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Na S, Kim JH, Jang HJ, Park HJ, Oh SW. Shelf life extension of Pacific white shrimp (Litopenaeus vannamei) using chitosan and ε-polylysine during cold storage. Int J Biol Macromol 2018; 115:1103-1108. [DOI: 10.1016/j.ijbiomac.2018.04.180] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Revised: 03/21/2018] [Accepted: 04/30/2018] [Indexed: 11/25/2022]
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2
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Wang J, Koseki S, Chung MJ, Oh DH. A Novel Approach to Predict the Growth of Staphylococcus aureus on Rice Cake. Front Microbiol 2017; 8:1140. [PMID: 28690596 PMCID: PMC5479919 DOI: 10.3389/fmicb.2017.01140] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 06/06/2017] [Indexed: 11/25/2022] Open
Abstract
This study aimed to investigate the growth kinetics of Staphylococcus aureus on rice cake and to determine the shelf life based on the probability model of the increase in S. aureus contamination on rice cake. Secondary models were developed based on the growth parameters derived from the Baranyi model at constant temperatures (15, 25, 35, and 45°C). External validation was then conducted using additional data under experimental conditions not used in development of the models to verify the performance and reliability of the developed model through different goodness-of-fit indices. Furthermore, the growth of S. aureus on rice cake under dynamic temperature was obtained with the root mean square error (RMSE) of 0.218 and the 90.9% acceptable prediction rate. In addition, probability models of the 1-, 2-, 3-, and 4-log increases of S. aureus on rice cake were also developed from the data, which could provide the probability and the time to a certain log increase. The results of validation demonstrated that the developed predictive model and the obtained growth parameters could be used for evaluating the growth behavior of S. aureus on rice cake under different conditions, and qualified to supply sufficient information for microbiological risk assessment studies of S. aureus on rice cake in Korea.
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Affiliation(s)
- Jun Wang
- College of Food Science and Engineering, Qingdao Agricultural UniversityQingdao, China
| | - Shige Koseki
- Research Faculty of Agriculture, Hokkaido UniversitySapporo, Japan
| | - Mi-Ja Chung
- Department of Food Science and Nutrition, College of Health, Welfare and Education, Gwangju UniversityGwangju, South Korea
| | - Deog-Hwan Oh
- Department of Food Science and Biotechnology, Institute of Bioscience and Biotechnology, Kangwon National UniversityChuncheon, South Korea
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3
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Microbial contamination of tofu in Korea and growth characteristics of Bacillus cereus isolates in Tofu. Lebensm Wiss Technol 2017. [DOI: 10.1016/j.lwt.2016.11.081] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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4
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Guérin A, Dargaignaratz C, Broussolle V, Clavel T, Nguyen-the C. Combined effect of anaerobiosis, low pH and cold temperatures on the growth capacities of psychrotrophic Bacillus cereus. Food Microbiol 2016; 59:119-23. [DOI: 10.1016/j.fm.2016.05.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Revised: 05/26/2016] [Accepted: 05/27/2016] [Indexed: 11/28/2022]
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5
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Ha JH, Choi C, Lee HJ, Ju IS, Lee JS, Ha SD. Efficacy of chemical disinfectant compounds against human norovirus. Food Control 2016. [DOI: 10.1016/j.foodcont.2015.04.040] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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6
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Lobacz A, Kowalik J, Tarczynska A. Modeling the growth of Listeria monocytogenes in mold-ripened cheeses. J Dairy Sci 2013; 96:3449-60. [PMID: 23548297 DOI: 10.3168/jds.2012-5964] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2012] [Accepted: 02/18/2013] [Indexed: 11/19/2022]
Abstract
This study presents possible applications of predictive microbiology to model the safety of mold-ripened cheeses with respect to bacteria of the species Listeria monocytogenes during (1) the ripening of Camembert cheese, (2) cold storage of Camembert cheese at temperatures ranging from 3 to 15°C, and (3) cold storage of blue cheese at temperatures ranging from 3 to 15°C. The primary models used in this study, such as the Baranyi model and modified Gompertz function, were fitted to growth curves. The Baranyi model yielded the most accurate goodness of fit and the growth rates generated by this model were used for secondary modeling (Ratkowsky simple square root and polynomial models). The polynomial model more accurately predicted the influence of temperature on the growth rate, reaching the adjusted coefficients of multiple determination 0.97 and 0.92 for Camembert and blue cheese, respectively. The observed growth rates of L. monocytogenes in mold-ripened cheeses were compared with simulations run with the Pathogen Modeling Program (PMP 7.0, USDA, Wyndmoor, PA) and ComBase Predictor (Institute of Food Research, Norwich, UK). However, the latter predictions proved to be consistently overestimated and contained a significant error level. In addition, a validation process using independent data generated in dairy products from the ComBase database (www.combase.cc) was performed. In conclusion, it was found that L. monocytogenes grows much faster in Camembert than in blue cheese. Both the Baranyi and Gompertz models described this phenomenon accurately, although the Baranyi model contained a smaller error. Secondary modeling and further validation of the generated models highlighted the issue of usability and applicability of predictive models in the food processing industry by elaborating models targeted at a specific product or a group of similar products.
