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Modelling-based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)1389-1401
Number of pages13
JournalJournal of Applied Microbiology
Issue number5
Early online date22 Mar 2017
DateAccepted/In press - 30 Jan 2017
DateE-pub ahead of print - 22 Mar 2017
DatePublished (current) - May 2017


Aims. To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses.

Methods and Results. Numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information that described farm layouts, farming conditions for individual flocks, the slaughterhouse layouts and operating conditions inside plants was collected, matched with each Campylobacter test result. Statistical models predicting the numbers of campylobacters on neck skins and in litter were constructed. Carcass microbial contamination was more strongly influenced by on farm production practices compared with slaughterhouse activities. We observed correlations between the chilling, washing and de-feathering stages of processing and numbers of campylobacters on carcasses. There were factors on farm that also correlated with numbers of campylobacters in litter. These included bird gender, the exclusion of dogs from houses, beetle presence in the house litter and the materials used to construct the house frame.

Conclusions. Changes to farming practices have greater potential for reducing chicken carcass microbial contamination compared with processing interventions.

Significance and impact of the study. Routine commercial practices were identified that were correlated with lowered numbers of campylobacters. Consequently, these practices are likely to be both cost-effective and suitable for adoption into established farms and commercial processing.

    Research areas

  • campylobacters, microbial contamination, modelling, processing



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