Vineyard management strategies adopted to mitigate the impacts of climate change affect the evolution of phenolics and color during bottle aging of Aglianico wines

he use of high-power ultrasound (US) is proving of great interest to the oenological industry due to its effects in the improvement of wine organoleptic characteristics, especially in terms of color [1, 2].

Water and nutrient availability significantly impact crop yield, thus the application of sustainable strategies towards efficient water use and nutrient absorption by plants is needed.

Differences in wine flavour proceed primarily from grape quality. Environmental factors determined by the climate, soil and training systems modify many grape and wine quality traits. Metabolic profiling based on proton nuclear magnetic resonance (1H-NMR) spectra has been proved to be useful to study multifactorial effects of the vine environment on intricate grape quality traits. The capacity of this method to discriminate the environmental effects on wine has to be demonstrated.

The conventional wisdom of vintners is that alkalinity, and thus less sour and more rounded taste, are enhanced in wine and grapes challenged by low-nutrient soils.

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.