A combination of biotechnology tools and coopers elements for an alternative the addition of SO2 at the end of the malolactic fermentation in red wines or at the “mutage” for the “liquoreux” wines

Del Barrio-Galán, R.a, b, Gómez-Parrini, A.a, Peña-Neira, A.b a Lallemand Inc. Chile y Compañía Limitada, Rosario Norte 407, piso 6, Las condes, Santiago, 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 It is well known that polysaccharides, mainly mannoproteins, play an important role on physical, chemical and sensory quality of wines. The ageing of white wines on lees is used in order to release higher amounts of polysaccharides by the autolytic processes in order to obtain higher-quality wines. However, this technique is too slow, because the temperature and pH conditions are not the most suitable for this process. In addition, it can also involve certain disadvantages such as a greater demand on winery resources, a longer period of wine storage, the appearance of reduction notes and some microbiological alterations.

The above-ground parts of plants, which constitute the phyllosphere, have long been considered devoid of bacteria and fungi, at least in their internal tissues and microbial presence there was long considered a sign of disease. However, recent studies have shown that plants harbour complex bacterial communities, the so-called “microbiome”[1]. We are only beginning to unravel the origin of these bacterial plant inhabitants, their community structure and their roles, which in analogy to the gut microbiome, are likely to be of essential nature. Among their multifaceted metabolic possibilities, bacteria have been recently demonstrated to emit a wide range of volatile organic compounds (VOCs), which can greatly impact the growth and development of both the plant and its disease-causing agents.

Wine is a solution containing abundant volatile compounds which contribute to their aroma. Many of them are produced by yeast as metabolism by-products. Different yeast strains produce different volatile profiles. The possibility of studying the evolution of volatile compounds during fermentation, using sampling methods that not alter the volume of fermentation media, is of great interest. In spite of this, non-invasive methods to monitoring the evolution of volatile profile during fermentation have been seldom used. The goals of this work were to use by first time the headspace sorptive extraction (HSSE) as non-invasive method to monitor the evolution of volatile profiles throughout alcoholic fermentation and to study the changes on volatile profiles produced by Saccharomyces cerevisiae and Lachancea thermotolerans during fermentation of a must with high sugar content.

The objective of this study is to review the scientific evidences and to advance into the knowledge of the molecular mechanisms of astringency. Astringency has been described as the drying, roughing and puckering sensation perceived when some food and beverages are tasted (1). The main, but possibly not the only, mechanism for the astringency is the precipitation of salivary proteins (2,3). Between phenolic compounds found in red wines, flavan-3-ols are the group usually related to the development of this sensation. Other compounds, phenolic or not, like anthocyanins, polysaccharides and mannoproteins could act modifying or modulating astringency perception by hindering the interaction between flavanols and salivary proteins either because of their interaction with the flavanols or because of their interaction with the salivary proteins.

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.