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Detalle de: Application of a substrate inhibition model to estimate the effect of fructose concentration on the growth of diverse Saccharomyces cerevisiae strains

Title Application of a substrate inhibition model to estimate the effect of fructose concentration on the growth of diverse Saccharomyces cerevisiae strains
Abstract

In this study, we performed an analysis of the ability of four Saccharomyces cerevisiae and one S. bayanus var. uvarum strains, isolated from different industrial processes, to ferment increasing amounts of fructose (from 0 to 70%, w/v). Overall yeast growth was estimated by integration of the area under optical density vs. time curves. Subsequently, this parameter was modeled by means of a substrate inhibition model. All strains showed a similar behavior against fructose concentration in spite of their different origins, but with slight differences. The optimum fructose concentrations to stimulate yeast growth were obtained between 4.33 and 6.05%, while the maximum concentrations above which growth was completely inhibited were attained between 59.56 and 63.85%. Statistically, model parameters calculated for wine yeast strains were significantly different than those obtained for yeasts from Agave and table olive fermentations, except for the maximum inhibitory concentration. The methodology used in this work could be useful for the industry in general as a first procedure to select yeast strains with higher fructose preferences or tolerances, and especially for winemakers, where the risk of spoilage increases by the presence of a marked residual fructose concentration in the finished wine.

Apa Reference Arroyo-López, F.N., Querol, A. & Barrio, E. (2009). Application of a substrate inhibition model to estimate the effect of fructose concentration on the growth of diverse Saccharomyces cerevisiae strains. Journal of Industrial Microbiology & Biotechnology, 36(5), 663-669. 10.1007/s10295-009-0535-x
Doi 10.1007/s10295-009-0535-x
Publication Date 11 Feb 2009
Publication Type Article
Researcher Amparo Querol
Ontology Model organisms
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