Botrytis cinerea is a fungus that causes common infection in grapes and other fruits. In winemaking, its presence can be both considered desirable in the case of noble rot infection or undesirable when grey rot is developed. This fungus produces an extracellular enzyme known as laccase which is able to cause oxidation of phenolic compounds present in must and wine, causing most of the times a decrease in its quality and problems during the winemaking process [1]. Material and methods: Three B. cinerea strains (B0510, VA612 and RM344) were selected and grown in a liquid medium adapted from one previously described [2]. The enzyme was isolated by tangential ultrafiltration of the culture medium using a QuixStand system equipped with a 30 KDa filtration membrane.

Climate change, driven by greenhouse gas (GHG) emissions, is one of humanity’s most significant environmental challenges.

Winemaking generates significant amounts of by-products, such as grape pomace and wine lees, which are primarily used for distillation and composting.

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.

wo spectrophotometric methods are recommended by the Organisation Internationale de la vigne et du vin (OIV). The first is the method after Glories, were the absorbances at 420 nm, 520 nm and 620 nm are measured (OIV 2006a).