Characterization and kinetic modeling of Levilactobacillus brevis malolactic fermentation under oenological conditions and different ethanol concentrations
School authors:
author photo
Pedro Saa
author photo
Wendy Verónica Franco
External authors:
  • Carla Vargas-Luna ( Pontificia Universidad Catolica de Chile )
  • I. Tapia ( Pontificia Universidad Catolica de Chile )
  • Liliana Godoy ( Pontificia Universidad Catolica de Chile )
Abstract:

Malolactic fermentation (MLF) remains an unpredictable process in winemaking, often leading to sluggish or stuck fermentations. While bacterial starter cultures have been proposed to improve its control, their kinetic behavior under oenological conditions remains poorly studied. To address this limitation, we characterized and modelled the growth dynamics of a lactic acid bacteria, Levilactobacillus brevis (L. brevis) BCV-46, in a synthetic wine under three ethanol concentration levels (10 %, 11.5 %, and 13.5 %). Fermentations were conducted in a synthetic Chardonnay must first inoculated with one of two commercial Saccharomyces cerevisiae strains. Once the alcoholic fermentation was completed, L. brevis was inoculated into the wine musts, ethanol concentration was adjusted to the desired level, and the MLF kinetics were monitored. Increased ethanol concentrations decreased microbial growth and L-malate to L-lactate conversion by L. brevis but promoted an increase in acetic acid production. To further understand the ethanol impact on the MLF, different kinetic models were evaluated, and a robust structure was identified that accurately described the experimental data. Kinetic parameters like the maximum specific growth rate were negatively affected by higher ethanol concentrations, whereas yield coefficients increased. Notably, the model revealed an important effect of the medium composition after the alcoholic fermentation on the conversion rate of L-malate to L-lactate. Overall, this work provides new insights into the ethanol tolerance of L. brevis BCV-46 under oenological conditions, contributing to a better understanding of the MLF.

UT WOS:001829222000001
Number of Citations 0
Type
Pages
ISSUE
Volume 83
Month of Publication SEP
Year of Publication 2026
DOI https://doi.org/10.1016/j.fbio.2026.109522
ISSN
ISBN