Cheese Microbial Risk Assessments - A Reviewopen access
- Authors
- Choi, Kyoung-Hee; Lee, Heeyoung; Lee, Soomin; Kim, Sejeong; Yoon, Yohan
- Issue Date
- Mar-2016
- Publisher
- ASIAN-AUSTRALASIAN ASSOC ANIMAL PRODUCTION SOC
- Keywords
- Predictive Model; Cheese; Microbial Risk Assessment
- Citation
- ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES, v.29, no.3, pp 307 - 314
- Pages
- 8
- Journal Title
- ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
- Volume
- 29
- Number
- 3
- Start Page
- 307
- End Page
- 314
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/9888
- DOI
- 10.5713/ajas.15.0332
- ISSN
- 1011-2367
1976-5517
- Abstract
- Cheese is generally considered a safe and nutritious food, but foodbome 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 foodbome 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.
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