Skip to main content

Risk Assessment of Listeria spp. Contamination in the Production Line of Ready-to-Eat Chicken Meat Products

Buy Article:

$37.00 plus tax (Refund Policy)


The risk of Listeria spp. contamination was assessed in frozen ready-to-eat chicken meat production lines by establishing a mathematical model for determining the probability of Listeria spp. prevalence on environmental surfaces directly in contact with the product at various times in a chicken plant in Thailand. Environmental surfaces were divided into three zones. Zone 1 included surfaces in direct contact with products. Both zones 2 and 3 included indirect contact surfaces; zone 2 was next to zone 1, and zone 3 was next to zone 2, relatively far from the product. The model for probability of Listeria spp. contamination on surfaces in zone 1 was derived from the probability of Listeria spp. on surfaces in zone 1 after the cleaning and sanitizing process multiplied by the probability of Listeria spp. transferred from zones 2 and 3 and the probability of Listeria spp. growth. The surfaces in zone 1 were cleaned with warm water, cleaned with detergent, and sanitized with a sanitizer. Factors affecting cleaning and sanitizing were water temperature, concentration, and contact time of detergent and sanitizer. The probability of Listeria spp. prevalence on surfaces in zone 1 was not affected by water temperatures of 50, 60, and 70°C and detergent concentrations of 0.5, 1, and 2% (vol/vol) at contact times of 5, 10, and 15 min. However, it was affected by sanitizer concentrations of 0.25, 0.5, and 1.25% (vol/vol) at contact times of 5, 10, and 20 min. Sensitivity analyses were conducted using the Monte Carlo simulation. The sanitizer concentration had the most significant influence on the prevalence of Listeria spp. on surfaces in zone 1. The prevalence of Listeria spp. on surfaces after cleaning and sanitizing, the production time, and the contact time with the sanitizer were highly correlated with the prevalence of Listeria spp. in zone 1. This model could be used as a management tool for assessing the risk of Listeria spp. contamination in food products.

Document Type: Research Article

Affiliations: Department of Food Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand

Publication date: May 1, 2008

More about this publication?
  • IAFP Members with personal subscriptions to JFP Online: To access full-text JFP or JMFT articles, you must sign-in in the upper-right corner using your Ingenta sign-in details (your IAFP Member Login does not apply to this website).

    The Journal of Food Protection (JFP) is a refereed monthly publication. Each issue contains scientific research and authoritative review articles reporting on a variety of topics in food science pertaining to food safety and quality. The Journal is internationally recognized as the leading publication in the field of food microbiology with a readership exceeding 11,000 scientists from 70 countries. The Journal of Food Protection is indexed in Index Medicus, Current Contents, BIOSIS, PubMed, Medline, and many others.

    Print and online subscriptions are available to IAFP Members and institutional subscribers. IAFP Members with a subscription to JFP Online will have access to all available JFP and JMFT content. Online visitors who are not IAFP Members or journal subscribers will be charged on a pay-per-view basis. Membership and subscription information is available at
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Membership Information
  • Information for Advertisers
  • Ingenta Connect is not responsible for the content or availability of external websites

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Partial Open Access Content
Partial Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more