The application of soil biological indicators to support soil conservation practices and landscape quality in viticulture

During red wine ageing or conservation, color and taste change and astringency tends to reduce. These changes result from reactions of flavan-3-ols and/or anthocyanins among which condensation reactions with acetaldehyde are particularly important. The full characterization of these reactions has not been fully achieved because of difficulties in extracting and separating the newly formed compounds directly from wine. Model solutions mimicking food products constitute a simplified medium for their exploration, allowing the detection of the newly formed compounds, their isolation, and their structure elucidation.

Wine grape pomace quantitatively and qualitatively represents the most important fraction of wine waste. Namely, this by-product makes ~ 20% of the total mass of vinified grapes, and it is characterized with high concentrations of polyphenolic antioxidants, as well as grape seed oil. Hence, valorization of wine pomace, as an alternative to traditionally employed disposal, has drown considerable interest in recent years. Earlier studies were mostly focused on the extraction of phenolics, while mechanisms enhancing the extraction of lipid fraction from grape pomace, as well as their impact on the grape seed oil quality are far less investigated.

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.

Climate change (CC) is altering grape/wine composition, leading to challenges in maintaining wine sensory quality.

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.