Investigating water stress-related seasonal and spatial patterns and the possible links with juice and wine compositional parameters

For sustainable viticulture, the substitution of chemical inputs with biocontrol products has become one of the most considered strategies. This strategy is based on elicitor-triggered immunity that requires a deep understanding of the molecular mechanisms involved in plant defense activation. Plant immune responses are triggered through the perception of conserved microbe-associated molecular patterns (MAMPs) which are recognized by pattern recognition receptors (PRRs) at the plasma membrane.

Hydroxytyrosol (HT) is a phenolic compound present in olives, virgin olive oil and wine. HT has attracted great scientific interest due to its biological activities which have been related with the ortho-dihydroxy conformation in the aromatic ring. In white and red wines, HT has been detected at concentrations ranging from 0.28 to 9.6 mg/L and its occurrence has been closely related with yeast metabolism of aromatic amino acids by Ehrlich pathway during alcoholic fermentation. One of the most promising properties of this compound is the neuroprotective activity against pathological mechanisms related with neurode-generative disorders including Alzheimer’s and Parkinson’s disease.

The foundation of wine production lies in the use of high-quality grapes. To produce wines that meet the highest standards, a fast and reliable analytical assessment of grape quality is essential. Many wineries currently employ Fourier-Transform Middle-Infrared Spectroscopy (FTIR) for this purpose.

Oxygen is playing a major role in wine ageing and conservation. Many chemical oxidation reactions occur but they are difficult to follow due to their slow reaction times

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.