Evaluation of Models Describing the Growth of Nalidixic Acid-Resistant E. coli O157:H7 in Blanched Spinach and Iceberg Lettuce as a Function of Temperature
The aim of this study was to model the growth of nalidixic acid-resistant E. coli O157:H7 ( E. coli O157:H7 NR) in blanched spinach and to evaluate model performance with an independent set of data for interpolation (8.5, 13, 15 and 27 °C) and for extrapolation (broth and fresh-cut iceberg lettuce) using the ratio method and the acceptable prediction zone method. The lag time (LT), specific growth rate (SGR) and maximum population density (MPD) obtained from each primary model were modeled as a function of temperature (7, 10, 17, 24, 30, and 36 °C) using Davey, square root, and polynomial models, respectively. At 7 °C, the populations of E. coli O157:H7 NR increased in tryptic soy broth with nalidixic acid (TSBN), blanched spinach and fresh-cut iceberg lettuce, while the populations of E. coli O157:H7 decreased in TSB after 118 h of LT, indicating the risk of nalidixic acid-resistant strain of E. coli O157:H7 contaminated in ready-to-eat produce at refrigerated temperature. When the LT and SGR models of blanched spinach was extended to iceberg lettuce, all relative errors (percentage of RE = 100%) were inside the acceptable prediction zone and had an acceptable Bf and Af values. Thus, it was concluded that developed secondary models for E. coli O157:H7 NR in blanched spinach were suitable for use in making predictions for fresh cut iceberg lettuce, but not for static TSBN in this work.
References
[1]
USDA Microbiological Data Program-Progress Update and 2009 Data Summary. Available online: http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELPRDC5088761 (accessed on 27 May 2013).
[2]
Berger, C.N.; Sodha, S.V.; Shaw, R.K.; Griffin, P.M.; Pink, D.; Hand, P.; Frankel, G. Fresh fruit and vegetables as vehicles for the transmission of human pathogens. Environ. Microbiol. 2010, 12, 2385–2397, doi:10.1111/j.1462-2920.2010.02297.x.
[3]
CDC Investigation Update: Multistate Outbreak of E. coli O157:H7 Infections Linked to Romaine Lettuce. Available online: http://www.cdc.gov/ecoli/2011/ecoliO157/romainelettuce/032312/index.html (accessed on 23 March 2013).
[4]
Harrington, R. Germany Finally Confirms Source of Deadly E. coli Outbreak. Available online: http://www.foodproductiondaily.com/Quality-Safety/Germany-finally-confirms-source-of-deadly-E.coli-outbreak (accessed on 13 June 2013).
[5]
CDC Multistate Outbreak of Shiga Toxin-producing Escherichia coli O157:H7 Infections Linked to Organic Spinach and Spring Mix Blend. Available online: http://www.cdc.gov/ecoli/2012/O157H7-11-12/index.html (accessed on 10 December 2012).
[6]
Kozak, G.K.; MacDonald, D.; Landry, L.; Farber, J.M. Foodborne outbreaks in Canada linked to produce: 2001 through 2009. J. Food Prot. 2013, 76, 173–183.
[7]
Ross, T.; Ratkowsky, D.A.; Mellefont, L.A.; McMeekin, T.A. Modelling the effects of temperature, water activity, pH and lactic acid concentration on the growth rate of Escherichia coli. Int. J. Food Microbiol. 2003, 82, 33–43, doi:10.1016/S0168-1605(02)00252-0.
[8]
Presser, K.A.; Ratkowsky, D.A.; Ross, T. Modelling the growth rate of Escherichia coli as a function of pH and lactic acid concentration. Appl. Environ. Microbiol. 1997, 63, 2355–2360.
[9]
Sutherland, J.P.; Bayliss, A.J.; Braxton, D.S.; Beaumont, A.L. Predictive modelling of Escherichia coli O157:H7: Inclusion of carbon dioxide as a fourth factor in a pre-existing model. Int. J. Food Microbiol. 1997, 37, 113–120, doi:10.1016/S0168-1605(97)00056-1.
[10]
Kovarova, K.; Zehnder, A.J.; Egli, T. Temperature-dependent growth kinetics of Escherichia coli ML 30 in glucose-limited continuous culture. J. Bacteriol. 1996, 178, 4530–4539.
[11]
Sutherland, J.P.; Bayliss, A.J.; Braxton, D.S. Predictive modelling of growth of Escherichia coli O157:H7: The effects of temperature, pH and sodium chloride. Int. J. Food Microbiol. 1995, 25, 29–49, doi:10.1016/0168-1605(94)00082-H.
[12]
Buchanan, R.L.; Bagi, L.K.; Goins, R.V.; Phillips, J.G. Response surface models for the growth kinetics of Escherichia coli O157:H7. Food Microbiol. 1993, 10, 303–315, doi:10.1006/fmic.1993.1035.
[13]
Koseki, S.; Isobe, S. Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table. Int. J. Food Microbiol. 2005, 104, 239–248, doi:10.1016/j.ijfoodmicro.2005.02.012.