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Affiliation(s)
- Adriana Lobacz
- Faculty of Food Sciences, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland.
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Wang J, Rahman S, Zhao XH, Forghani F, Park MS, Oh DH. Predictive Models for the Growth Kinetics of Listeria monocytogenes
on White Cabbage. J Food Saf 2013. [DOI: 10.1111/jfs.12022] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jun Wang
- College of Life Science; Linyi University; Linyi China
- Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology; Kangwon National University; Chuncheon Gangwon 200-701 Korea
| | - S.M.E. Rahman
- Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology; Kangwon National University; Chuncheon Gangwon 200-701 Korea
| | - Xi-Hong Zhao
- Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology; Kangwon National University; Chuncheon Gangwon 200-701 Korea
| | - Fereidoun Forghani
- Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology; Kangwon National University; Chuncheon Gangwon 200-701 Korea
| | - Myoung-Su Park
- Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology; Kangwon National University; Chuncheon Gangwon 200-701 Korea
| | - Deog-Hwan Oh
- Department of Food Science and Biotechnology and Institute of Bioscience and Biotechnology; Kangwon National University; Chuncheon Gangwon 200-701 Korea
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Daelman J, Vermeulen A, Willemyns T, Ongenaert R, Jacxsens L, Uyttendaele M, Devlieghere F. Growth/no growth models for heat-treated psychrotrophic Bacillus cereus spores under cold storage. Int J Food Microbiol 2013; 161:7-15. [DOI: 10.1016/j.ijfoodmicro.2012.11.017] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2012] [Revised: 11/09/2012] [Accepted: 11/12/2012] [Indexed: 11/16/2022]
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9
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Koseki S, Nonaka J. Alternative approach to modeling bacterial lag time, using logistic regression as a function of time, temperature, pH, and sodium chloride concentration. Appl Environ Microbiol 2012; 78:6103-12. [PMID: 22729541 PMCID: PMC3416635 DOI: 10.1128/aem.01245-12] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2012] [Accepted: 06/16/2012] [Indexed: 11/20/2022] Open
Abstract
The objective of this study was to develop a probabilistic model to predict the end of lag time (λ) during the growth of Bacillus cereus vegetative cells as a function of temperature, pH, and salt concentration using logistic regression. The developed λ model was subsequently combined with a logistic differential equation to simulate bacterial numbers over time. To develop a novel model for λ, we determined whether bacterial growth had begun, i.e., whether λ had ended, at each time point during the growth kinetics. The growth of B. cereus was evaluated by optical density (OD) measurements in culture media for various pHs (5.5 ∼ 7.0) and salt concentrations (0.5 ∼ 2.0%) at static temperatures (10 ∼ 20°C). The probability of the end of λ was modeled using dichotomous judgments obtained at each OD measurement point concerning whether a significant increase had been observed. The probability of the end of λ was described as a function of time, temperature, pH, and salt concentration and showed a high goodness of fit. The λ model was validated with independent data sets of B. cereus growth in culture media and foods, indicating acceptable performance. Furthermore, the λ model, in combination with a logistic differential equation, enabled a simulation of the population of B. cereus in various foods over time at static and/or fluctuating temperatures with high accuracy. Thus, this newly developed modeling procedure enables the description of λ using observable environmental parameters without any conceptual assumptions and the simulation of bacterial numbers over time with the use of a logistic differential equation.
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Affiliation(s)
- Shige Koseki
- National Food Research Institute, Tsukuba, Ibaraki, Japan.
