• Journal of Food Hygiene and Safety
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• v.12 no.4
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• pp.346-353
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• 1997

This study was undertaken to find out distribution and contamination sources of hazardous microbes through microbial hazard analysis on the processing steps of surimi-based imitation crab (SBIC). As a results of ananlysis of 9 hazardous microbes for 16 raw materials and 8 processing steps, no Samonella spp. and Escherichia coli were detected in all samples. Level and distribution of hazardous microbes in mixed color were similar to those of surimi. Changes of aerobic plate counts (APC), psychrotropic bacteria, coliforms, Staphylococcus aureus and Vibrio parahaemolyticus showed similar trends at different processing steps. Thermotrophic bacteria and aerobic sporeformers were not detected until mixing step and feeding step, respectively and not reduced after cooking step. According to the comparison of APC at each step, it was suggested that surimi, workers and silent cutter at mixing step, and mixed color, workers and bundler at packaging step were the major contamination sources of bacteria.

• Journal of Food Hygiene and Safety
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• v.12 no.4
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• pp.340-345
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• 1997

This study was undertaken to evaluate microbial risk degree of some processed foods in Korea. In this study the data on the outbreak of foodborne diseases during recent 18 years (1976-1989, 1993-1996. 8) were analyzed. The most frequently isolated pathogens were Salmonella (36.9%); followed vibrio (22.0%), Staphylococcus (15.7%) and Escherichia coli (13.3%). Outbreak rate of Staphylococcus, Vibrio, E. coli and Salmonella, was 33.0%, 23.5%, 17.5% and 17.1%, respectively. Overall risk degree of pathogens by fatality rate, outbreak rate and pathogen amount for foodborne outbreak was Clostridium, 5, Staphylococcus and Vibrio, 4, Salmonella and E. coli, 3. Based on foodborne pathogens, the risk degree of raw seafoods, raw eggs and processed seafoods were 4, and those of raw meats, Doshiraks and milk products were 3. Also, based on processing characteristics of foods, the risk degree of surimi-based imitation crab was 3. Foods of the highest actual risk degree were raw seafoods and raw eggs (16); followed raw meats (15), surimi-based imitation crab (12), Doshirak (9) and milk products (6).

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1012-1017
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• 2005

Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.

• Korean Journal of Food Science and Technology
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• v.37 no.2
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• pp.194-198
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• 2005

Growth curves of Listeria monocytogenes in modified surimi-based imitation crab (MIC) broth were obtained by measuring cell concentration in MIC broth at different culture conditions [initial cell numbers, $1.0{\times}10^{2},\;1.0{\times}10^{3}\;and\;1.0{\times}10^{4}$, colony forming unit (CFU)/mL; temperature, 15, 20, 25, 37, and $40^{\circ}C$] and applied to Gompertz model to determine microbial growth indicators, maximum specific growth rate constant (k), lag time (LT), and generation time (GT). Maximum specific growth rate of L. monocytogenes increased rapidly with increasing temperature and reached maximum at $37^{\circ}C$, whereas LT and GT decreased with increasing temperature and reached minimum at $37^{\circ}C$. Initial cell number had no effect on k, LT, and GT (p > 0.05). Polynomial and square root models were developed to express combined effects of temperature and initial cell number using Gauss-Newton Algorism. Relative coefficients of experimental k and predicted k of polynomial and square root models were 0.92 and 0.95, respectively, based on response surface model. Results indicate L. monocytogenes growth was mainly affected by temperature and square root model was more effective than polynomial model for growth prediction.

• Korean Journal of Food Science and Technology
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• v.36 no.2
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• pp.349-354
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• 2004

Predictive growth model of Vibrio parahaemolyticus in modified surimi-based imitation crab broth was investigated. Growth curves of V. parahaemolyticus were obtained by measuring cell concentration in culture broth under different conditions ($Initial\;cell\;level,\;1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}\;colony\;forming\;unit\;(CFU)/mL$; temperature, 15, 25 37, and $40^{\circ}C$; pH 6, 7, and 8) and applying them to Gompertz model. Microbial growth indicators, maximum specific growth rate (k), lag time (LT), and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of V. parahaemolyticus increased with increasing temperature, reaching maximum rate at $37^{\circ}C$. LT and GT were also the shortest at $37^{\circ}C$. pH and initial cell number did not influence k, LT, and GT values significantly (p>0.05). Polynomial model, $k=a{\cdot}\exp(-0.5{\cdot}((T-T_{max}/b)^{2}+((pH-pH_{max)/c^{2}))$, and square root model, ${\sqrt{k}\;0.06(T-9.55)[1-\exp(0.07(T-49.98))]$, were developed to express combination effects of temperature and pH under each initial cell number using Gauss-Newton Algorism of Sigma plot 7.0 (SPSS Inc.). Relative coefficients between experimental k and k Predicted by polynomial model were 0.966, 0.979, and 0.965, respectively, at initial cell numbers of $1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}CFU/mL$, while that between experimental k and k Predicted by square root model was 0.977. Results revealed growth of V. parahaemolyticus was mainly affected by temperature, and square root model showing effect of temperature was more credible than polynomial model for prediction of V. parahaemolyticus growth.