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Investigating the influence of organic acid marinades, storage temperature and time on the survival/inactivation interface of Salmonella on chicken breast fillets
- Lytou, Anastasia E., Tzortzinis, Konstantinos, Skandamis, Panagiotis N., Nychas, George-John E., Panagou, Efstathios Z.
- International journal of food microbiology 2019 v.299 pp. 47-57
- Salmonella, acetic acid, breast meat, chicken meat, citric acid, fillets, flora, lemons, marinating, model validation, models, pathogens, prediction, probability, serotypes, spoilage microorganisms, storage temperature, vinegars
- The aim of this work was to study the influence of lemon and vinegar marinades on Salmonella inoculated on chicken fillets and stored under different storage temperatures for nine days in the presence of indigenous microbiota. In addition to this, model development for the determination of the inactivation boundaries and the prediction of pathogens response was attempted. The different acid concentrations in the marinades, the type of acid, the storage temperature as well as the duration of storage impacted the levels of pathogens and background flora. The higher tested concentrations (2% and 4% v/v for acetic and citric acid) were more effective against Salmonella and spoilage microorganisms than the lower ones (0.5 and 1% v/v for acetic and citric acid), while the intermediate concentrations (1, 1.5 and 2, 3% v/v for acetic and citric acid, respectively) presented differentiations of particular interest to the microbial responses to acidic stress. The aforementioned parameters also differentiated Salmonella serovars persistence and spoilage microorganisms dominance. Regarding model development, the probability of inactivation of Salmonella was satisfactorily predicted particularly in the case of acetic acid marination while in model validation, the majority of the vinegar marinated samples were correctly classified, whereas, in case of lemon marination, a higher number of misclassifications was observed, indicating a partial weakness of the model to predict the pathogens response at interface concentrations.