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Modeling survival of Listeria monocytogenes in the traditional Greek soft cheese Katiki
Authors:Mataragas Marios  Stergiou Virginia  Nychas George-John E
Affiliation:Laboratory of Food Quality Control and Hygiene, Department of Food Science and Technology, Agricultural University of Athens, Iera Odos 75, GR-11855 Athens, Greece. mmat@aua.gr
Abstract:In the present work, survival of Listeria monocytogenes in the traditional Greek soft, spreadable cheese Katiki was studied throughout the shelf life of the product. Samples of finished cheese were inoculated with a cocktail of five L. monocytogenes strains (ca. 6 log CFU g(-1)) and stored at 5, 10, 15, and 20 degrees C. Acid-stress adaptation or cross-protection to the same stress was also investigated by inoculation of acid-adapted cells in the product. The results showed that pathogen survival was biphasic. Various mathematical equations (Geeraerd, Cerf, Albert-Mafart, Whiting, Zwietering, and Baranyi models) were fitted to the experimental data. A thorough statistical analysis was performed to choose the best model. The Geeraerd model was finally selected, and the results revealed no acid tolerance acquisition (no significant differences, P > 0.05, in the survival rates of the non-acid-adapted and acid-adapted cells). Secondary modeling (second-order polynomial with a(0) = 0.8453, a(1) = -0.0743, and a(2) = 0.0059) of the survival rate (of sensitive population), and other parameters that were similar at all temperatures (fraction of initial population in the major population = 99.98%, survival rate of resistant population = 0.10 day(-1), and initial population = 6.29 log CFU g(-1)), showed that survival of the pathogen was temperature dependent with bacterial cells surviving for a longer period of time at lower temperatures. Finally, the developed predictive model was successfully validated at two independent temperatures (12 and 17 degrees C). This study underlines the usefulness of predictive modeling as a tool for realistic estimation and control of L. monocytogenes risk in food products. Such data are also useful when conducting risk assessment studies.
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