Genetic prospecting of rainfed viticulture in the region with the largest cultivated area in Chile

The agri-food industry is constantly searching for ingredients of high functional value, healthy and of natural origin. One species of particular interest is Vitis vinifera, due to its recognized antioxidant potential. Among the grape varieties, one group possesses these antioxidant compounds not only in the skin, but also in its pulp: Teinturier. The red grape has traditionally been used for color correction purposes in winemaking, however, its high antioxidant content transforms it into a raw material of high potential for new formulations of ingredients and foods for the health and wellness market.

During red wine fermentation, the extraction of phenolics compounds and sufficient oxygen provision are critical for wine quality [1,2]. In this trial, we aimed at evaluating the kinetics of phenolic extraction and dissolved oxygen during red wine fermentations using the airmixing system. Twenty lots of red grape musts were fermented in 300.000 L tanks, equipped with airmixing, using two injection regimes (i.e., high and low intensity, and high and low daily frequency). An oxygen analyzer was introduced into the tanks in order to record the concentration of dissolved oxygen over time.

Traditional drought tolerant varieties such as Cabernet Sauvignon, Monastrell, and Syrah [1], have been used as parents in the grapevine breeding program initiated by the Instituto Murciano de Investigación y Desarrollo Agrario y Medioambiental (IMIDA) in 1997 [2]. This work presents the results of evaluating three new genotypes obtained from crosses between ‘Monastrell’ and ‘Cabernet Sauvignon’ (MC16 and MC80) and between ‘Monastrell’ and ‘Syrah’ (MS104), comparing their performance under conditions of water scarcity and high temperatures with that of their respective parental varieties. For this purpose, the six genotypes were cultivated under controlled irrigation conditions (60% ETc) and rainfed conditions.

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).

Brettanomyces is a world-renowned yeast that negatively impacts the chemical composition of wines through the production of metabolites that negatively impact the sensory properties of the final product. Its resilience in wine conditions and ability to produce off-flavors make it a challenge for winemakers. Currently, the primary control technique involves adding sulfur dioxide (SO2); however, some Brettanomyces strains are developing resistance to this preservative agent. [1] Therefore, new management strategies are necessary to control this spoilage yeast.