Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Vitis vinifera ‘Nebbiolo’ cultivar is a 3’-subsituted anthocyanin prevalent wine variety. It is grown in North-West Italy for the production of high quality ageing wines. In the present work berry skin anthocyanin amounts and profiles of the clones CVT 308, CVT 423 and CVT 142 were studied in 2004 and in 2005 in four environmentally different locations of North-West Italy: Donnas (steep mountain area), Monforte (hilly area, with a pH of 8.1), Vezza (hilly area, with a pH of 8.2) and Lessona (plain area, with a pH of 4.8).

The Intergovernmental Panel on Climate Change (IPCC) forecasts an increase in global temperature and a decrease in relative humidity (RH) in the coming decades, which may have implications for berry ripening and composition.

The present study evaluates the effect of prefermentative maceration enzymes and yeast autolysate on the concentration of conjugated precursors and volatile thiols, respectively.Sauvignon blanc and Merlot grapes underwent skin-contact maceration with or without pectolytic enzymes, for the production of white and rosé wines

Water availability is the most limiting factor for vineyard productivity under Mediterranean conditions. Due to the effects caused by the current climate change, wine-growing regions may face serious soil moisture conservation problems, due to the lower water retention capacity of the soil and higher soil irradiation. The aim of this work was to evaluate the effects of soil recharge irrigation in pre-sprouting and summer irrigation every week (30 % ETo) from the pea size state until the end of ripening (RP) compared to exclusively summer irrigation every week (R) in the same way that RP, on berry phenolic composition at harvest.

Grape harvest time is one of the most fundamental aspects that affect grape quality and thus wine quality. Many factors influence the decision of harvest; among them technological and phenolic maturity of grape. Technological ripeness is mainly related to sugar concentration, titratable acidity and pH. Conventional methods for chemical analysis of grapes are normally sample-destructive, time-consuming, include laborious sample preparation steps, and generate chemical waste, thereby limiting their utility in online/in-line quality monitoring. Moreover, destructive analyses can be performed only on a limited number of fruit pieces and, thus, their statistical relevance could be limited. This study evaluated the ability of a lab-scale hyperspectral imaging (HYP-IM) technique to predict titratable acidity, organic acid and sugar content of grapes. Samples of Cabernet franc and Chenin blanc grapes were consecutively collected six times at weekly intervals after veraison. The images were recorded thanks to the hyperspectral imaging camera Pica L (Resonon) in a spectral range from 400 to 1000 nm. Statistics were performed using Microsoft Xlstat software. Successively, the berries were analyzed for their sugar (glucose and fructose) and organic acid (malic and tartaric acid) content and titratable acidity according to usual methods.