Predicting growth of Listeria monocytogenes at dynamic conditions during manufacturing, ripening and storage of cheeses – Evaluation and application of models. (December 2020)
- Record Type:
- Journal Article
- Title:
- Predicting growth of Listeria monocytogenes at dynamic conditions during manufacturing, ripening and storage of cheeses – Evaluation and application of models. (December 2020)
- Main Title:
- Predicting growth of Listeria monocytogenes at dynamic conditions during manufacturing, ripening and storage of cheeses – Evaluation and application of models
- Authors:
- Martinez-Rios, Veronica
Gkogka, Elissavet
Dalgaard, Paw - Abstract:
- Abstract: Mathematical models were evaluated to predict growth of L. monocytogenes in mould/smear-ripened cheeses with measured dynamic changes in product characteristics and storage conditions. To generate data for model evaluation three challenge tests were performed with mould-ripened cheeses produced by using milk inoculated with L. monocytogenes . Growth of L. monocytogenes and lactic acid bacteria (LAB) in the rind and in the core of cheeses were quantified together with changes in product characteristics over time (temperature, pH, NaCl/aw, lactic- and acetic acid concentrations). The performance of nine available L. monocytogenes growth models was evaluated using growth responses from the present study and from literature together with the determined or reported dynamic product characteristics and storage conditions (46 kinetics). The acceptable simulation zone (ASZ) method was used to assess model performance. A reduced version of the Martinez-Rios et al. (2019) model (https://doi.org/10.3389/fmicb.2019.01510) and the model of Østergaard et al. (2014) (https://doi.org/10.1016/j.ijfoodmicro.2014.07.012 ) had acceptable performance with a ASZ-score of 71-70% for L. monocytogenes growth in mould/smear-ripened cheeses. Models from Coroller et al. (2012) (https://doi.org/10.1016/j.ijfoodmicro.2011.09.023 ) had close to acceptable performance with ASZ-scores of 67–69%. The validated models (Martinez-Rios et al., 2019; Østergaard et al., 2014) can be used to facilitate theAbstract: Mathematical models were evaluated to predict growth of L. monocytogenes in mould/smear-ripened cheeses with measured dynamic changes in product characteristics and storage conditions. To generate data for model evaluation three challenge tests were performed with mould-ripened cheeses produced by using milk inoculated with L. monocytogenes . Growth of L. monocytogenes and lactic acid bacteria (LAB) in the rind and in the core of cheeses were quantified together with changes in product characteristics over time (temperature, pH, NaCl/aw, lactic- and acetic acid concentrations). The performance of nine available L. monocytogenes growth models was evaluated using growth responses from the present study and from literature together with the determined or reported dynamic product characteristics and storage conditions (46 kinetics). The acceptable simulation zone (ASZ) method was used to assess model performance. A reduced version of the Martinez-Rios et al. (2019) model (https://doi.org/10.3389/fmicb.2019.01510) and the model of Østergaard et al. (2014) (https://doi.org/10.1016/j.ijfoodmicro.2014.07.012 ) had acceptable performance with a ASZ-score of 71-70% for L. monocytogenes growth in mould/smear-ripened cheeses. Models from Coroller et al. (2012) (https://doi.org/10.1016/j.ijfoodmicro.2011.09.023 ) had close to acceptable performance with ASZ-scores of 67–69%. The validated models (Martinez-Rios et al., 2019; Østergaard et al., 2014) can be used to facilitate the evaluation of time to critical L. monocytogenes growth for mould/smear-ripened cheeses including modification of recipes with for example reduced salt/sodium or to support exposure assessment studies for these cheeses. Highlights: Extensive evaluation of models to predict growth of L. monocytogenes in mould/smear-ripened cheeses. Model including the effect of temperature, pH, NaCl/aw, lactic and acetic acid concentrations. Predictions can facilitate estimation of safe shelf-life for mould/smear-ripened cheeses. … (more)
- Is Part Of:
- Food microbiology. Volume 92(2020)
- Journal:
- Food microbiology
- Issue:
- Volume 92(2020)
- Issue Display:
- Volume 92, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 92
- Issue:
- 2020
- Issue Sort Value:
- 2020-0092-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-12
- Subjects:
- Predictive microbiology -- Model validation -- Exposure assessment -- Food safety -- Smear cheese -- White-mould cheese -- Blue/white cheese
Food Microbiology -- Periodicals
Aliments -- Microbiologie -- Périodiques
Food -- Microbiology
Periodicals
Food -- Microbiology -- Periodicals
Food contamination -- Periodicals
664.001579 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0740-0020;screen=info;ECOIP ↗
http://www.sciencedirect.com/science/journal/07400020 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.fm.2020.103578 ↗
- Languages:
- English
- ISSNs:
- 0740-0020
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3981.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14425.xml