An epifluorescence-based technique accelerates risk assessment of aggregated bacterial communities in carcass and environment.
ENVIRONMENTAL POLLUTION(2020)
Abstract
The severe and pervasive effects of multispecies foodborne microbial biofilms highlight the importance of rapid detection and diagnosis of contamination risk in the field using epifluorescence-based techniques (EBT) combined with automatic image-counting software. This study screened the hygiene quality of the environment, the carcass and the slaughtering equipment in the El-Kharga abattoir, New Valley Province, Egypt, to assess possible contamination during slaughter process. In addition, biofilm was assessed, and bacteria was enumerated by epifluorescence microscopy. Using both conventional and EBT, the highest bacterial counts were observed for the slaughtering equipment (6.6 and 5.2 cfu/cm2, respectively), followed by different parts of the carcass (4.1 and 4.4 cfu/cm2, respectively) and environmental samples (3.9 and 4.1 cfu/cm2, respectively). A high prevalence of E. coli O157:H7 was observed on the slaughtering equipment (25%), which also led to carcass (1%) contamination. Moreover, Enterobacteriaceae members were detected during examination, such as Klebsiella pneumoniae, Enterobacter aerogenes, and Raoultella ornithinolytica. Despite the relatively good hygiene quality of the abattoir environment, there is also a high risk associated with biofilm formation by pathogenic microorganisms on the slaughtering equipment. Moreover, EBT showed different structures of the biofilm, including those formed at different maturation stages, such as voids, microbubbles, channels and mushroom shapes. (EBT) microscopy combined with image-counting software could be a candidate substitute to estimate efficiently, precisely and rapidly the microbial aggregation and exposure risk in field than the conventional counting techniques. (C) 2020 Elsevier Ltd. All rights reserved.
MoreTranslated text
Key words
BioFilm Analyzer software,Total viable counts,Epiflourescent bacterial counts,E. coli O157:H7,Enterobacteriaceae
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined