Modeling of yeast thermal resistance and optimization of the pasteurization treatment applied to soft drinks.

Int J Food Microbiol

Centro Interdipartimentale di Ricerca Industriale Agroalimentare, Università degli Studi di Bologna, Sede di Cesena, Via Quinto Bucci 336, 47521 Cesena, FC, Italy; Dipartimento di Scienze e Tecnologie Agro-alimentari, Università degli Studi di Bologna, Sede di Cesena, Piazza Goidanich 60, 47521 Cesena, FC, Italy.

Published: July 2019

AI Article Synopsis

  • Yeast spoilage in soft drinks and fruit beverages is linked to low pH and high carbon/nitrogen ratios, and while thermal treatments help maintain microbial stability, excessive heat can compromise food quality.
  • A study investigated the thermal resistance of various yeast strains, finding significant variability in their resistance, particularly highlighting one S. cerevisiae strain for further testing in orange juice-based drinks.
  • The findings suggest that traditional pasteurization methods should be updated, as they don't account for new scientific insights, which could lead to optimized thermal processes that ensure microbial stability while minimizing thermal damage and energy use.

Article Abstract

Yeast are usually responsible for spoilage of soft drinks and fruit beverages, because of the particular characteristics of these products (low pH, high C/N ratio). The microbial stability is guaranteed by thermal treatments. However, excessive heat treatments can affect food sensorial quality. In this work the thermal resistance of different yeasts strains (seven belonging to the species Saccharomyces cerevisiae and six belonging to the species Kluyveromyces marxianus, Zygosaccharomyces bisporus, Z. mellis, Z. rouxii, Schizosaccharomyces pombe and Saccharomycodes ludwigii) was assessed in a model system. The results showed non-linear death curves and a high variability also within the same species. The most resistant strain, belonging to the species S. cerevisiae, was chosen for further experiments in orange juice based industrial beverages: first, death curves were performed; then, the probability of beverage spoilage in relation to process parameters (initial inoculum, temperature, treatment time) was evaluated using a logistic regression model. Finally, a cross-validation was performed to investigate the predictive capability of the fitted model. Pasteurization in the soft drink industry is commonly applied according to parameters defined several decades ago, which does not consider the successive findings concerning microbial physiology and stress response, the process improvement and the more recent tools provided by predictive microbiology. In this perspective, this study can fill a gap in the literature on this subject, going to be a basis for optimizing thermal processes. In fact, the data obtained indicated an interesting possibility for food industry to better modulated (and even reduce) thermal treatments, with the aim to guarantee microbial stability while reducing thermal damage and energy costs.

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Source
http://dx.doi.org/10.1016/j.ijfoodmicro.2019.04.006DOI Listing

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