Implications of the nature of organic mulches used in vineyards on grapevine water status, yield, berry quality and biological soil health  

Croatian viticulture is mainly based on native grapevine varieties susceptible to various diseases and pests, which leads to unsustainable use of large amounts of pesticides. The sustainable development of viticulture in the future will only be possible by increasing the resistance of the grapevine through the development of new resistant varieties. Breeding programs have been launched in the leading wine-growing countries to develop resistant varieties possessing high-quality levels. Native cultivars from Croatia are not included in the breeding programs of other countries.

The wine industry is increasing the demand for indigenous yeasts adapted to the terroir to produce unique wines that reflect the distinctive characteristics of each region. In our group, we have identified and characterized 60 native yeast strains isolated from a vineyard in Maldonado-Uruguay, in which three strains stood out: Saccharomyces cerevisiae T193FS, Saturnispora diversa T191FS, and Starmerella bacillaris T193MS. Their oenological potential was evaluated at a semi-pilot scale in Tannat must vinification in the wine cellar to have a more precise and representative evaluation of the final product.

The wine spoilage caused by Brettanomyces bruxellensis is one of the global concerns for winemakers. Detecting the presence of B. bruxellensis using routine laboratory culture techniques becomes challenging when cells enter the viable but not culturable (VBNC) state. This study aims to investigate the impact of p-coumaric acid (a volatile phenol precursor) and micronutrients on B. bruxellensis’ culturability, viability, and volatile phenol production under sulfite stress. In red wine, exposure to a high sulfite dose (100.00 mg L-1 potassium metabisulfite) resulted in immediate cell death, followed by a recovery of culturability after two weeks.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.