The adaptation and resilience of scions and rootstocks to water constraint

Cannonau variety is historically grown in a large Sardinia area (Jerzu district) and the vineyards are planted both in the plane and in the sloped hills reaching also 650 m of altitude a.s.l. Thus, in order to discover how climate, soil diversity and growing traditions could account for differences in grape and wine quality, this trial was carried out.

El archipiélago Canario, conocido en el pasado como las Islas del Vino, fue una gran potencia en la elaboración y comercialización del vino, sobre todo de caldos elaborados con la variedad Malvasía.

Row orientation is a critical long-term viticulture practice, which may have a determining effect on grape and wine quality as well as cost efficiency on a specific terroir selected for cultivation.

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.

Winter pruning is today the longest operation for hand workers in the vineyard. Over the last years, mechanical pruning practices have become popular in southern France vineyards to respond to competitiveness issue especially for the basic and mid-range wine production. Wine farmers have developed different vineyard management techniques associated with mechanical winter pruning. They sought to be precise or not to control the buds number per vine.