Influence of season and type of restaurants on sashimi microbiota

Eur J Public Health. 2016 Oct;26(5):877-881. doi: 10.1093/eurpub/ckw009. Epub 2016 Feb 24.

Abstract

Background: In recent years, an increase in the consumption of Japanese food in European countries has been verified, including in Portugal. These specialities made with raw fish, typical Japanese meals, have been prepared in typical and on non-typical restaurants, and represent a challenge to risk analysis on HACCP plans. The aim of this study was to evaluate the influence of the type of restaurant, season and type of fish used on sashimi microbiota.

Methods: Sashimi samples (n = 114) were directly collected from 23 sushi restaurants and were classified as Winter and Summer Samples. They were also categorized according to the type of restaurant where they were obtained: as typical or non-typical. The samples were processed using international standards procedures.

Results: A middling seasonality influence was observed in microbiota using mesophilic aerobic bacteria, psychrotrophic microorganisms, Lactic acid bacteria, Pseudomonas spp., H2S positive bacteria, mould and Bacillus cereus counts parameters. During the Summer Season, samples classified as unacceptable or potentially Hazardous were observed. Non-typical restaurants had the most cases of Unacceptable/potentially hazardous samples 83.33%. These unacceptable results were obtained as a result of high values of pathogenic bacteria like Listeria monocytogenes and Staphylococcus aureus No significant differences were observed on microbiota counts from different fish species.

Conclusion: The need to implement more accurate food safety systems was quite evident, especially in the warmer season, as well as in restaurants where other kinds of food, apart from Japanese meals, was prepared.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Fishes / microbiology*
  • Food Contamination / statistics & numerical data*
  • Humans
  • Microbiota*
  • Portugal
  • Raw Foods / microbiology*
  • Raw Foods / statistics & numerical data*
  • Restaurants / statistics & numerical data*
  • Seasons*