Proceedings of OENO IVAS 2019

Polyphenolic compounds are considered to have a major impact on the quality of red wines. Sensory impact, such as astringency and bitterness, stems directly from tannin composition. Thenceforth, quick analytical measurement of phenolic compounds appears to be a real challenge for winemaking monitoring and process control. Many methods were developed to analyzed polyphenols in wine, but they are time-consuming and require chemistry skills and equipment, not suitable for a rapid routine analysis. A reliable and rapid method to obtain this kind of measurement is Fourier Transform Infrared (FTIR) spectroscopy.

Although some wine production processes still rely on post-production evaluation and off-site laboratory analysis, the new winemaking industry is aware of a need for a better knowledge of the process to improve the properties of the final product. Thus, more and more wineries are interested in incorporating quality-by-design (QbD) strategies instead of postproduction testing because of the possibility to early detect deviations in fermentation or any other wine process. This would allow to detect unwanted situations and eventually to ‘readjust’ the process, thus minimizing rejects.

Gum arabic is composed of a polysaccharide rich in galactose and arabinose along with a small protein fraction [1, 2], which gives its stabilizing power with respect to the coloring substances or tartaric precipitation of bottled wine. It is a gummy exudation from Acacia trees; the products used in enology have two possible botanical origins, i.e. Acacia seyal and Acacia senegal, with different chemical-physical features and consequently different technological effects on wines. The aim of this work is to evaluate the feasibility of discrimination of commercial gums Arabic between their two different sources, on the basis of the absorption of the Fourier Transform Infrared (FT-IR) spectra of their aqueous solutions, in order to propose an extremely rapid and cost-saving method for quality control laboratories.

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.