Modeling survival of high hydrostatic pressure treated stationary- and exponential-phase Listeria innocua cells

• Published in: Innovative food science & emerging technologies 2009-04, Vol.10 (2), p.135-141
• Main Authors: Saucedo-Reyes, Daniela, Marco-Celdrán, Aurora, Pina-Pérez, María Consuelo, Rodrigo, D., Martínez-López, Antonio
• Format: Article
• Language: English
• Subjects: cell cycle; equations; food pathogens; Gompertz and Baranyi models; High hydrostatic pressure; high pressure treatment; Inactivation kinetics; kinetics; Listeria innocua; mathematical models; microbial growth; mortality; Predictive microbiology; simulation models
• ISSN: 1466-8564; 1878-5522
• DOI: 10.1016/j.ifset.2008.11.004

High Hydrostatic Pressure (HHP) inactivation (325–400 MPa; 0–20 min; maximum temperature 30 °C) of cells of Listeria innocua CECT 910 was studied in two different growth phases (exponential and stationary), and the corresponding survival curves were obtained for each case. The curves were fitted to two nonlinear models, the modified Gompertz equation and the Baranyi model. The kinetic constants calculated for both models, µ max and k max, indicated that cells in exponential growth phase were more sensitive to pressure than those in stationary phase. Both mathematical models were suitable for describing L. innocua HHP survival curves, rendering kinetic constants that increased with increasing pressure. When considering the experimental models validation, both Gompertz and Baranyi predicted in a similar way, however Baranyi had slightly lower A f (Accuracy factor) and B f (Bias factor) values, which indicated better prediction values. In summary, both mathematical models were perfectly valid for describing L. innocua inactivation kinetics under HHP treatment. The mathematical models for inactivation and growth of microorganisms are the foundation of predictive microbiology and are used in risk assessments procedures as part of the food safety management system. Besides, these models together with those applied to inactivation of enzymes and destruction of quality factors are essential to optimize processes and thus to lay the foundations for industrial processing. It is therefore necessary to identify generally applicable kinetic models that will produce primary and secondary kinetic parameters and are statistically reliable as a key tool to predict the behaviour of microorganisms, enzymes and quality factors after processing.