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Growth Characteristics of Enterobacter sakazakii Used to Develop a Predictive Model  

Seo, Kyo-Young (Department of Food Science and Technology, Chung-Ang University)
Heo, Sun-Kyung (Department of Food Science and Technology, Chung-Ang University)
Bae, Dong-Ho (Division of Bioscience and Biotechnology, Konkuk University)
Oh, Deog-Hwan (Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology, Kangwon National University)
Ha, Sang-Do (Department of Food Science and Technology, Chung-Ang University)
Publication Information
Food Science and Biotechnology / v.17, no.3, 2008 , pp. 642-650 More about this Journal
Abstract
A mathematical model was developed for predicting the growth rate of Enterobacter sakazakii in tryptic soy broth medium as a function of the combined effects of temperature (5, 10, 20, 30, and $40^{\circ}C$), pH (4, 5, 6, 7, 8, 9, and 10), and the NaCl concentration (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10%). With all experimental variables, the primary models showed a good fit ($R^2=0.8965$ to 0.9994) to a modified Gompertz equation to obtain growth rates. The secondary model was 'In specific growth $rate=-0.38116+(0.01281^*Temp)+(0.07993^*pH)+(0.00618^*NaCl)+(-0.00018^*Temp^2)+(-0.00551^*pH^2)+(-0.00093^*NaCl^2)+(0.00013^*Temp*pH)+(-0.00038^*Temp*NaCl)+(-0.00023^*pH^*NaCl)$'. This model is thought to be appropriate for predicting growth rates on the basis of a correlation coefficient (r) 0.9579, a coefficient of determination ($R^2$) 0.91, a mean square error 0.026, a bias factor 1.03, and an accuracy factor 1.13. Our secondary model provided reliable predictions of growth rates for E. sakazakii in broth with the combined effects of temperature, NaCl concentration, and pH.
Keywords
Enterobacter sakazakii; predictive model; growth rate;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
Times Cited By Web Of Science : 3  (Related Records In Web of Science)
Times Cited By SCOPUS : 2
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1 Jung MK, Park JH. Prevalence and thermal stability of Enterobacter sakazakii form unprocessed ready-to-eat agricultural products and powdered infant formulas. Food Sci. Biotechnol. 15: 152-157 (2006)   과학기술학회마을
2 Urmenty AMC, Franklin AW. Neonatal death from pigmented coliform infection. Lancet 1: 313-315 (1961)
3 Iversen C, Forsythe S. Risk profile of Enterobacter sakazakii, an emergent pathogen associated with infant milk formula. Trends Food Sci. Tech. 14: 443-454 (2003)   DOI   ScienceOn
4 Schaffner DW, Labuza TP. Predictive microbiology: Analyzing the present and the future. Food Technol.-Chicago 51: 95-99 (1997)
5 GraphPad Software, Inc. Prism 4 User's Guide. GraphPad Software Institute, San Diego, CA, USA (2003)
6 Nerbrink E, Borch E, Blom H, Nesbakken T. A model based on absorbance data on the growth rate of Listeria monocytogenes and including the effects of pH, NaCl, Na-lactate, and Na-acetate. Int. J. Food Microbiol. 47: 99-109 (1999)   DOI   ScienceOn
7 Neumeyer K, Ross T, McMeekin TA. Development of a predictive model to describe the effects of temperature and water activity on the growth of spoilage Pseudomonas. Int. J. Food Microbiol. 38: 45- 54 (1997)   DOI   ScienceOn
8 Zurera-Cosano GA, Castillejo-Rodríguez M, García-Gimeno RM, Rincón-León F. Performance of response surface and Davey model for prediction of Staphylococcus aureus growth parameters under different experimental conditions. J. Food Protect. 67: 1138-1145 (2004)   DOI
9 Park SY, Choi JW, Yeon JH, Lee MJ, Chung DH, Kim MG, Lee KH, Kim KS, Lee DH, Bahk GJ, Bae DH, Kim KY, Kim CH, Ha SD. Predictive modeling for the growth of Listeria monocytogenes as a function of temperature, NaCl, and pH. J. Microbiol. Biotechn. 15: 1323-1329 (2005)   과학기술학회마을
10 Adair C, Kilsby DC, Whittall PT. Comparison of the school field (non-linear Arrhenius) model and the square root model for predicting bacterial growth in foods. Food Microbiol. 6: 7-18 (1989)   DOI
11 Ross T. Predictive Food Microbial. Models in the Meat Industry. Meat and Livestock Australia, Sydney, Australia. p. 196 (1999)
12 Breener DJ, Farmer III JJ, Hickman FW, Asbury MA, Steigerwalt AG. Taxonomic and Nomenclature Changes in Enterobacteriaceae. Centers for Disease Control and Prevention, Atlanta, GA, USA (1977)
13 Kim SH, Park JH. Thermal resistance and inactivation of Enterobacter saskazakii isolates during rehydration of powdered infant formula. J. Microbiol. Biotechn. 17: 364-368 (2007)   과학기술학회마을
14 Seo KY, Chung DH, Kim MG, Lee KH, Kim KS, Bahk GJ, Bae DH, Kim KY, Kim CH, Ha SD. Development of predictive mathematical model for the growth kinetics of Staphylococcus aureus by response surface model. J. Microbiol. Biotechn. 17: 1437- 1444 (2007)   과학기술학회마을