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10
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Modeling the combined effect of temperature and relative humidity on Escherichia coli O157:H7 on lettuce. Food Sci Biotechnol 2012. [DOI: 10.1007/s10068-012-0111-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
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11
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WANG JUN, OH DEOGHWAN. EFFECT OF TEMPERATURE AND RELATIVE HUMIDITY ON GROWTH BEHAVIOR OF ESCHERICHIA COLI O157:H7 ON SPINACH USING RESPONSE SURFACE METHODOLOGY. J Food Saf 2012. [DOI: 10.1111/j.1745-4565.2012.00380.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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12
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Kim BY, Lee JY, Ha SD. Growth characteristics and development of a predictive model for Bacillus cereus in fresh wet noodles with added ethanol and thiamine. J Food Prot 2011; 74:658-64. [PMID: 21477484 DOI: 10.4315/0362-028x.jfp-10-131] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Response surface methodology was used to determine growth characteristics and to develop a predictive model to describe specific growth rates of Bacillus cereus in wet noodles containing a combination of ethanol (0 to 2% [vol/wt]) and vitamin B(1) (0 to 2 g/liter). B. cereus F4810/72, which produces an emetic toxin, was used in this study. The noodles containing B. cereus were incubated at 10°C. The growth curves were fitted to the modified Gompertz equation using nonlinear regression, and the growth rate values from the curves were used to establish the predictive model using a response surface methodology quadratic polynomial equation as a function of concentrations of ethanol and vitamin B(1). The model was shown to fit the data very well (r(2) = 0.9505 to 0.9991) and could be used to accurately predict growth rates. The quadratic polynomial model was validated, and the predicted growth rate values were in good agreement with the experimental values. The polynomial model was found to be an appropriate secondary model for growth rate (GR) and lag time (LT) based on the correlation of determination (r(2) = 0.9899 for GR, 0.9782 for LT), bias factor (B(f) = 1.006 for GR, 0.992 for LT), and accuracy factor (A(f) = 1.024 for GR, 1.011 for LT). Thus, this model holds great promise for use in predicting the growth of B. cereus in fresh wet noodles using only the bacterial concentration, an important contribution to the manufacturing of safe products.
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Affiliation(s)
- Bo-Yeon Kim
- Department of Food Science and Technology, Chung-Ang University, Korea 72-1 Nae-ri, Daeduk-myun, Ansung, Gyunggido 456-756, Republic of Korea
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Byelashov OA, Daskalov H, Geornaras I, Kendall PA, Belk KE, Scanga JA, Smith GC, Sofos JN. Reduction of Listeria monocytogenes on frankfurters treated with lactic acid solutions of various temperatures. Food Microbiol 2010; 27:783-90. [DOI: 10.1016/j.fm.2010.04.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2010] [Revised: 04/01/2010] [Accepted: 04/06/2010] [Indexed: 10/19/2022]
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14
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Theys T, Geeraerd A, Devlieghere F, Van Impe J. On the selection of relevant environmental factors to predict microbial dynamics in solidified media. Food Microbiol 2010; 27:220-8. [DOI: 10.1016/j.fm.2009.10.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2008] [Revised: 10/02/2009] [Accepted: 10/05/2009] [Indexed: 12/01/2022]
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LEE MINJEONG, HA JIHYOUNG, HA SANGDO. SYNERGISTIC EFFECT OF VITAMIN B1ON SANITIZER AND DISINFECTANT TREATMENTS FOR REDUCTION OFBACILLUS CEREUSIN RICE. J Food Saf 2010. [DOI: 10.1111/j.1745-4565.2009.00185.x] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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16
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Muller M, Patureau D, Godon JJ, Delgenès JP, Hernandez-Raquet G. Molecular and kinetic characterization of mixed cultures degrading natural and synthetic estrogens. Appl Microbiol Biotechnol 2009; 85:691-701. [DOI: 10.1007/s00253-009-2160-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2009] [Revised: 07/20/2009] [Accepted: 07/20/2009] [Indexed: 10/20/2022]
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17
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Heo SK, Lee JY, Baek SB, Ha SD. A response surface model to describe the effect of temperature and pH on the growth of Bacillus cereus in cooked rice. J Food Prot 2009; 72:1296-300. [PMID: 19610344 DOI: 10.4315/0362-028x-72.6.1296] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
This study was performed to develop a predictive model for the growth rate of Bacillus cereus in cooked rice. A response surface methodology (RSM) was used with a combination of storage temperature (10 to 40 degrees C) and pH value (5.4 to 6.8). The growth curves generated under different conditions were fitted using a modified Gompertz equation, and the relationship of the growth rate to the growth curves was modeled using an RSM quadratic polynomial equation. The predictive model was significant (P < 0.01), and the predicted values of the growth parameters obtained using the model equations were in close agreement with experimental values (R2 = 0.9864). The RSM evaluation for describing the growth rate of B. cereus involved both a bias factor (Bf) and an accuracy factor (Af). Both the Bf value (1.006) and the Af value (1.011) approached 1.0 and were within acceptable ranges. Therefore, the adequacy of the predictive model for B. cereus in cooked rice was verified by the validation data.
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Affiliation(s)
- Sun-Kyung Heo
- Department of Food Science and Technology, Chung-Ang University, 72-1 Nae-ri, Ansung-si, Gyunggi-do 456-756, Republic of Korea
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18
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Heo SK, Lee HS, Ha SD. A predictive model for the growth rate of Bacillus cereus in broth by response surface methodology. BIOTECHNOL BIOPROC E 2009. [DOI: 10.1007/s12257-008-0187-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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