Using atmospheric and statistical models to understand local climate and assess spatial temperature variability at a fine scale over the Stellenbosch wine district, South Africa

Compactness is a complex trait of V. vinifera L. and is defined ultimately by the portion of free space within the bunch which is not occupied by the berries. A high degree of compactness results in poor ventilation and consequently a higher susceptibility to fungal diseases, diminishing the quality of the fruit. The easiness to conceptualize the trait and its importance arguably contrasts with the difficulty to measure and quantify it. However, recent technical advancements have allowed to study this attribute more accurately over the last decade. Our main objective was to explore the underlying genetics determining bunch compactness by applying updated phenotyping methods in a collection of V. vinifera L. cultivars with a wide genetic diversity.

It is well known that the vinification of grapes at full maturation can produce rich, full-bodied wines,
with intense and complex flavour profiles. However, the juice obtained from such grapes may have very
high sugar concentration, resulting in wines with an excessive concentration of ethanol. In addition, the decoupling between technological maturity and phenolic/aromatic one due to global warming, exacerbates this problem in some wine-growing regions. In parallel with the increase of the mean alcohol content of wines on the market, also the demand for reduced alcohol beverages has increased in recent years, mainly as a result of health and social concerns about the risks related to the consumption of alcohol.

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.

This presentation illustrates a series of successful wine businesses, which have managed to counter the downward trend impacting the global industry. How these businesses have been successful is explained through the planning and execution of strategies that focused on a clear and consistent aim in attracting new consumers. These cases add weight to the ehrenbergian position that for a business to be successful it must target new customers as a priority over alternative options like increasing value or improving customer retention.

Climate change is drastically modifying grape composition and wine quality. As consequence, must and wines are becoming unbalanced, with high sugar concentration, increased alcohol content, lower acidity, excessive astringency, color instability and also a rise in the incidence of tartaric instability is being showed.