A Focus on the Death Kinetics in Predictive Microbiology: Benefits and Limits of the Most Important Models and Some Tools Dealing with Their Application in Foods
Abstract
:1. Introduction: A Focus on Predictive Microbiology
2. Overview of Death Equations
2.1. Log-Linear Model
2.2. Shoulder-Tail and Negative Gompertz Equations
- i)
- Microorganisms are organized in clumps. The shoulder is the time before all but one organism in such a clump has been killed.
- ii)
- Cells tend to counterbalance the effect of a lethal treatment, thus the shoulder is the period when cells are able to resynthesize a critical component and death occurs only when the rate of destruction exceeds the rate of synthesis.
- iii)
- A shoulder could describe the protective effect of the medium or some components (fats, proteins) on cells.
- iv)
- A shoulder may describe a kind of cumulative injury that must occur before cell inactivation.
- i)
- Vitalistic approach: this sub-population is very resistant to heat/inactivation treatment.
- ii)
- Mechanistic approach. Theory I: the tail is a “normal” trait of an inactivation kinetic, as it describes a sub-population inaccessible to or adapted to the lethal treatment.
- iii)
- Mechanistic approach. Theory II: the tail is an artifact, because the residual sub-population is genetically more resistant or does not receive the same lethal dose.
2.3. Weibull
2.4. Biphasic Equation
2.5. Other Models
2.5.1. Casolari I
2.5.2. Casolari II
2.5.3. Sapru
2.5.4. Whiting
2.5.5. Xiong
2.6. Death Model and Probability
Benefits | Limits | |
---|---|---|
Shoulder/ tail |
|
|
Negative Gompertz |
|
|
Weibull |
|
|
Biphasic |
|
|
3. Tools
3.1. GInaFit
3.2. Meat and Livestock Australia (MLA)-Model for Escherichia coli Inactivation in Fermented Meats
3.3. AMIF Process Lethality Determination Spreadsheet
3.4. DMFit
Author Contributions
Conflicts of Interest
References
- Bigelow, W.D. The logarithmic nature of thermal death time curves. J. Infect. Dis. 1921, 29, 528–536. [Google Scholar] [CrossRef]
- Bigelow, W.D.; Esty, J.R. The thermal death point in relation to time of thermophilic microorganisms. J. Infect. Dis. 1920, 27, 602–617. [Google Scholar] [CrossRef]
- Esty, J.R.; Meyer, K.F. The heat resistance of spores of B. botulinus and allied anaerobes. J. Infect. Dis. 1922, 31, 650–663. [Google Scholar] [CrossRef]
- Pérez-Rodríguez, F.; Valero, A. Predictive Microbiology in Foods; Springer: London, UK, 2013. [Google Scholar]
- Roberts, T.A.; Jarvis, B. Predictive modelling of food safety with particular reference to Clostridium botulinum in model cured meat systems. In Food Microbiology: Advances and Prospects; Roberts, T.A., Skinner, F.A., Eds.; Academic Press: New York, NY, USA, 1983; pp. 85–95. [Google Scholar]
- Esty, J.R.; Williams, C.C. Heat resistance studies. A new method for determination of heat resistance of bacterial spores. J. Infect. Dis. 1924, 34, 516–528. [Google Scholar] [CrossRef]
- Ball, C.O.; Olson, F.C.W. Sterilization in Food Technology Theory, Practice and Calculation; McGraw-Hill Book: New York, NY, USA, 1957. [Google Scholar]
- Cole, M.B.; Davies, K.W.; Munro, G.; Holyoak, C.D.; Kilsby, D.C. A vitalistic model to describe the thermal inactivtion of Listeria monocytogenes. J. Ind. Microbiol. 1993, 12, 232–239. [Google Scholar] [CrossRef]
- Geeraerd, A.H.; Valdramidis, V.P.; Van Impe, J.F. GInaFit, a freeware tool to assess non-log-linear microbial survivor curves. Int. J. Food Microbiol. 2005, 102, 95–105. [Google Scholar] [CrossRef] [PubMed]
- Geeraerd, A.H.; Herremans, C.H.; Van Impe, J.F. Structural model requirements to describe microbial inactivation during a mild heat treatment. Int. J. Food Microbiol. 2000, 59, 185–200. [Google Scholar] [CrossRef]
- Casolari, A. Microbial death. In Physiological Models in Microbiology; Bazin, M.J., Prosser, J.I., Eds.; CRC Press: Boca Raton, FL, USA, 1988; Volume 2, pp. 1–44. [Google Scholar]
- Bevilacqua, A.; Sinigaglia, M. Food shelf life and safety: Challenge tests, prediction and mathematical tools. In Application of Alternative Food-Preservation Technologies to Enhance Food Safety and Stability; Bevilacqua, A., Corbo, M.R., Sinigaglia, M., Eds.; Bentham Publisher: Sharjah, UAE, 2010; pp. 161–187. [Google Scholar]
