Cheese Microbial Risk Assessments — A Review

• Published in: Animal bioscience Vol. 29; no. 3; pp. 307 - 314
• Main Authors: Choi, Kyoung-Hee, Lee, Heeyoung, Lee, Soomin, Kim, Sejeong, Yoon, Yohan
• Format: Journal Article
• Language: English
• Published: Korea (South) Asian - Australasian Association of Animal Production Societies 01.03.2016; Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST); Asian-Australasian Association of Animal Production Societies; 아세아·태평양축산학회
• Subjects: Bacterial infections; Cheese; Health aspects; Health risk assessment; Methods; Microbial Risk Assessment; Predictive Model; Risk factors; 축산학; Predictive Model; Microbial Risk Assessment; Cheese
• ISSN: 1011-2367; 2765-0189; 1976-5517; 2765-0235
• DOI: 10.5713/ajas.15.0332

Cheese is generally considered a safe and nutritious food, but foodborne illnesses linked to cheese consumption have occurred in many countries. Several microbial risk assessments related to Listeria monocytogenes, Staphylococcus aureus, and Escherichia coli infections, causing cheese-related foodborne illnesses, have been conducted. Although the assessments of microbial risk in soft and low moisture cheeses such as semi-hard and hard cheeses have been accomplished, it has been more focused on the correlations between pathogenic bacteria and soft cheese, because cheese-associated foodborne illnesses have been attributed to the consumption of soft cheeses. As a part of this microbial risk assessment, predictive models have been developed to describe the relationship between several factors (pH, Aw, starter culture, and time) and the fates of foodborne pathogens in cheese. Predictions from these studies have been used for microbial risk assessment as a part of exposure assessment. These microbial risk assessments have identified that risk increased in cheese with high moisture content, especially for raw milk cheese, but the risk can be reduced by preharvest and postharvest preventions. For accurate quantitative microbial risk assessment, more data including interventions such as curd cooking conditions (temperature and time) and ripening period should be available for predictive models developed with cheese, cheese consumption amounts and cheese intake frequency data as well as more dose-response models.