Literature DB >> 19833037

Development and validation of an extensive growth and growth boundary model for Listeria monocytogenes in lightly preserved and ready-to-eat shrimp.

Ole Mejlholm1, Paw Dalgaard.   

Abstract

An existing cardinal parameter growth and growth boundary model for Listeria monocytogenes (O. Mejlholm and P. Dalgaard, J. Food Prot. 70:70-84 and 2485-2497, 2007) was expanded with terms for the effects of acetic, benzoic, citric, and sorbic acids to include a total of 12 environmental parameters and their interactive effects. The new model predicted growth rates (micro(max) values) of L. monocytogenes accurately with bias and accuracy factors of 1.0 and 1.5, respectively, for 16 batches of brined shrimp with benzoic, citric, and sorbic acids. Corresponding values of 0.9 and 1.2, respectively, were obtained for five batches of brined shrimp with acetic and lactic acids. Growth and no-growth responses of L. monocytogenes were also appropriately predicted with 88% correct prediction for 26 experiments with brined shrimp. The new model performed better than existing L. monocytogenes models with a comparable degree of complexity. The high number of environmental parameters, including six organic acids (acetic acid, benzoic acid, citric acid, diacetate, lactic acid, and sorbic acid), allows the new model to predict the effect of substituting one set of preserving parameters for another. The new model also allowed the distance between the growth boundary and specific product characteristics to be quantified by a psi value. This can be of practical importance in the development or reformulation of seafood with preserving parameters that prevent growth of L. monocytogenes and take variability in product characteristics into account.

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Year:  2009        PMID: 19833037     DOI: 10.4315/0362-028x-72.10.2132

Source DB:  PubMed          Journal:  J Food Prot        ISSN: 0362-028X            Impact factor:   2.077


  6 in total

1.  Modeling the growth of Listeria monocytogenes in soft blue-white cheese.

Authors:  Per Sand Rosshaug; Ann Detmer; Hanne Ingmer; Marianne Halberg Larsen
Journal:  Appl Environ Microbiol       Date:  2012-09-14       Impact factor: 4.792

2.  Integrated kinetic and probabilistic modeling of the growth potential of bacterial populations.

Authors:  S M George; A Métris; J Baranyi
Journal:  Appl Environ Microbiol       Date:  2015-03-06       Impact factor: 4.792

3.  Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety.

Authors:  Pierluigi Polese; Manuela Del Torre; Mara Lucia Stecchini
Journal:  Ital J Food Saf       Date:  2018-04-09

4.  Comparison of Chemical Composition and Safety Issues in Fish Roe Products: Application of Chemometrics to Chemical Data.

Authors:  Mauro Vasconi; Erica Tirloni; Simone Stella; Chiara Coppola; Annalaura Lopez; Federica Bellagamba; Cristian Bernardi; Vittorio Maria Moretti
Journal:  Foods       Date:  2020-04-27

5.  The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods.

Authors:  Taran Skjerdal; Andras Gefferth; Miroslav Spajic; Edurne Gaston Estanga; Alessandra De Cesare; Silvia Vitali; Frederique Pasquali; Federica Bovo; Gerardo Manfreda; Rocco Mancusi; Marcello Trevisiani; Girum Tadesse Tessema; Tone Fagereng; Lena Haugland Moen; Lars Lyshaug; Anastasios Koidis; Gonzalo Delgado-Pando; Alexandros Ch Stratakos; Marco Boeri; Cecilie From; Hyat Syed; Mirko Muccioli; Roberto Mulazzani; Catherine Halbert
Journal:  Biomed Res Int       Date:  2017-12-04       Impact factor: 3.411

6.  A Novel LSSVM Based Algorithm to Increase Accuracy of Bacterial Growth Modeling.

Authors:  Masoud Salehi Borujeni; Mostafa Ghaderi-Zefrehei; Farzan Ghanegolmohammadi; Saeid Ansari-Mahyari
Journal:  Iran J Biotechnol       Date:  2018-05-15       Impact factor: 1.671

  6 in total

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