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Detection of Listeria Species by Conventional Culture-Dependent and Alternative Rapid Detection Methods in Retail Ready-to-Eat Foods in Turkey

  • Emine Dincer (Faculty of Health Sciences, Department of Nutrition and Dietetics, Sivas Cumhuriyet University)
  • Received : 2023.08.24
  • Accepted : 2023.10.30
  • Published : 2024.02.28

Abstract

Foodborne pathogens, like Listeria monocytogenes, continue to inflict substantial financial losses on the food industry. Various methods for detecting Listeria in food have been developed and numerous studies have been conducted to compare the different methods. But, in recent years, new Listeria species have been identified, and currently the genus comprises 26 species. Therefore, it would be a more accurate approach to re-evaluate existing detection methods by considering new species. The present investigation involved the analysis of 42 ready-to-eat (RTE) foods, encompassing a variety of food categories, such as mezes, salads, dairy products, and meat products, with the aim of ascertaining the presence of Listeria. Among the traditional culture-dependent reference methods, the ISO 11290 method was preferred. The process of strain identification was conducted with the API Identification System. Furthermore, to ascertain the existence of L. monocytogenes and Listeria spp., the samples underwent additional analysis employing the VIDAS Immunoassay System, ELISA, and RT-PCR methodologies. Thus, four alternative approaches were employed in this study to compare not only the different methods used to determine Listeria while taking into account the newly identified Listeria species, but also to assess the compliance of retail RTE food items with microbiological criteria pertaining to the genus Listeria. Based on the conducted analyses, L. monocytogenes was conclusively determined to be present in one sample. The presence of Listeria spp. was detected in 30.9% of the samples, specifically in Turkish cig kofte, sliced salami, and salads.

Keywords

Acknowledgement

E. Dincer especially thanks Prof. Dr. Merih Kivanc for making her laboratory available.

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