Effect of supplementation with inactive yeast during alcoholic fermentation in base wine for sparkling

The effectiveness of enzyme-mediated maceration processes in red winemaking relies on a clear picture of the target (berry cell wall structure) to achieve the optimum combination of specific enzymes to be used. However, we lack the information on both essential factors of the reaction (i.e. specific activities in commercial enzyme preparation and the cell wall structure of berry tissue). In this study, the different combinations of pure recombinant enzymes and the recently validated high throughput cell wall profiling tools were applied to extend our knowledge on the grape berry cell wall polymeric deconstruction during the winemaking following a combinatorial enzyme treatment design.

Introduction: Malolactic fermentation (MLF) is a common process in winemaking to reduce wine acidity, maintain microbial stability and modify wine aroma. However, successful MLF is often hampered by their sluggish or stuck activity of malolactic bacteria (MLB) which may be caused by nutrient deficiency, especially when MLB are inoculated after alcoholic fermentation (Alexandre et al., 2004; Lerm et al., 2010). Identification and characterization of essential nutrients and growth factors for MLB allows for production of highly efficient nutrient supplements for MLF.

Colour is an important quality parameter in wines and is the result of a complex mixture of pigments
(including anthocyanins and their derivatives, quinones, xanthyllium compounds, etc.). Red wine colour changes over time as pigments react between themselves and with other wine macromolecules
(particularly polyphenols). During wine tasting, colour is normally assessed on the outer rim of the wine profile in a tilted glass, since most wines are too opaque to be analysed in the middle of the glass. Therefore, depending on the depth of observation considered, the perception of wine colour can be different.

Multiple Factor Analysis (MFA) According to the Chenin blanc Association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded (RRU), and Rich and Ripe Wooded (RRW), classically attributed with the help of sensory evaluation. One of the “rapid methods” has drawn our attention for the purpose of simplifying and making style attribution for large sample sets, evaluated during different sessions, more robust. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping (PM) and Polarised Sensory Positioning (PSP). It is a reference-based method in which poles
(references) are used for the evaluation of similarities and dissimilarities between samples.

The occurrence of faults and taints in wine, such as those caused by microbial spoilage or various taints, have resulted in significant financial losses to wine producers. The wine industry commits significant financial resources towards fining and taint removal processes each year. Fining involves the addition of one or more adsorptive substrates to juice or wine to bind certain components, thus reducing their concentration [1]. However, these processes are often not selective and can also remove desirable flavour and aroma compounds.