Modeling of yeast thermal resistance and optimization of the pasteurization treatment applied to soft drinks
| Autor: | Mauro Ponzetto, Giulia Tabanelli, Chiara Montanari, Erika Redaelli, Aldo Gardini, Fausto Gardini, Ilaria Zamagna, Federica Barbieri |
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| Přispěvatelé: | Montanari, Chiara, Tabanelli, Giulia, Zamagna, Ilaria, Barbieri, Federica, Gardini, Aldo, Ponzetto, Mauro, Redaelli, Erika, Gardini, Fausto |
| Rok vydání: | 2019 |
| Předmět: |
Food industry
Food spoilage Logistic regression Pasteurization Carbonated Beverages Saccharomyces cerevisiae Microbiology law.invention 03 medical and health sciences Weibull model Kluyveromyces marxianus law Food microbiology Thermal treatment Food-Processing Industry Food science Carbonated Beverage Citrus sinensi 030304 developmental biology Mathematics Orange juice 0303 health sciences biology 030306 microbiology business.industry Temperature General Medicine Models Theoretical biology.organism_classification Yeast Fruit and Vegetable Juices Fruit and Vegetable Juice Food Microbiology Food processing Fruit beverage business Citrus sinensis Food Science |
| Zdroj: | International Journal of Food Microbiology. 301:1-8 |
| ISSN: | 0168-1605 |
| DOI: | 10.1016/j.ijfoodmicro.2019.04.006 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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