techniques, pomace need to be stored before being processed. The aim of this study is to test various storage conditions in order to maintain high level of polyphenols over 180 days, while keeping storage cost economically interesting. In a first step, different storage conditions (ambient temperature or cooled (4°C) temperature, anaerobic (saturation with N2) or aerobic conditions, and addition of sulphur dioxide (SO2)) were compared on small samples (1 kg) packed in plastic pockets. The quality of storage was assessed by following the optical density of the pomace extract at 280 nm (DO 280 expressed as mg/l eq gallic acid), which is an indication of the amount of remaining extractable polyphenols.

Sessile oak and pedunculate oak have shown several differences of interest for enological purposes. Tannic and aromatic composition among sessile oak or pedonculate oak has been well studied. Sessile oak is generally more aromatic than pedunculated, while the later is more tannic. This scientific point of view is rarely applied to classify oak in cooperages. Most coopers use the type of grain to distinguish wide and thin grain.

Teran is an important native variety grown in Istria known for its high level of polyphenols and intensive fruity character of wines. Teran’s yield and wine typicity have recently decreased due to climate changes (increased temperature and severe drought). Four drip irrigation treatments (25%, 50%, 75%, 100% of total evapotranspiration) and control were investigated for the influence on Teran yield and quality, where focus was given to the content and composition of main polyphenolic and volatile compounds in grapes. Irrigation positively influenced yield since the berry weight also increased with increased irrigation. This resulted in the highest yield for 100% ETc. The highest concentration of polyphenols had control, while the irrigation treatments did not differ significantly. However, there was a tendency to decrease concentration with increased irrigation probably due to the increased berry size, which led to a dilution effect. Regarding the volatile compounds, the most abundant group was alcohols, followed by acids.

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.