[14]
McKellar, R.C.; Delaquis, P. Development of a dynamic growth-death model for Escherichia coli O157:H7 in minimally processed leafy green vegetables. Int. J. Food Microbiol. 2011, 151, 7–14, doi:10.1016/j.ijfoodmicro.2011.07.027.
[15]
Oscar, T.P. Development and validation of primary, secondary, and tertiary models for growth of Salmonella typhimurium on sterile chicken. J. Food Prot. 2005, 68, 2606–2613.
[16]
Ross, T. Indices for performance evaluation of predictive models in food microbiology. J. Appl. Bacteriol. 1996, 81, 501–508.
[17]
Oscar, T.P. Validation of lag time and growth rate models for Salmonella typhimurium: Acceptable prediction zone method. Food Microbiol. Saf. 2005, 70, M129–M137.
[18]
Inatsu, Y.; Bari, M.L.; Kawasaki, S.; Isshiki, K.; Kawamoto, S. Efficacy of acidified sodium chlorite treatments in reducing Escherichia coli O157:H7 on Chinese cabbage. J. Food Prot. 2005, 68, 251–255.
[19]
Yoon, K.S.; Burnette, C.N.; Abou-Zeid, K.A.; Whiting, R.C. Control of growth and survival of Listeria monocytogenes on smoked salmon by combined potassium lactate and sodium diacetate and freezing stress during refrigeration and frozen storage. J. Food Prot. 2004, 67, 2465–2471.
[20]
Daughtry, B.J.; Davey, K.R.; King, K.D. Temperature dependence of growth kinetics of food bacteria. Food Microbiol. 1997, 14, 21–30, doi:10.1006/fmic.1996.0064.
[21]
Oscar, T.P. Development and validation of a tertiary simulation model for predicting the potential growth of Salmonella typhimurium on cooked chicken. Int. J. Food Microbiol. 2002, 76, 177–190, doi:10.1016/S0168-1605(02)00025-9.
[22]
Ratkowsky, D.A.; Olley, J.; McMeekin, T.A.; Ball, A. Relationship between temperature and growth rate of bacterial cultures. J. Bacteriol. 1982, 149, 1–5.
[23]
McMeekin, T.A.; Olley, J.; Ross, T. Predictive Microbiology: Theory and Application; John Wiley & Sons Ltd.: Hoboken, NJ, USA, 1993.
[24]
Abou-Zeid, K.A.; Oscar, T.P.; Schwarz, J.G.; Hashem, F.M.; Whiting, R.C.; Yoon, K. Development and validation of a predictive model for Listeria monocytogenes Scott A as a function of temperature, pH, and commercial mixture of potassium lactate and sodium diacetate. J. Microbiol. Biotechnol. 2009, 19, 718–726.
[25]
Delignette-Muller, M.L.; Rosso, L.; Flandrois, J.P. Accuracy of microbial growth predictions with square root and polynomial models. Int. J. Food Microbiol. 1995, 27, 139–146, doi:10.1016/0168-1605(94)00158-3.
[26]
Bharathi, S.; Ramesh, M.N.; Varadaraj, M.C. Predicting the behavioural pattern of Escherichia coli in minimally processed vegetables. Food Control 2001, 12, 275–284, doi:10.1016/S0956-7135(01)00008-1.
[27]
Khalil, R.K.; Frank, J.F. Behavior of Escherichia coli O157:H7 on damaged leaves of spinach, lettuce, cilantro, and parsley stored at abusive temperatures. J. Food Prot. 2010, 73, 212–220.
[28]
Palumbo, S.A.; Call, J.E.; Schultz, F.J.; Williams, A.C. Minimum and maximum temperatures for growth and verotoxin production by hemorrhagic strains of Escherichia coli. J. Food Prot. 1995, 58, 352–356.
[29]
Rosso, L.; Lobry, J.R.; Flandrois, J.P. An unexpected correlation between cardinal temperatures of microbial growth highlighted by a new model. J. Theor. Biol. 1993, 162, 447–463, doi:10.1006/jtbi.1993.1099.
[30]
Tamplin, M.L. Growth of Escherichia coli O157:H7 in raw ground beef stored at 10 °C and the influence of competitive bacterial flora, strain variation, and fat level. J. Food Prot. 2002, 65, 1535–1540.
[31]
Ross, T. Predictive Food Microbiology Models in the Meat Industry; Meat and Livestock Australia (MLA): North Sydney, Australia, 1999; p. 196.
[32]
Walls, I.; Scott, V.N. Validation of predictive mathematical models describing the growth of Escherichia coli O157:H7 in raw ground beef. J. Food Prot. 1996, 59, 1331–1335.
[33]
Rasch, M. Experimental Design and Data Collection. Modelling Microbial Responses in Food; CRC Press: London, UK, 2004.
[34]
Salter, M.A.; Ross, T.; McMeekin, T.A. McMeekin, Applicability of a model for non-pathogenic Escherichia coli for predicting the growth of pathogenic Escherichia coli. J. Appl. Microbiol. 1998, 85, 357–364.