- Bhaduri, S.; Smith, P.W.; Palumbo, S.A.; Turner-Jones, C.O.; Smith, J.L.; Marmer, B.S.; Buchanan, R.L.; Zaika, L.L.; Williams, A.C. Thermal destruction of Listeria monocytogenes in liver sausage slurry. Food Microbiol. 1991, 8, 75–78. [Google Scholar] [CrossRef]
- Linton, R.H.; Carter, W.H.; Pierson, M.D.; Hackney, C.R. Use of a modified Gompertz Equation to model nonlinear survival curves for Listeria monocytogenes Scott A. J. Food Prot. 1995, 58, 946–954. [Google Scholar]
- Corbo, M.R.; Campaniello, D.; D’Amato, D.; Bevilacqua, A.; Sinigaglia, M. Behavior of Listeria monocytogenes and Escherichia coli O157:H7 in fresh-sliced cactus pear fruit. J. Food Saf. 2005, 25, 157–172. [Google Scholar] [CrossRef]
- Couvert, O.; Gaillard, S.; Savy, N.; Mafart, P.; Leguérinel, I. Survival curves of heated bacterial spores: Effect of environmental factors on Weibull parameters. Int. J. Food Microbiol. 2005, 101, 73–81. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mafart, P.; Couvert, O.; Gaillard, S.; Leguerinel, I. On calculating sterility in thermal preservation methods: Application of the Weibull frequency distribution model. Int. J. Food Microbiol. 2000, 72, 107–113. [Google Scholar] [CrossRef]
- Van Boekel, M.A. On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells. Int. J. Food Microbiol. 2002, 74, 139–159. [Google Scholar] [CrossRef]
- Bevilacqua, A.; Cibelli, F.; Cardillo, D.; Altieri, C.; Sinigaglia, M. Metabolic effects of Fusarium spp. on Escherichia coli O157:H7 and Listeria monocytogenes on raw portioned tomatoes. J. Food Prot. 2008, 71, 1366–1371. [Google Scholar] [PubMed]
- Albert, I.; Mafart, P. A modified Weibull model for bacterial inactivation. Int. J. Food Microbiol. 2005, 100, 197–211. [Google Scholar] [CrossRef] [PubMed]
- Cerf, O. Tailing of survival curves of bacterial spores, a review. J. Appl. Bacteriol. 1977, 42, 1–19. [Google Scholar] [CrossRef] [PubMed]
- Sapru, V.; Teixeira, A.A.; Smerage, G.H.; Lindsay, J.A. Predicting thermophilic spore population dynamics for UHT sterilization processes. J. Food Sci. 1992, 575, 1248–1252. [Google Scholar] [CrossRef]
- Whiting, R.C. Modeling bacterial survival in unfavorable environments. J. Ind. Microbiol. 1993, 12, 240–246. [Google Scholar] [CrossRef]
- Xiong, R.; Xie, G.; Edmondson, A.E.; Sheard, M.A. A mathematical model for bacterial inactivation. Int. J. Food Microbiol. 1999, 46, 45–55. [Google Scholar] [CrossRef]
- Peleg, M.; Cole, M.B. Reinterpretation of microbial survival curves. Crit. Rev. Food Sci. Nutr. 1998, 38, 353–380. [Google Scholar] [CrossRef] [PubMed]
- Bassett, J.; Nauta, M.; Lindqvist, R.; Zwietering, M. Tools for Microbiological Risk Assessment; ILSI Europe: Brussels, Belgium, 2012. [Google Scholar]
- GInaFit. Availabe online: cit.kuleuven.be/biotec/downloads.php (accessed on 26 July 2015).
- Model for Escherichia coli inactivation in fermented meats. Available online: www.foodsafetycentre.com.au/fermenter.php (accessed on 26 July 2015).
- Combase. Available online: www.combase.cc (accessed on 26 July 2015).
- Baranyi, J.; Roberts, T.A. A dynamic approach to predicting bacterial growth curve in food. Int. J. Food Microbiol. 1994, 23, 277–294. [Google Scholar] [CrossRef]
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Bevilacqua, A.; Speranza, B.; Sinigaglia, M.; Corbo, M.R. A Focus on the Death Kinetics in Predictive Microbiology: Benefits and Limits of the Most Important Models and Some Tools Dealing with Their Application in Foods. Foods 2015, 4, 565-580. https://doi.org/10.3390/foods4040565
Bevilacqua A, Speranza B, Sinigaglia M, Corbo MR. A Focus on the Death Kinetics in Predictive Microbiology: Benefits and Limits of the Most Important Models and Some Tools Dealing with Their Application in Foods. Foods. 2015; 4(4):565-580. https://doi.org/10.3390/foods4040565
Chicago/Turabian StyleBevilacqua, Antonio, Barbara Speranza, Milena Sinigaglia, and Maria Rosaria Corbo. 2015. "A Focus on the Death Kinetics in Predictive Microbiology: Benefits and Limits of the Most Important Models and Some Tools Dealing with Their Application in Foods" Foods 4, no. 4: 565-580. https://doi.org/10.3390/foods4040565