Towards a better understanding of the root system diversity and plasticityin young grafted vines using 2D imaging and 3D modelling tools

Valpolicella is a famous wine producing region in the province of Verona owing its fame above all to the production of two Protected Designation of Origins (PDOs) withered wines: Amarone and Recioto. In recent years, however, the wineries have been interested in the enhancement and qualitative increase of another PDO, Valpolicella Superiore. All the Valpolicella PDOs wines are produced with a unique grape blend, mainly Corvina, Corvinone, Rondinella and a range of other minor varieties.From 2019 Valpolicella product regulation has changed the grape proportion of the blend allowing new composition parameters of wines. For this reason, studying the volatile chemical profiles to support wine makers in the effort to produce high quality wines represents a field of great interest.

Many fleshy fruit, including the grape berry, exhibit a double‐sigmoid growth (DSG) pattern. Identification of the curious DSG habit has long been attributed to Connors’ (1919) work with peaches

The increasing demand for healthier, more transparent, and sustainable wine products has prompted the need for innovative solutions to optimize the wine health value chain.

The analysis of polyfunctional thiols in wine is challenging due to their low abundance and instability within a complex matrix. However, volatile thiols are highly aroma-active, making their accurate quantification in wine at low concentrations crucial [1].

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.