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

• Published in: International journal of food microbiology Vol. 301; pp. 1 - 8
• Main Authors: Montanari, Chiara, Tabanelli, Giulia, Zamagna, Ilaria, Barbieri, Federica, Gardini, Aldo, Ponzetto, Mauro, Redaelli, Erika, Gardini, Fausto
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 16.07.2019; Elsevier BV
• Subjects: Baking yeast; Beverage industry; Beverages; Carbon/nitrogen ratio; death; Energy costs; Food industry; Food processing industry; Food quality; Fruit beverages; Fruit juices; fruits; heat tolerance; Heat transfer; Heat treatment; Heat treatments; Inoculum; Kluyveromyces marxianus; Logistic regression; microbial physiology; Microbiology; Microorganisms; Optimization; orange juice; Oranges; Pasteurization; predictive microbiology; probability; Process parameters; regression analysis; Regression models; Saccharomyces cerevisiae; Saccharomycodes; Schizosaccharomyces pombe; Sensory properties; Soft drinks; Species; Spoilage; Stability; Statistical analysis; stress response; temperature; Thermal resistance; Thermal treatment; Weibull model; Yeast; yeasts; Zygosaccharomyces rouxii; Logistic regression; Weibull model; Yeast; Fruit beverages; Thermal treatment
• DOI: 10.1016/j.ijfoodmicro.2019.04.006
• ISSN: 0168-1605; 1879-3460

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. •High variability in yeast thermal resistance was found.•A logit model described S. cerevisiae inactivation in relation to process parameters.•Thermal treatment can be optimized to limit heat damage and energy cost.