Assessing the prediction ability of different mathematical models for the growth of Lactobacillus plantarum under non-isothermal conditions

Journal of Theoretical Biology

Volumn 335, Issue , 2013, Pages 88-96

  Longhi, Daniel Angelo ^a   Dalcanton, Francieli ^a   Aragão, Gláucia Maria Falcão de ^a   Carciofi, Bruno Augusto Mattar ^a   Laurindo, João Borges ^a  

^a FEDERAL UNIVERSITY OF SANTA CATARINA   (Brazil)

Author keywords

Acid lactic bacteria; Food shelf life; Non isothermal models; Predictive microbiology

Indexed keywords

BACTERIUM; FOOD QUALITY; GROWTH RATE; MEAT; MICROBIOLOGY; NUMERICAL MODEL; PREDICTION; TEMPERATURE EFFECT;

ACCURACY; ADAPTATION; ARTICLE; BACTERIAL GROWTH; CONTROLLED STUDY; CULTURE MEDIUM; FACTORIAL ANALYSIS; FREEZING; ISOTHERM; LACTOBACILLUS PLANTARUM; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MICROBIAL ACTIVITY; NONHUMAN; OSCILLATION; PREDICTION; PRIORITY JOURNAL; TEMPERATURE SENSITIVITY; VALIDATION PROCESS;

ACID LACTIC BACTERIA; FOOD SHELF LIFE; NON-ISOTHERMAL MODELS; PREDICTIVE MICROBIOLOGY;

BACTERIAL PHYSIOLOGICAL PHENOMENA; LACTOBACILLUS PLANTARUM; MODELS, BIOLOGICAL;

EID: 84880636690     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2013.06.030     Document Type: Article

References (46)

