Study of the colour and phenolic evolution of three different tannin/anthocyanin ratios over time in a model wine

The color of a red wine is one of the most important parameters of its quality, giving much information on its status, such as the grape variety used or the winemaking style. As the result of a complex equilibrium between different forms of anthocyanins and polymerization reactions which occur over the course of time, color can also serve as an indication of a wines’ age. For this purpose the “chemical age” i and ii indexes have been introduced by Somers in 1977. The chemical age index i measures the color absorbance after the addition of acetaldehyde while chemical index ii provides an indication of how much of the total red pigments are resistant to SO2 bleaching.

Polyphenols are present in a wide variety of plants and foods such as tea, cacao and grape1. An important sub-class of these compounds is the flavanols present in grapes and wines as monomers (e.g (+)-catechin or (-)-epicatechin), or polymers also called condensed tannins or proanthocyanidins. They have important antioxidant properties2 but their biosynthesis remains partly unknown. Some recent studies have focused on the role of glycosylated intermediates that are involved in the transport of the monomers and may serve as precursors in the polymerization mechanism3, 4. The global objective of this work is to identify flavanol glycosides in grapes or wines, describe their structure and determine their abundance during grape development and in wine.

Filtration is a critical step in ensuring the clarity and microbial stability of wine prior to bottling. However the process of filtering potentially reduces red wine quality by removing some of the macromolecules that contribute to the texture of the wine. Commercial red wines, Cabernet Sauvignon (CAS) and Shiraz (SHZ), of two vintages and two grades (premium grade wines from the older vintage: CAS13 and SHZ13; and standard grade wines from a younger vintage: CAS14 and SHZ14) were filtered through industrial-scale commercial filtration units prior to bottling. Samples were taken before and after cross-flow filtration, lenticular filters, 0.65 µm and 0.45 µm pore size nylon membrane filters. The concentration and composition of macromolecules, including tannins and polysaccharides, were measured in all samples as well as particle size distribution and wine colour.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.

Úbeda-Aguilera, C a, b, Peña-Neira, A.b Del Barrio-Galán, R.b, c a Biomedical Sciences Institute, Science Faculty, Universidad Autónoma de Chile, Chile. b Department of Agro-Industry and Enology, Faculty of Agronomical Sciences, University of Chile, Post Office Box 1004, Santa Rosa 11315, La Pintana, Santiago, Chile c Lallemand Inc. Chile y Compañía Limitada, Rosario Norte 407, piso 6, Las Condes, Santiago, Chile The wine is a complex matrix made up of several compounds which can interact among themselves throughout the wine ageing process, thereby modifying their sensorial characteristics. It is well known that during ageing of wines on lees, polysaccharides (mainly mannoproteins) can be released and can interact with the aromatic fraction modifying its volatility.