Application of a low-cost device VIS-NIRs-based for polyphenol monitoring during the vinification process

Sulfonated monomeric and dimeric flavan-3-ols are recently discovered in wine and proved to have great importance in understanding wine chemistry and quality [1, 2].

L’étude des relations Terroir – Vigne – Raisin est complexe. La recherche et le développement des facteurs qualitatifs qui influencent le caractère des vins sont multiples. Divers travaux mettent en évidence la relation entre l’alimentation en eau de la plante, son développement végétatif et les caractéristiques de ses raisins.

Climate change projections point to an increase of temperatures and changes in rainfall patterns in the mediterranean region.

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.

The paper proposes an algorithm for validating a modified internal standard method using ethyl alcohol contained in the test sample as a reference substance.