Contamination of Clostridium perfringens in soy sauce, and quantitative microbial risk assessment for C. perfringens through soy sauce consumption

Yeongeun Seo, Yewon Lee, Sejeong Kim, Jimyeong Ha, Yukyung Choi, Hyemin Oh, Yujin Kim, Min Suk Rhee, Yohan Yoon

Research output: Contribution to journalArticlepeer-review

Abstract

The objective of this study was to conduct QMRA (quantitative microbial risk assessment) of Clostridium perfringens through soy sauce consumption. Four hundred and ninety soy sauce samples from markets were analyzed to detect C. perfringens. Temperature and time were also measured during transportation and display of soy sauce. A primary model was developed by fitting the Weibull model to the C. perfringens cell counts in soy sauce at 7–35°C, and δ (the time needed to decrease 1 log CFU/ml) and ρ (curve shape) were calculated. The parameters were analyzed, using the Exponential model (secondary model) as a function of temperature. The consumption amount and percentage of soy sauce were surveyed, and a dose-response model was searched. Using all collected data, a simulation model was prepared in the @RISK program to estimate the probability of C. perfringens foodborne illness by soy sauce consumption. C. perfringens were negative in 490 samples. Thus, the initial contamination level was estimated to be −2.9 log CFU/ml. The developed predictive models showed that C. perfringens cell counts decreased during transportation and display. The average consumption amounts, and the percentage of soy sauce were 7.81 ml and 81.2%, respectively. The simulation showed that the probability of C. perfringens foodborne illness by consumption of soy sauce was 1.7 × 10–16 per person per day. Therefore, the risk of C. perfringens by consumption of soy sauce is low in Korea.

Original languageEnglish
Pages (from-to)2139-2146
Number of pages8
JournalFood Science and Nutrition
Volume9
Issue number4
DOIs
Publication statusPublished - 2021 Apr

Keywords

  • @risk
  • Clostridium perfringens
  • dose-response
  • predictive model
  • quantitative microbial risk assessment
  • soy sauce

ASJC Scopus subject areas

  • Food Science

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