1. Augustin J.C., Rosso L., Carlier V. Estimation of temperature dependent growth rate and lag time of Listeria monocytogenes by optical density measurements. J. Microbiol. Methods 1999, 38:137-146.
2. Baranyi J. Stochastic modelling of bacterial lag phase. Int. J. Food Microbiol. 2002, 73:203-206.
3. Baranyi J., Roberts T. A dynamic approach to predicting bacterial-growth in food. Int. J. Food Microbiol. 1994, 23:277-294.
4. Baranyi J., Robinson T., Kaloti A., Mackey B. Predicting growth of brochothrix thermosphacta at changing temperature. Int. J. Food Microbiol. 1995, 27:61-75.
5. Baty F., Delignette-Muller M. Estimating the bacterial lag time: which model, which precision?. Int. J. Food Microbiol. 2004, 91:261-277.
6. Baty F., Flandrois J.P., Delignette-Muller M.L. Modeling the lag time of Listeria monocytogenes from viable count enumeration and optical density data. Appl. Environ. Microbiol. 2002, 68:5816-5825.
7. Begot C., Desnier I., Daudin J.D., Labadie J.C., Lebert A. Recommendations for calculating growth parameters by optical density measurements. J. Microbiol. Methods 1996, 25:225-232.
8. Biesta-Peters E.G., Reij M.W., Joosten H., Gorris L.G.M., Zwietering M.H. Comparison of two optical-density-based methods and a plate count method for estimation of growth parameters of Bacillus cereus. Appl. Environ. Microbiol. 2010, 76:1399-1405.
9. Borch E., KantMuermans M., Blixt Y. Bacterial spoilage of meat and cured meat products. Int. J. Food Microbiol. 1996, 33:103-120.
10. Bovill R., Bew J., Cook N., D'Agostino M., Wilkinson N., Baranyi J. Predictions of growth for Listeria monocytogenes and Salmonella during fluctuating temperature. Int. J. Food Microbiol. 2000, 59:157-165.
11. Cayre M., Vignolo G., Garro O. Modeling lactic acid bacteria growth in vacuum-packaged cooked meat emulsions stored at three temperatures. Food Microbiol. 2003, 20:561-566.
12. Corradini M., Peleg M. Estimating non-isothermal bacterial growth in foods from isothermal experimental data. J. Appl. Microbiol. 2005, 99:187-200.
13. Dalgaard P., Koutsoumanis K. Comparison of maximum specific growth rates and lag times estimated from absorbance and viable count data by different mathematical models. J. Microbiol. Methods 2001, 43:183-196.
14. Fu B., Taoukis P., Labuza T. Predictive microbiology for monitoring spoilage of dairy-products with time-temperature integrators. J. Food Sci. 1991, 56:1209-1215.
15. Fujikawa H., Kai A., Morozumi S. A new logistic model for Escherichia coli growth at constant and dynamic temperatures. Food Microbiol. 2004, 21:501-509.
16. Garcia-Gimeno R., Hervas-Martinez C., de Siloniz M Improving artificial neural networks with a pruning methodology and genetic algorithms for their application in microbial growth prediction in food. Int. J. Food Microbiol. 2002, 72:19-30.
17. Gospavic R., Kreyenschmidt J., Bruckner S., Popov V., Haque N. Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions. Int. J. Food Microbiol. 2008, 127:290-297.
18. Huang L. Estimation of growth of Clostridium perfringens in cooked beef under fluctuating temperature conditions. Food Microbiol. 2003, 20:549-559.
19. Huang L. Growth kinetics of Listeria monocytogenes in broth and beef frankfurters-determination of lag phase duration and exponential growth rate under isothermal conditions. J. Food Sci. 2008, 73:235-242.
20. Hugas M. Bacteriocinogenic lactic acid bacteria for the biopreservation of meat and meat products. Meat Sci. 1998, 49:139-150.
21. Juneja V., Melendres M., Huang L., Gumudavelli V., Subbiah J., Thippareddi H. Modeling the effect of temperature on growth of Salmonella in chicken. Food Microbiol. 2007, 24:328-335.
22. Juneja V., Marks H., Huang L., Thippareddi H. Predictive model for growth of Clostridium perfringens during cooling of cooked uncured meat and poultry. Food Microbiol. 2011, 28:791-795.
23. Kreyenschmidt J., Hubner A., Beierle E., Chonsch L., Scherer A., Petersen B. Determination of the shelf life of sliced cooked ham based on the growth of lactic acid bacteria in different steps of the chain. J. Appl. Microbiol. 2010, 108:510-520.
24. Lee D., Hwang K., An D., Park J., Lee H. Model on the microbial quality change of seasoned soybean sprouts for on-line shelf life prediction. Int. J. Food Microbiol. 2007, 118:285-293.
25. Mafart P. Food engineering and predictive microbiology: on the necessity to combine biological and physical kinetics. Int. J. Food Microbiol. 2005, 100:239-251.
26. McMeekin T.A., Mellefont L.A., Ross T. Predictive microbiology: past, present and future. Modelling Microorganisms in Food 2007, 7-21. CRC Press, Boca Raton Boston New York Washington, DC. S. Brul, S. Van Gerwen, M. Zwietering (Eds.).
27. Ng H., Ingraham J.L., Marr A.G. Damage and derepression in Escherichia coli resulting from growth at low temperatures. J. Bacteriol. 1962, 84:331-339.
28. Nychas G., Skandamis P., Tassou C., Koutsoumanis K. Meat spoilage during distribution. Meat Sci. 2008, 78:77-89.
29. Pal A., Labuza T., Diez-Gonzalez F. Comparison of primary predictive models to study the growth of Listeria monocytogenes at low temperatures in liquid cultures and selection of fastest growing ribotypes in meat and turkey product slurries. Food Microbiol. 2008, 25:460-470.
30. Peleg M., Corradini M.G. Microbial growth curves: what the models tell us and what they cannot. Crit. Rev. Food Sci. Nutr. 2011, 51:917-945.
31. Ratkowsky D., Olley J., McMeekin T., Ball A. Relationship between temperature and growth-rate of bacterial cultures. J. Bacteriol. 1982, 149:1-5.
32. Ross T. Indices for performance evaluation of predictive models in food microbiology. J. Appl. Bacteriol. 1996, 81:501-508.
33. Salih M., Mytilinaios I., Schofield H.K., Lambert R.J.W. Modelling of bacterial growth with shifts in temperature using automated methods with Listeria monocytogenes and Pseudomonas aeruginosa as examples. Int. J. Food Microbiol. 2012, 155:29-35.
34. Samelis J., Kakouri A., Rementzis J. Selective effect of the product type and the packaging conditions on the species of lactic acid bacteria dominating the spoilage microbial association of cooked meats at 4 degrees C. Food Microbiol. 2000, 17:329-340.
35. Soper, H.E., Young, A.W., Cave, B.M., Lee, A., Pearson, K., 1917. On the Distribution of the Correlation Coefficient in Small Samples. Appendix II to the Papers of "Student" and R. A. Fisher. Biometrika 11: 328-413.
36. Swinnen I.A.M., Bernaerts K., Dens E., Geeraerd A., Van Impe J.F. Predictive modelling of the microbial lag phase: a review. Int. J. Food Microbiol. 2004, 94:137-159.
37. Swinnen I.A.M., Bernaerts K., Gysemans K., Van Impe J.F. Quantifying microbial lag phenomena due to a sudden rise in temperature: a systematic macroscopic study. Int. J. Food Microbiol. 2005, 100:85-96.
38. Valero A., Pérez-Rodríguez F., Carrasco E., García-Gimeno R.M., Zurera G. Modeling the growth rate of Listeria monocytogenes using absorbance measurements and calibration curves. J. Food Sci. 2006, 71:257-264.
39. Van Impe J., Nicolai B., Martens T., Debaerdemaeker J., Van de Walle J. Dynamic mathematical-model to predict microbial-growth and inactivation during food-processing. Appl. Environ. Microbiol. 1992, 58:2901-2909.
40. Van Impe J., Nicolai B., Schellekens M., Martens T., Debaerdemaeker J. Predictive microbiology in a dynamic environment-a system-theory approach. Int. J. Food Microbiol. 1995, 25:227-249.
41. Velugoti P., Bohra L., Juneja V., Huang L., Wesseling A., Subbiah J., Thippareddi H. Dynamic model for predicting growth of Salmonella spp. in ground sterile pork. Food Microbiol. 2011, 28:796-803.
42. Whiting R., Buchanan R. A classification of models in predictive microbiology-reply. Food Microbiol. 1993, 10:175-177.
43. Xanthiakos K., Simos D., Angelidis A., Nychas G., Koutsoumanis K. Dynamic modeling of Listeria monocytogenes growth in pasteurized milk. J. Appl. Microbiol. 2006, 100:1289-1298.
44. Yates G.T., Smotzer T. On the lag phase and initial decline of microbial growth curves. J. Theor. Biol. 2007, 244:511-517.
45. Zwietering M., Jongenburger I., Rombouts F., Vant Riet K. Modeling of the bacterial-growth curve. Appl. Environ. Microbiol. 1990, 56:1875-1881.
46. Zwietering M., Dewit J., Cuppers H., Vant Riet K. Modeling of bacterial-growth with shifts in temperature. Appl. Environ. Microbiol. 1994, 60:204-213.