Fertilization with Seaweed (Laminaria japonica) on the characteristics of the bunch and the quality of the grape must of ‘Cabernet Sauvignon’

Climate change is profoundly affecting wine production globally. Increasing temperatures induce advanced phenology, shifting the ripening period to a warmer part of the summer.

In many traditional wine-growing regions of Europe, most of the vineyards remain rainfed.

Upgrading wine industry solid wastes is considered as one of the main strategies to support the circular economy. Red grape pomaces constitute a rich source of polyphenols, which have been shown to possess antioxidant properties and to provide benefits for human and animal health. The objective of this work was to obtain and characterise polyphenolic extracts from red grape pomaces via green supercritical CO₂ extraction using ethanol as a co-solvent, and to evaluate their antibacterial activity against susceptible and multidrug-resistant Escherichia coli strains of animal intestinal origin.

Disease resistant grapevine varieties (PIWI) are increasingly important for sustainable wine production, yet the impact of different yeasts on their wine profiles remains poorly studied. In this study, nine white interspecies varieties (i.e., caladris blanc, fleurtai, hibernal, johanniter, muscaris, sauvignon kretos, soreli, souvignier gris, and voltis) grown at the faculty of agriculture, university of Zagreb (Croatia) were vinified with three different saccharomyces cerevisiae yeasts (control strain, zymaflore x5, and zymaflore xarom).

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.