Calculating microbial survival parameters and predicting survival curves from non-isothermal inactivation data.
Irrespective of whether the isothermal semi-logarithmic survival curves of heat inactivated microbial cells or spores are linear or nonlinear, it is theoretically possible to numerically calculate their survival parameters from inactivation data obtained under non-isothermal conditions. A method to do the calculation, when the temperature history ('profile') is expressed algebraically, is demonstrated with simulated survival curves. It has been tested with the published survival data of Salmonella, whose nonlinear semi-logarithmic isothermal survival curves can be described by a power law model. The reported survival ratios of Salmonella, determined during non-isothermal heat treatments in a broth and in ground chicken breast, were used to estimate its isothermal survival parameters in the two media and their temperature dependence. These, in turn, were used to predict the cells' survival curves under different temperature 'profiles.' There was a good agreement between the predicted and the reported experimental survival curves in the broth case and reasonable agreement in the ground chicken breasts, where the database was considerably smaller The development of a mathematical method to calculate survival parameters from non-isothermal inactivation data will eliminate the need to determine these parameters under isothermal conditions, which can only be approximated and are technically difficult to perform. In many cases, the proposed method will also enable the determination of the survival parameters in the actual food or medium of interest, which may contain particles, or is too viscous to be heated and cooled effectively using the currently available experimental procedures. In principle, the described mathematical method can also be used to assess organisms' survival parameters in nonthermal inactivation processes, such as exposure to a dissipating chemical agent or the application of ultra high-pressure.
Peleg
Micha
M
Department of Food Science, Chenoweth Laboratory, University of Massachusetts, Amherst, Massachusetts 01003, USA. micha.peleg@foodsci.umass.edu
Normand
Mark D
MD
D000818:Animals; D018407:Bacterial Physiological Phenomena; D002645:Chickens; D005516:Food Microbiology; D006358:Hot Temperature; D007700:Kinetics; D008433:Mathematics; D008828:Microbiological Techniques; D008954:Models, Biological; D011202:Poultry Products / Q000382:microbiology; D012475:Salmonella / Q000502:physiology; D013171:Spores, Bacterial / Q000502:physiology