Literature DB >> 28458190

Characterization of four Paenibacillus species isolated from pasteurized, chilled ready-to-eat meals.

Mariette Helmond1, Masja N Nierop Groot1, Hermien van Bokhorst-van de Veen2.   

Abstract

Food spoilage is often caused by microorganisms. The predominant spoilage microorganisms of pasteurized, chilled ready-to-eat (RTE) mixed rice-vegetable meals stored at 7°C were isolated and determined as Paenibacillus species. These sporeforming psychrotrophic bacteria are well adapted to grow in the starch-rich environment of pasteurized and chilled meals. Growth of the Paenibacillus isolates appeared to be delayed by decreased (<7°C) temperature or chilled temperature (7°C) combined with decreased pH (<5), increased sodium chloride (>5.5%, corresponding with an aw<0.934), or decreased aw (<0.931; using sucrose). To gain insight in the effect of the pasteurization processing of the meal on spore inactivation, heat-inactivation kinetics were determined and D-values were calculated. According to these kinetics, pasteurization up to 90°C, necessary for inactivation of vegetative spoilage microorganisms and pathogens, does not significantly contribute to the inactivation of Paenibacillus spores in the meals. Furthermore, outgrowth of pasteurized spores was determined in the mixed rice-vegetable meal at several temperatures; P. terrae FBR-61 and P. pabuli FBR-75 isolates did not substantially increase in numbers during storage at 2°C, but had a significant increase within a month of storage at 4°C or within several days at 22°C. Overall, this work shows the importance of Paenibacillus species as spoilage microorganisms of pasteurized, chilled RTE meals and that the meals' matrix, processing conditions, and storage temperature are important hurdles to control microbial meal spoilage.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Growth limits; Paenibacilli; Shelf life control; Spore heat resistance

Mesh:

Year:  2017        PMID: 28458190     DOI: 10.1016/j.ijfoodmicro.2017.04.008

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  1 in total

1.  Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty.

Authors:  Satoko Hiura; Hiroki Abe; Kento Koyama; Shige Koseki
Journal:  Front Microbiol       Date:  2021-06-24       Impact factor: 5.640

  1 in total

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