Activation of retrotransposition in grapevine

The presence of undesirable compounds in wines, such as ota, biogenic amines and pesticides residues, affects wine quality and can cause health problems for the consumer. Additionally, an excess of tannins can produce an undesirable increase in the astringency and bitterness of the wine, so tannins are also a target for reduction. The main tool that a winemaker has to reduce their content in the wine is fining. However, some of the fining agents commonly used in the winery can cause allergies or even increase the protein content in the wine, increasing the turbidity.

The wine industry works to minimize pesticides and adapt to climate change. Breeding programs have developed disease-resistant grape varieties, particularly against downy and powdery mildew, to minimize pesticide applications [1]. However, their enological potential remains underexplored.

Extension specialists often recommend nutrient monitoring through leaf blade or petiole sampling twice a season for each vineyard block. However, due to the time and labor required to collect a large, random sample, many growers complete the task infrequently or incorrectly. Readily available remote sensing images capture the vineyard variability at both spatial and temporal scales, which can capture canopy and soil variability and be used to guide growers to representative sampling locations.

There has been a shift in modern industry to implement non-destructive and non-invasive process monitoring techniques (Helmdach et al., 2013).

Characterize taste and mouthfeel properties of grapes elicited by the phenolic fraction (PF) of grape berries and establish relationships with chemical variables. METHODS: As many as 31 diverse grape lots of Tempranillo Tinto and Garnacha Tinta from three different regions were harvested. Grapes were destemmed and macerated in 15% of ethanol for one week and extracts were submitted to solid phase extraction. The recovered polyphenolic fraction was reconstituted in wine model and characterized by a panel of 21 wine experts employing a list of 23 taste and mouthfeel-related attributes following a rate-k-attributes methodology. RESULTS: Six significant attributes among the 31 samples differed based on ANOVA results: “dry”, “coarse”, “bitter”, “dry on tongue”, “sticky” and “watery”. PCA with VARIMAX algorithm was calculated.