Macrowine 2021
IVES 9 IVES Conference Series 9 Effect of mixed Torulaspora delbrueckii-Saccharomyces cerevisiae culture on rose quality wine

Effect of mixed Torulaspora delbrueckii-Saccharomyces cerevisiae culture on rose quality wine

Abstract

Alcoholic fermentation using no Saccharomyces wine is an effective means of modulating wine aroma. This study investigated the impact of coinoculating Torulaspora delbruecki with two Saccharomyces cerevisiae commercial yeast (QA23, Lallemand; Red Fruit, Sepsa-Enartis) on enological quality parameters, volatile composition and sensory analysis. The following assays were performed on Tempranillo variety: Saccharomyces QA23 (CTQA), Saccharomyces Red Fruit (CTRF), coinoculated T. delbrueckii + S.cerevisiae QA23 (CIQA) and coinoculated T. delbrueckii + S.cerevisiae (CIRF). The results showed that chemical and sensory profiles of coinoculated wines were different from Saccharomyces-strain wines. Coinoculated wines (CIQA and CIRF) showed lower alcohol content, total acidity and malic acid meanwhile higher isobutanol and isoamylic alcohols with respect to their respective controls (CTQA and CTRF). Ester composition was significantly affected by the fermentation strategy. Coinoculated wines (CIQA and CIRF) were characterized by higher contents of ethyl esters of branched acids, (EEBAs), ethyl cinnamates (CINNs) and ethyl propionate. Meanwhile CT wines (CTQA and CTRF) shown higher significant quantities of higher acohol acetates (HAAs) and ethyl esters of straight chain fatty acids (EEs). In control wines, RF yeast produced higher quantities of (HAAs) in comparison with QA, where isoamyl acetate was the main contributor to differences. Color differences between coinoculated wines and their respective controls were human eye-perceptible (ΔE*ab ≥ 3 CIELab units). Sensory analysis aroma showed no significant differences. In the mouth coinoculated wines resulted less heat, according with alcohol content; meanwhile control wines had higher aroma intensity. The highest global score was got for CTRF wines.

Publication date: May 17, 2024

Issue: Macrowine 2016

Type: Poster

Authors

Belen Puertas*, Emma Cantos, Ignacio Soto, Jose Manuel Muñoz-Redondo, María Ruiz-Moreno

*IFAPA

Contact the author

Tags

IVES Conference Series | Macrowine | Macrowine 2016

Citation

Related articles…

Anti/prooxidant activity of wine polyphenols in reactions of adrenaline auto-oxidation

Adrenaline (epinephrine) belongs to catecholamine class. It is a neurotransmitter and both a hormone which is released by the sympathetic nervous system and adrenal medulla in response to a range of stresses in order to regulate blood pressure, cardiac stimulation, relaxation of smooth muscles and other physiological processes. Adrenaline exhibits an effective antioxidant capacity (1). However, adrenalin is capable to auto-oxidation and in this case it generates toxic reactive oxygen intermediates and adrenochrome. Under in vitro conditions, auto-oxidation of adrenaline occurs in an alkaline medium (2).

Testing the effectiveness of Cell-Wall material from grape pomace as fining agent for red wines

Lately several works highlighted the capacity of grape cell-wall material (CWM) to interact with proanthocyanidins (PA), indicating its potential use as fining agent for red wines.1–4 However, those studies were performed by using purified PAs and very high doses of CWM (almost ten-fold higher than those used in wine industry for other commercial fining agents). The present study focuses on the applicability of CWM from Cabernet sauvignon pomace as fining agent for red wines under real winery conditions. Grapes of cultivar Cabernet sauvignon were harvested at three different maturity levels
(unripe, mature, and overripe) and used for red winemaking. The pomace of such vinifications were used as source of CWM, and applied into red wines at two different concentrations: 0.2 g/L and 2.5 g/L.

Identification of green, aggressive and hard character of wines by a chemo-sensory directed methodology

With climate change, it is progressively more often to obtain grapes with an acceptable content in sugars or acids but with immature tannins described as green, aggressive or hard (noted as GAH onwards). During winemaking, the oenologist has to make decisions related to the elaboration of such grapes based mainly on empirical experience, given the lack of objective criteria to this concern. An increase in the chemical and sensory knowledge of immature tannins would allow managing this GAH character of grapes with the maximum possible efficiency during winemaking processes. The present work aims at isolating and identifying the group of compounds responsible for the GAH character present in wines.

Sensory definition of green aroma concept in red French wines. Evidence for the contribution of novel volatile markers

The aromatic complexity of a wine results from the perception of the association of volatile molecules and each aroma can be categorized into different families. The “green” aromas family in red wines has retained our attention by its close link with the fruity perception. In that study, the “green” olfactory concept of red wines was considered through a strategy combining both sensory analysis and hyphenated chromatographic techniques including HPLC and MDGC (Multidimensional Gas Chromatography). The aromatic space of this concept was specified by lexical generation through a free association task on 22 selected wines by a panel of wine experts. Then, 70 French red wines were scored on the basis of the intensity of their “green” and “fruity” attributes.

New molecular evidence of wine yeast-bacteria interaction unraveled by untargeted metabolomic profiling

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.