Literature DB >> 16416909

A probabilistic modeling approach in thermal inactivation: estimation of postprocess Bacillus cereus spore prevalence and concentration.

J M Membré1, A Amézquita, J Bassett, P Giavedoni, C de W Blackburn, L G M Gorris.   

Abstract

The survival of spore-forming bacteria is linked to the safety and stability of refrigerated processed foods of extended durability (REPFEDs). A probabilistic modeling approach was used to assess the prevalence and concentration of Bacillus cereus spores surviving heat treatment for a semiliquid chilled food product. This product received heat treatment to inactivate nonproteolytic Clostridium botulinum during manufacture and was designed to be kept at refrigerator temperature postmanufacture. As key inputs for the modeling, the assessment took into consideration the following factors: (i) contamination frequency (prevalence) and level (concentration) of both psychrotrophic and mesophilic strains of B. cereus, (ii) heat resistance of both types (expressed as decimal reduction times at 90 degrees C), and (iii) intrapouch variability of thermal kinetics during heat processing (expressed as the time spent at 90 degrees C). These three inputs were established as statistical distributions using expert opinion, literature data, and specific modeling, respectively. They were analyzed in a probabilistic model in which the outputs, expressed as distributions as well, were the proportion of the contaminated pouches (the likely prevalence) and the number of spores in the contaminated pouches (the likely concentration). The prevalence after thermal processing was estimated to be 11 and 49% for psychrotrophic and mesophilic strains, respectively. In the positive pouches, the bacterial concentration (considering psychrotrophic and mesophilic strains combined) was estimated to be 30 CFU/g (95th percentile). Such a probabilistic approach seems promising to help in (i) optimizing heat processes, (ii) identifying which key factor(s) to control, and (iii) providing information for subsequent assessment of B. cereus resuscitation and growth.

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Year:  2006        PMID: 16416909     DOI: 10.4315/0362-028x-69.1.118

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


  3 in total

1.  Probabilistic model for Listeria monocytogenes growth during distribution, retail storage, and domestic storage of pasteurized milk.

Authors:  Konstantinos Koutsoumanis; Athanasios Pavlis; George-John E Nychas; Konstantinos Xanthiakos
Journal:  Appl Environ Microbiol       Date:  2010-02-05       Impact factor: 4.792

2.  Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment.

Authors:  Kento Koyama; Hidekazu Hokunan; Mayumi Hasegawa; Shuso Kawamura; Shigenobu Koseki
Journal:  Appl Environ Microbiol       Date:  2017-02-01       Impact factor: 4.792

3.  The COM-Poisson Process for Stochastic Modeling of Osmotic Inactivation Dynamics of Listeria monocytogenes.

Authors:  Pierluigi Polese; Manuela Del Torre; Mara Lucia Stecchini
Journal:  Front Microbiol       Date:  2021-07-09       Impact factor: 5.640

  3 in total

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