Behavior of Listeria spp. in Smoked Fish Products Affected by Liquid Smoke, NaCI Concentration, and Temperature

Thurette, J.; Membré, J.M.; Ching, L. Han; Tailliez, R.; Catteau, M

doi:10.4315/0362-028x-61.11.1475

Cited by 45 publications

(30 citation statements)

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“…Differential susceptibility to freezing was suggested previously by Destro et al (5), who found that only two PFGE profile groups were present on a frozen shrimp product even though nine different groups were isolated from shrimp in the processing area. Guyer and Jemmi (16) found that the cold-smoking process did not affect L. monocytogenes, although it has been reported that smoke compounds are inhibitory to L. monocytogenes (35,36). Eklund et al (7) observed a decrease in L. monocytogenes populations in surface-inoculated portions treated with smoke and an increase when the organism was injected into the injector of the flesh.…”

Section: Discussionmentioning

confidence: 99%

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Elucidation of Listeria monocytogenes Contamination Routes in Cold-Smoked Salmon Processing Plants Detected by DNA-Based Typing Methods

Vogel

Huss

Ojeniyi

et al. 2001

Appl Environ Microbiol

213

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The contamination routes of Listeria monocytogenes in cold-smoked salmon processing plants were investigated by analyzing 3,585 samples from products (produced in 1995, 1996, 1998, and 1999) and processing environments (samples obtained in 1998 and 1999) of two Danish smokehouses. The level of product contamination in plant I varied from 31 to 85%, and no L. monocytogenes was found on raw fish (30 fish were sampled). In plant II, the levels of both raw fish and product contamination varied from 0 to 25% (16 of 185 raw fish samples and 59 of 1,000 product samples were positive for L. monocytogenes). A total of 429 strains of L. monocytogenes were subsequently compared by random amplified polymorphic DNA (RAPD) profiling, and 55 different RAPD types were found. The RAPD types detected on the products were identical to types found on the processing equipment and in the processing environment, suggesting that contamination of the final product (cold-smoked salmon) in both plants (but primarily in plant I) was due to contamination during processing rather than to contamination from raw fish. However, the possibility that raw fish was an important source of contamination of the processing equipment and environment could not be excluded. Contamination of the product occurred in specific areas (the brining and slicing areas). In plant I, the same RAPD type (RAPD type 12) was found over a 4-year period, indicating that an established in-house flora persisted and was not eliminated by routine hygienic procedures. In plant II, where the prevalence of L. monocytogenes was much lower, no RAPD type persisted over long periods of time, and several different L. monocytogenes RAPD types were isolated. This indicates that persistent strains may be avoided by rigorous cleaning and sanitation; however, due to the ubiquitous nature of the organism, sporadic contamination occurred. A subset of strains was also typed by using pulsed-field gel electrophoresis and amplified fragment length polymorphism profiling, and these methods confirmed the type division obtained by RAPD profiling.

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Section: Discussionmentioning

confidence: 99%

“…Two processes, smoking and freezing, separate the raw material from the sliced material, and both processes are known to reduce bacterial levels (8,35,36). The shift in DNA types during processing could be explained by different abilities of different DNA types to withstand freezing or smoking.…”

Section: Discussionmentioning

confidence: 99%

Elucidation of Listeria monocytogenes Contamination Routes in Cold-Smoked Salmon Processing Plants Detected by DNA-Based Typing Methods

Vogel

Huss

Ojeniyi

et al. 2001

Appl Environ Microbiol

213

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“…An interaction between salt and phenols has been shown in several studies (Leblanc et al, 2000;Membre, Thurette, & Catteau, 1997;Thurette, Membre, Ching, Tailliez, & Catteau, 1998). The growth inhibitory effect on L. monocytogenes is dependent on the salt concentration, i. e. a mixture of 0.002% phenol and 2 or 3% NaCl had no effect, but the same phenol concentration with 4% NaCl led to a significant reduction in growth (Thurette et al, 1998).…”

Section: Saltmentioning

confidence: 94%

The microbiology of cold smoked salmon

Løvdal

2015

Food Control

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“…Initially, Dalgaard [18] proposed an iterative approach to modelling L. monocytogenes in CSS, combining different kinetic and empirical models. Next, Thurette et al [19] developed a model to predict the behaviour of Listeria as a function of temperature, salt, and amount of liquid smoke expressed as phenol concentration. They validated their model with challenge tests on smoked fish and found agreement between predicted and experimental values within 0.5 log for 60% of the results.…”

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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Behavior of Listeria spp. in Smoked Fish Products Affected by Liquid Smoke, NaCI Concentration, and Temperature

Cited by 45 publications

References 0 publications

Elucidation of Listeria monocytogenes Contamination Routes in Cold-Smoked Salmon Processing Plants Detected by DNA-Based Typing Methods

Elucidation of Listeria monocytogenes Contamination Routes in Cold-Smoked Salmon Processing Plants Detected by DNA-Based Typing Methods

The microbiology of cold smoked salmon

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

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