15 Farmer JJ III, Asbury MA, Hickman FW, Brenner DJ. The Enterobacteriaceae study group. Enterobacter sakazakii: A new species of 'Enterobacter sakazakii' isolated from clinical specimens. Int. J. Syst. Bacteriol. 30: 569-584 (1980)   DOI
16 Bektas S, Goetze B, Speer CP. Decreased adherence, chemotaxis, and phagocytic activities of neutrophils from preterm neonates. Acta Pediatr. Scand. 79: 1031-1038 (1990)   DOI
17 Skinner GE, Larkin JW, Rhodehamel EJ. Mathematical modeling of microbial growth: A review. J. Food Safety 14: 175-217 (1994)   DOI   ScienceOn
18 Sutherland JP, Bayliss AJ, Roberts TA. Predictive modeling of growth of Staphylococcus aureus: The effects of temperature, pH, and sodium chloride. Int. J. Food Microbiol. 21: 217-236 (1994)   DOI   ScienceOn
19 Jin S-S, Jin Y-G, Yoon KS, Woo G-J, Hwang I-G, Bahk G-J, Oh DH. Predictive modeling of the growth and survival of Listeria monocytogenes using a response surface model. Food Sci. Biotechnol. 15: 715-720 (2006)   과학기술학회마을
20 Dalgaard P, Ross T, Kamperman L, Neumeyer K, McMeekin TA. Estimation of bacterial growth rates from turbidimetric and viable count data. Int. J. Food Microbiol. 23: 391-404 (1994)   DOI   ScienceOn
21 Whiting RC. Microbiogical modeling. Crit. Rev. Food Sci. 35: 457- 494 (1995)
22 Dlgaard P, Mejlholm O, Huss HH. Application of an iterative approach for development of a microbial model predicting the shelflife of packed fish. Int. J. Food Microbiol. 38: 169-179 (1997)   DOI
23 Palumbo SA, Williams AC, Buchanan RL, Phillips JG. Model for the aerobic growth of Aeromonas hydrophila K144. J. Food Protect. 54: 429-435 (1991)   DOI
24 Duffy LL, Vanderlinde PB, Grau FH. Growth of Listeria monocytogenes on vacuum-packed cooked meats: Effects of pH, Aw, nitrite, and ascorbate. Int. J. Food Microbiol. 23: 377-390 (1994)   DOI   ScienceOn
25 Himelright I, Harris E, Lorch V, Anderson M, Jones T, Craig A, Kuehnert M, Forster T, Arduino M, Jensen B, Jernigan D. Enterobacter sakazakii infections associated with the use of powdered infant formula - Tennessee. Morbid. Mort. Weekly Rpt. 51: 298-300 (2002)
26 Park SY, Choi J-W, Chung DH, Kim M-G, Lee K-H, Kim K-S, Bahk G-J, Bae D-H, Park S-K, Kim K-Y, Kim C-H, Ha S-D. Development of a predictive mathematical model for the growth kinetics of Listeria monocytogenes in sesame leaves. Food Sci. Biotechnol. 16: 238-242 (2007)   과학기술학회마을
27 Whiting RC, Buchanan RL. Predictive modeling. pp. 728-739. In: Food Microbiology: Fundamentals and Frontiers. Doyle MP, Beuchat LR, Montville TJ (eds). ASM Press, Washington DC, USA (1997)
28 Gibson AM, Bratchell N, Roberts TA. Predicting microbial growth: Growth responses of Salmonella in a laboratory medium as affected by pH, sodium chloride, and storage temperature. Int. J. Food Microbiol. 6: 155-178 (1988)   DOI   ScienceOn
29 Buchanan RL, Phillips JG. Response surface models for predicting the effects of temperature, pH, sodium chloride content, sodium nitrite concentration, and atmosphere on the growth of Listeria monocytogenes. J. Food Protect. 53: 370-376 (1990)   DOI
30 Buchanan RL. Predictive food microbiology. Trends Food Sci. Tech. 4: 6-11 (1993)   DOI   ScienceOn
31 Soboleva TK, Pleasants AB, Roux G le. Predictive microbiology and food safety. Int. J. Food Microbiol. 57: 183-192 (2000)   DOI   ScienceOn
32 Park SY, Seo KY, Ha SD. A response surface model based on absorbance data for the growth rates of Salmonella enterica serovar Typhimurium as a function of temperature, NaCl, and pH. J. Microbiol. Biotechn. 15: 1323-1329 (2007)   과학기술학회마을
33 Grau FH, Vanderlinede PB. Aerobic growth of Listeria monocytogenes on beef lean and fatty tissue: Equations describing the effects of temperature and pH. J. Food Protect. 56: 96-101 (1993)   DOI
34 Karch H, Bielaszewska M, Bitzan M, Schmidt H. Epidemiology and diagnosis of shiga toxin-producing Escherichia coli infections. Diagn. Micr. Infec. Dis. 34: 229-243 (1999)   DOI   ScienceOn
35 Ross T. Indices for performance evaluation of predictive models in food microbiology. J. Appl. Bacteriol. 81: 501-508 (1996)
36 Buchanan RL, Bagi LK, Goins RV, Phillips JG. Response surface model for the growth kinetics of Escherichia coli O157:H7. Food Microbiol. 10: 303-315 (1993)   DOI   ScienceOn
37 SAS Institute, Inc. SAS User's Guide. Statistical Analysis Systems Institute, Cary, NC, USA (2002)
38 Bhaduri S, Turner-Jones CO, Buchanan RL, Phillips JG. Response surface models of the effect of pH, sodium chloride, and sodium nitrite on growth of Yersinia enterocolitica at low temperatures. Int. J. Food Microbiol. 23: 333-343 (1994)   DOI   ScienceOn