E. fergusonii , a member of the genus Escherichia , has been reported to transmit via the food chain and cause diseases in humans. However, the prevalence of multidrug-resistant E. fergusonii , especially mcr-1 -positive E. fergusonii isolates, has rarely been reported.

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A quite simple, sensitive and visual detection method was developed for in situ detection of V. parahaemolyticus within only 1 hour.

The study was to establish a predictive model for reduction and cross-contamination of Salmonella on chicken in chilling process. Reduction of Salmonella on chicken was 0.75 ± 0.04, 0.74 ± 0.08, and 0.79 ± 0.07 log CFU/g with 20, 50, and 100 mg/L of chlorine, respectively. No significant differences of bacterial reductions with 20–100 mg/L of chlorine were found and a Normal (−0.75, 0.1) distribution could describe the uncertainty of bacterial reductions. Inoculated and non-inoculated chicken samples were washed together and bacterial transfer rates among them were 0.13%–0.004% with 20–100 mg/L of chlorine. No significant differences of transfer rates with 50–100 mg/L of chlorine were observed and a Triangle (−2.5, −1.5, −1.1) distribution could describe the log transfer rate. Additionally, a 3-factor response surface model based on the central composite design was developed to evaluate the effects of initial contamination level (1–5 log CFU/g), pre-chill incidence (3%–40%) and chlorine concentration (0–100 mg/L) on post-chill incidence. The post-chill incidences in these treatments were within 30%–91.7%. The developed model showed a satisfactory performance to predict the post-chill incidence as evidenced by statistical indices (pseudo-R2 = 0.9; p < 0.0001; RMSE = 0.21) and external validation parameters (Bf = 1.02; Af = 1.11).

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Chlorine disinfectants have been widely used in the poultry supply chain but this exposure can also result in the development of bacterial tolerance to chlorine and this is often linked to antibiotic cross-resistance. The objectives of this study were to investigate sodium hypochlorite (NaClO) tolerance of Salmonella isolated from poultry supply chains and evaluate cross-resistance. We collected 172 Salmonella isolates from poultry farms, slaughter houses and retail markets in China during 2019–2020. We found that S. Enteritidis, S. Kentucky, and S. Typhimurium constituted &gt; 80% of our Salmonella isolates. Overall, 68% of Salmonella isolates were resistant to &gt; 3 antibiotics and S. Kentucky displayed a significantly (p &gt; 0.05) higher frequency (93.2%) of multidrug resistance than the other serovars. Tolerance to chlorine at MIC &gt; 256 mg/L was detected in 93.6% of isolates (161/172) and tolerant isolates displayed higher decimal reduction times (D value) and less ultrastructural damage than did the suspectable strains under chlorine stress. Spearman analysis indicated significant positive correlations between chlorine tolerance (evaluated by the OD method) and antibiotic resistance (p &lt; 0.05) to ceftiofur, tetracycline, ciprofloxacin and florfenicol and this was most likely due to efflux pump over-expression. The most frequently detected chlorine resistance gene was qacEΔ1 (83.1%, n = 143) and we found a positive correlation between its presence and MIC levels (r = 0.66, p &lt; 0.0001). Besides, we found weak correlations between chlorine-tolerance and antibiotic resistance genes. Our study indicated that chlorine disinfectants most likely played an important role in the emergence of chlorine tolerance and spread of antibiotic resistance and therefore does not completely control the risk of food-borne disease. The issue of disinfectant resistance should be examined in more detail at the level of the poultry production chain.

This study evaluated the effects of early intervention with Clostridium butyricum (C. butyricum) on shaping the intestinal microbiota of Muscovy ducklings. A total of 160 1-day-old male ducks were randomly divided into two groups: the CB group was administered with 1 mL of C. butyricum (2 × 109 CFU/mL), while the C group was given 1 mL of saline. The administration lasted for 3 days. We found that C. butyricum had no significant effect on growth performance. The results indicated that inoculation with C. butyricum could significantly increase the abundance of genera Bacteroides, Lachnospiraceae_uncultured, and Ruminococcaceae on Day 14 and reduce the abundance of Escherichia–Shigella and Klebsiella on Days 1 and 3. Moreover, the CB group ducks had higher concentrations of acetic, propionic, and butyrate in the cecum than the C group. Overall, these results suggest that early intervention with C. butyricum could have positive effects on Muscovy ducks’ intestinal health, which might be attributed to the modulation in the intestinal microbial composition and the increased concentrations of short-chain fatty acids (SCFAs). C. butyricum might even have the potential to help the colonization of beneficial bacteria in the intestine microbiota in Muscovy ducks in poultry and other livestock.

The objective of this study was to develop predictive models for describing the inoculated Salmonella reductions on chicken during the scalding process in China. Salmonella reductions on chicken breasts at a 100 s treatment were 1.12 ± 0.07, 1.38 ± 0.01, and 2.17 ± 0.11 log CFU/g at scalding temperatures of 50, 60 and 70 °C, respectively. For chicken wingettes, 0.87 ± 0.02, 0.99 ± 0.14 and 1.11 ± 0.17 log CFU/g reductions were obtained at 50, 60 and 70 °C after the 100 s treatment, respectively. Greater bacterial reductions were observed on chicken breasts than on chicken wingettes (p < 0.05). A logistic (−1.12, 0.06) distribution could describe the bacterial reductions on chicken breasts at 50–60 °C. Weibull, exponential and log-linear models were compared for describing the bacterial reduction on chicken breasts at 70 °C and the Weibull model showed the best fit as indicated by the pseudo-R2, root mean square error (RMSE) and standard error of prediction (SEP) values. For chicken wingettes, a logistic (−0.95, 0.07) distribution could be used to describe the bacterial reduction at 50–70 °C. The developed predictive models could provide parts of the input data for microbial risk assessment of the poultry supply chain in China.