Journal Article
Research Support, Non-U.S. Gov't
Add like
Add dislike
Add to saved papers

Modeling and predicting the growth of lactic acid bacteria in lightly preserved seafood and their inhibiting effect on Listeria monocytogenes.

A cardinal parameter model was developed to predict the effect of diacetate, lactate, CO2, smoke components (phenol), pH, NaCl, temperature, and the interactions between all parameters on the growth of lactic acid bacteria (LAB) in lightly preserved seafood. A product-oriented approach based on careful chemical characterization and growth of bacteria in ready-to-eat seafoods was used to develop this new LAB growth model. Initially, cardinal parameter values for the inhibiting effect of diacetate, lactate, CO2, pH, and NaCl-water activity were determined experimentally for a mixture of LAB isolates or were obtained from the literature. Next, these values and a cardinal parameter model were used to model the effect of temperature (T(min)) and smoke components (P(max)). The cardinal parameter model was fitted to data for growth of LAB (mu(max) values) in lightly preserved seafood including cold-smoked and marinated products with different concentrations of naturally occurring and added organic acids. Separate product validation studies of the LAB model resulted in average bias and accuracy factor values of 1.2 and 1.5, respectively, for growth of LAB (mu(max) values) in lightly preserved seafood. Interaction between LAB and Listeria monocytogenes was predicted by combining the developed LAB model and an existing growth and growth boundary model for the pathogen (O. Mejlholm and P. Dalgaard, J. Food Prot. 70:70-84). The performance of the existing L. monocytogenes model was improved by taking into account the effect of microbial interaction with LAB. The observed and predicted maximum population densities of L. monocytogenes in inoculated lightly preserved seafoods were 4.7 and 4.1 log CFU g(-1), respectively, whereas for naturally contaminated vacuum-packed cold-smoked salmon the corresponding values were 0.7 and 0.6 log CFU g(-1) when a relative lag time of 4.5 was used for the pathogen.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app