The Fitness Advantage of Commercial Wine Yeasts in Relation to the Nitrogen Concentration, Temperature, and Ethanol Content under Microvinification Conditions
Author(s) -
Estéfani GarcíaRíos,
Alicia Gutiérrez,
Zoel Salvadó,
Francisco Noé ArroyoLópez,
José Manuel Guillamón
Publication year - 2013
Publication title -
applied and environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.552
H-Index - 324
eISSN - 1070-6291
pISSN - 0099-2240
DOI - 10.1128/aem.03405-13
Subject(s) - wine , yeast , fermentation , food science , strain (injury) , competition (biology) , population , biology , microbiology and biotechnology , winemaking , biochemical engineering , chemistry , biochemistry , engineering , ecology , demography , sociology , anatomy
The effect of the main environmental factors governing wine fermentation on the fitness of industrial yeast strains has barely received attention. In this study, we used the concept of fitness advantage to measure how increasing nitrogen concentrations (0 to 200 mg N/liter), ethanol (0 to 20%), and temperature (4 to 45°C) affects competition among four commercial wine yeast strains (PDM, ARM, RVA, and TTA). We used a mathematical approach to model the hypothetical time needed for the control strain (PDM) to out-compete the other three strains in a theoretical mixed population. The theoretical values obtained were subsequently verified by competitive mixed fermentations in both synthetic and natural musts, which showed a good fit between the theoretical and experimental data. Specifically, the data show that the increase in nitrogen concentration and temperature values improved the fitness advantage of the PDM strain, whereas the presence of ethanol significantly reduced its competitiveness. However, the RVA strain proved to be the most competitive yeast for the three enological parameters assayed. The study of the fitness of these industrial strains is of paramount interest for the wine industry, which uses them as starters of their fermentations. Here, we propose a very simple method to model the fitness advantage, which allows the prediction of the competitiveness of one strain with respect to different abiotic factors.
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