Impact of water stress on the phenolic composition of cv. Merlot grapes, in a typical terroir of the La Mancha region (Spain)

In the context of climate change and the need to reduce inputs, optimising photosynthesis and grapevine performance requires a better understanding of the interactions between water status, nitrogen availability, and source-sink relationships.

The study of wine evolution during barrel aging is an important aspect of wine quality. Our previous works have shown that wine metabolome monitoring by

1H-NMR approaches allows determining the impact of different winemaking processes including traitements using enzymes or finning agents [1].

Champagne regulation allows winegrowers to stock small amounts of still wines in order to compensate vintages’ quality shifts mainly due to climate variations. According to their technical requirements and house style some Champagne producers (commonly named “Champagne houses”) use these stored wines in the blend in order to introduce an element of complexity. These wines possess the particularity of being aged on fine lees in thermo-regulated stainless steel tanks. The Champagne house of Veuve Clicquot Ponsardin has several wines stored this way.

Soil and climate maps at the 1:10000 scales exist for more than 12’000 ha of Swiss vineyards. The use of these maps as consulting tools for growers remains difficult due to the complexity

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.