Quantitative Microbial Risk Assessment For Campylobacter Jejuni And C. Coli Associated With The Consumption Of Camel Milk Qatar

2014 ◽  
Author(s):  
Hussni Omar Mohammed ◽  
Kenlyn Peters ◽  
Ahmed Salem ◽  
Sanjay Doiphode ◽  
Ali Sultan
Keyword(s):  
Risk Assessment ◽  
Campylobacter Jejuni ◽  
Camel Milk ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk

scholarly journals Quantitative Microbial Risk Assessment for Campylobacter jejuni in Ground Meat Products in Korea

2019 ◽  
Vol 39 (4) ◽  
pp. 565-575 ◽  
Author(s):  
Jeeyeon Lee ◽  
Heeyoung Lee ◽  
Soomin Lee ◽  
Sejeong Kim ◽  
Jimyeong Ha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Campylobacter Jejuni ◽  
Meat Products ◽  
Quantitative Microbial Risk Assessment ◽  
Ground Meat ◽  
Microbial Risk Assessment ◽  
Microbial Risk

scholarly journals Evaluation of strain variability in inactivation of Campylobacter jejuni in simulated gastric fluid by using hierarchical Bayesian modeling

2021 ◽  
Author(s):  
Kento Koyama ◽  
Jukka Ranta ◽  
Kohei Takeoka ◽  
Hiroki Abe ◽  
Shige Koseki
Keyword(s):  
Risk Assessment ◽  
Campylobacter Jejuni ◽  
Gastric Fluid ◽  
Simulated Gastric Fluid ◽  
Model Parameters ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Different Strains ◽  
Strain Variability

This study was conducted to quantitatively evaluate the variability of stress resistance in different strains of Campylobacter jejuni and the uncertainty of such strain variability. We developed Bayesian statistical models with multilevel analysis to quantify variability within a strain and variability between different strains and the uncertainty associated with these estimates. Furthermore, we measured the inactivation of 11 strains of C. jejuni in simulated gastric fluid with low pH, using the Weibullian survival model. The model was first developed for separate pH conditions, and then analyzed over a range of pH levels. We found that the model parameters developed under separate pH conditions exhibited clear dependence of survival on pH. In addition, the uncertainty of the variability between different strains could be described as the joint distribution of the model parameters. The latter model, including pH dependency, accurately predicted the number of surviving cells in individual as well as multiple strains. In conclusion, variabilities and uncertainties in inactivation could be simultaneously evaluated and interpreted via a probabilistic approach based on Bayesian theory. Such hierarchical Bayesian models could be useful for understanding individual strain variability in quantitative microbial risk assessment. Importance Since microbial strains vary in their growth and activation patterns in food materials, it is important to accurately predict these patterns for quantitative microbial risk assessment. However, most previous studies in this area have used highly resistant strains, which could lead to inaccurate predictions. Moreover, Variability including measurement errors and variability within a strain and between different strains, can contribute to predicted individual-level outcomes. Therefore, a multilevel framework is required to resolve these levels of variability and estimate their uncertainties. We developed a Bayesian predictive model for the survival of Campylobacter jejuni in simulated gastric conditions taking into account the variabilities and uncertainties. We demonstrated a high correspondence between predictions from the model and empirical measurements. The modeling procedure proposed in this study recommends a novel framework for predicting pathogen behavior, which can help improve quantitative microbial risk assessment during food production and distribution.

scholarly journals Quantitative microbial risk assessment of Campylobacter jejuni in jerky in Korea

2019 ◽  
Vol 32 (2) ◽  
pp. 274-281 ◽  
Author(s):  
Jimyeong Ha ◽  
Heeyoung Lee ◽  
Sejeong Kim ◽  
Jeeyeon Lee ◽  
Soomin Lee ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Campylobacter Jejuni ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk

Enteric virus presence in green vegetables and associated irrigation waters in a rural area from Argentina. A quantitative microbial risk assessment

LWT ◽  
2021 ◽  
Vol 144 ◽  
pp. 111201 ◽  
Author(s):  
Prez Verónica Emilse ◽  
Victoria Matías ◽  
Martínez Laura Cecilia ◽  
Giordano Miguel Oscar ◽  
Masachessi Gisela ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Rural Area ◽  
Enteric Virus ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Irrigation Waters
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