Use of <scp>ComBase</scp> data to develop an artificial neural network model for nonthermal inactivation of <scp> <i>Campylobacter jejuni</i> </scp> in milk and beef and evaluation of model performance and data completeness using the acceptable prediction zones method-Reference-Cited by-同舟云学术

Use of ComBase data to develop an artificial neural network model for nonthermal inactivation of Campylobacter jejuni in milk and beef and evaluation of model performance and data completeness using the acceptable prediction zones method

Published:2022-05-04 Issue:4 Volume:42 Page:
ISSN:0149-6085
Container-title:Journal of Food Safety
language:en
Short-container-title:Journal of Food Safety

Author:

Boleratz Bethany L.¹,Oscar Thomas P.¹^ORCID

Affiliation:

1. US Department of Agriculture, Agricultural Research Service, Chemical Residue and Predictive Microbiology Research Unit, Center for Food Science and Technology University of Maryland Eastern Shore Princess Anne Maryland USA

Funder

Agricultural Research Service

Publisher

Wiley

Subject

Microbiology,Food Science,Parasitology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfs.12983

Reference68 articles.

1. Effect of Oxygen Stress on Growth and Survival of Clostridium perfringens, Campylobacter jejuni, and Listeria monocytogenes under Different Storage Conditions

2. ComBase: A Common Database on Microbial Responses to Food Environments†

3. Ranking the Disease Burden of 14 Pathogens in Food Sources in the United States Using Attribution Data from Outbreak Investigations and Expert Elicitation†

4. Response Surface Model for Predicting the Effects of Temperature pH, Sodium Chloride Content, Sodium Nitrite Concentration and Atmosphere on the Growth of Listeria monocytogenes

5. Comparison of growth and survival kinetics of Salmonella typhimurium and Campylobacter jejuni on cooked chicken breast stored under aerobic conditions at various temperatures;Burnette C. N.;Food Science and Biotechnology,2004

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