Volatile and phenolic profiles of wines closed with different stoppers and stored for 30 months

Ontario’s wine regions lie at the climatic margins of commercial viticulture owing to their cold winters and short cool growing season. The gradual warming of northern latitudes projected under a human-induced climate change scenario could bring mixed benefits to these wine regions.

Bud fruitfulness is a key determinant of the potential and the actual yield. The formation of the grapevine yield spans over a period of two consecutive growing seasons (Ferrara & Mazzeo, 2023).

The purpose of this research was to study the interaction between oenotannins and wine matrix in order to design a targeted oenotannins addition for modulating the redox status of wine. It is in fact known that oenotannins can regulate the redox potential of musts and wines since they are electroactive substances (1).

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.

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.