Statistical Modelling of Cold-Smoked Salmon Temperature Profiles for Risk Assessment of Listeria Monocytogenes

Afchain, Anne-Laure; Derens, Evelyne; Guilpart, J.; Cornu, Marie

doi:10.17660/actahortic.2005.674.47

Cited by 20 publications

(18 citation statements)

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“…Refrigerators containing dairy products showed DT values within the range observed by Likar and Jev snik (2006), and lower by at least 1 C to values obtained by Koutsoumanis et al (2010). The greatest differences were observed in the group of fishery products, with DT values about 4 C lower than those obtained by Afchain et al (2005).…”

Section: Resultsmentioning

confidence: 52%

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Effectiveness of the cold chain control procedure in the retail sector in Southern Spain

et al. 2016

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Section: Resultsmentioning

confidence: 52%

“…It is well known that the early stages of the cold chain (processing and distribution) are, in most cases, successfully controlled (Afchain, Derens, Guilpart, & Cornu, 2005). However, the retail level appears to be one of the weakest points where more temperature abuses have been observed (Derens, Palagos, & Guilpart, 2006;EFSA, 2007).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of the cold chain control procedure in the retail sector in Southern Spain

et al. 2016

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“…(FDA, 2011;ICMSF, 1996;IFT, 2003;NACMCF, 2010) Temperature is one the most important factors affecting growth of pathogens and thus safety of refrigerated composite products. Available data show that the first steps of the logistic chain are in most cases satisfactorily controlled (Afchain et al, 2005). In contrast, conditions at the retail level are out of manufacturers" direct control and often deviate from legislated temperature limits.…”

Section: Factors Impacting On Risks In Composite Productsmentioning

confidence: 99%

Scientific Opinion on Public health risks represented by certain composite products containing food of animal origin

Cerf¹,

Koutsoumanis²,

Nguyen-Thé³

et al. 2012

EFSA Journal

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This Opinion reviews the factors that affect microbial survival and growth in composite products, and in foods in general. It concludes that the main factors to be considered are: water activity, pH, temperature and duration of storage, processing, and intensity and duration of other non-thermal physical processes applied. Prevalence and concentration of the pathogens in food are important to determine the risk for consumers. The opinion presents a review of the quantitative microbiology models and databases that can be used to provide quantitative estimations of the impact of the above factors on the survival and growth of the main bacterial pathogens. In composite products, migration and diffusion of moisture and substances among the ingredients may change their physico-chemical parameters, particularly at the interfaces. Therefore, the assessment of the risk posed by composite products needs to consider the combinations of parameters most permissive to survival and growth of pathogens. Two complementary approaches are proposed for the identification and profiling of microbiological hazards in different specific composite products. The first one is based on past outbreaks and prevalence of hazards in the products and leads to the conclusion that the most frequent hazard-composite product combinations are Salmonella in cakes and bakery products. The second one consists in decision tools based on the impact on the pathogens of food composition and food processing. Categorisation of the risk for composite products requires information on their composition, processing and further handling, which can largely differ for foods belonging to the same category. Further conditions may influence the risk and should be verified, i.e. hygienic conditions during preparation of the composite products and their ingredients, shelf-life conditions, and reliability of cooking by consumers to inactivate pathogens. The decision tools developed apply to all composite products considered by the mandate, as well as to all other foods. © European Food Safety Authority, 2012 KEY WORDSComposite product, food-borne pathogens. SUMMARYFollowing a request from the European Commission, the Panel on Biological Hazards (BIOHAZ) was asked to deliver a Scientific Opinion on public health risks represented by certain composite products containing food of animal origin.Currently, imports into the EU of composite products are subject to specific rules in relation to both public health and animal health aspects. Some derogations currently apply to those rules, and there is a need for the European Commission to develop harmonised risk-based public health rules for import of those composite products for which controls are not currently prescribed. Therefore, the European Commission requested EFSA to recommend/identify physico-chemical parameters for certain composite products containing no meat and/or less than 50% of products of animal origin that could be relevant for the growth/survival of pathogenic microorganisms of public health importan...

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“…Then, Gimenez and Dalgaard [20] developed a model based on the cooked meat model of Devlieghere et al [21], but incorporating the effect of smoke components. Afchain et al [22] developed a statistical model of the effect of dynamic temperature on growth of L. monocytogenes in CSS that took account of a w and pH. About the same time, Augustin et al [23] evaluated models for their ability to describe the behaviour of L. monocytogenes in seafood products.…”

Section: Growth Of Listeria Monocytogenes In Lightly Preserved Seafoodmentioning

confidence: 99%

Using Predictive Models for the Shelf‐Life and Safety of Seafood

Fletcher

2010

Handbook of Seafood Quality, Safety and Health Applications

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In terms of quality, the seafood industry needs to know what their products will look, smell, and taste like when it is consumed next week in the case of a chilled product, or next year in the case of a frozen product. With regard to microbial safety, the seafood industry needs to not only know that its products are safe now but will be safe next week when their customers eat them. However, because tests take time to complete, microbiologists can only confirm that a product was safe a few hours, or more often, a few days ago. For the seafood industry, predicting the future is not an optional feature. It is an essential for doing business. It is this need that predictive modelling of seafood shelf-life and safety is designed to address.Although great progress has been made in the science and mathematics of predictive food modelling over the last four decades, it is beyond the scope of this chapter to review all of this. Books have been written on this subject [1-3] and international conferences [4] provide effective reviews of advances in the area. This chapter highlights predictive models that have been developed specifically for seafood.Two main types of models are usually used in predictive modelling.1) Primary models indicate the effect of time on a particular attribute (e.g. bacterial number) under particular constant processing or storage conditions (e.g. 0 • C storage). 2) Secondary models indicate how parameters derived from the primary model (e.g. the bacterial growth rate) change in response to the product being held under different constant processing or storage conditions (e.g. temperatures between -5 and 20 • C).A number of predictive models for food have been incorporated into software packages (socalled tertiary models). The user can input their product and environmental parameters and obtain predictions of microbial numbers or product quality at selected times. Dalgaard [5,6] has produced and made freely available an invaluable piece of software for predicting seafood safety and spoilage under various conditions (Fig. 20.1). The software contains 15 models to predict the shelf-life and safety of seafood and can be accessed in 15 languages. The Fish Shelf-life Prediction Program [7], an add-in for Excel, is also freely available. It models Handbook of Seafood Q uality, Safety and Health Applications Edited by Cesarettin Alasalvar, Fereidoon Shahidi, Kazuo Miyashita and Udaya Wanasundara

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Statistical Modelling of Cold-Smoked Salmon Temperature Profiles for Risk Assessment of Listeria Monocytogenes

Cited by 20 publications

References 0 publications

Effectiveness of the cold chain control procedure in the retail sector in Southern Spain

Effectiveness of the cold chain control procedure in the retail sector in Southern Spain

Scientific Opinion on Public health risks represented by certain composite products containing food of animal origin

Using Predictive Models for the Shelf‐Life and Safety of Seafood

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