T8-05 Accurate Quantification of Campylobacter Contamination on Chicken Carcasses Including Variability and Uncertainty

Friday, 31 March 2017: 09:30
314-316 (The Square)
Benjamin Duqué, UMR1014 SECALIM, INRA, Oniris, Nantes, France
Samuel Daviaud, UMR1014 SECALIM, INRA, Oniris, Nantes, France
Sandrine Guillou, Oniris, Nantes, France
Nabila Haddad, UMR1014 SECALIM, INRA, Oniris, Nantes, France
Jeanne-Marie Membré, UMR1014 SECALIM, INRA, Oniris, Nantes, France
Introduction:  Campylobacter is a foodborne pathogen, highly prevalent in poultry, and the primary cause of enteritis in humans. In this context, a project between academics and industrials was set up to evaluate, accurately, the level of contamination at different steps of process in different slaughterhouses.

Purpose:  The purpose of this study was to evaluate, accurately, the contamination level of Campylobacter spp. on chicken carcasses.

Methods: From a large dataset with censored data (concentration less than 10 CFU/g), several factors were considered; including, the month of sampling, the age of chickens (<50 days vs >50 days), the farming method (standard vs quality label), and the sampling area (neck vs leg). First, data were fitted by different distributions considering uncertainty and variability, separately. Then, the effect of factors was assessed taking the uncertainty into account. All analyses were performed in R.

Results:  Among factors studied, only those associated with the sampling period and area were shown to significantly affect the contamination level of Campylobacter spp. Thereby, two distributions of contamination levels were obtained per season (cold vs warm) and per sampling area. During the warm season, the mean contamination level was 2.6 (2.4; 2.8) log CFU/g and 1.8 (1.5; 2.0) log CFU/g for neck and leg, respectively. In contrast, during the cold season, the contamination level was 1.0 (0.6; 1.3) log CFU/g and 0.6 (0.3; 0.9) log CFU/g for neck and leg, respectively. Uncertainty was small (ca. 0.5 log) in comparison to variability (3 log or more), showing an accurate quantification of contamination, even with censored data.

Significance:  An accurate quantification of contamination level could enable industrials to better adapt their processing and hygiene practices. These results will help in refining exposure assessment models.