Impact of canopy management on thiol precursors in white grapes: a six-year field study

I performed my PhD in grapevine physiology under the supervision of Dr. H. Medrano, standing in the vineyards from pre-dawn to sunrise during many hot, wet and sunny days with my colleagues J.M.E. and J.B. I also spent many days and nights facing ticks year-round working in Mediterranean macchias with J.Gu. and M.M. Later I was able to supervise PhD students on grapevines – like A.P. and M.T. – and on Mediterranean vegetation – like J.Gal. With the incorporation to the group of M.R.-C. ‘the puzzle’ was completed and, combining the aforementioned studies, we could conclude (more than 20 years ago) things like: (1) stomatal conductance is the best proxy for ‘water stress’ in studies on photosynthesis; (2) steady-state chlorophyll fluorescence retrieves photosynthesis under saturating light; (3) photoinhibition is not a major photosynthetic limitation under water stress; (4) mesophyll conductance instead is; and (5) mesophyll conductance is a major driver of leaf water use efficiency.

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.

It is often said that wine is a complex matrix and the chemical analysis of wine with the thousands of compounds detected and often measured is proof. New technologies can assist not only in separating and identifying wine compounds, but also in providing information about the sample as a whole. Information-rich techniques can offer a fingerprint of a sample (untargeted analysis), a comprehensive view of its chemical composition. Applying statistical analysis directly to the raw data can significantly reduce the number of compounds to be identified to the ones relevant to a particular scientific question. More data can equal more information, but also more noise for the subsequent statistical handling.

Labor shortage is one of the most crucial issues in current viticulture. Mechanized approaches are helpful in reducing production costs and increasing vineyard efficiency but their effect on grapes and wines needs evaluation. This work assess the results of combined mechanical pruning and shoot thinning with deficit irrigation strategies to reduce management costs but not quality of production.