Development of an exposure assessment industrial model for Bacillus cereus in rice matrix containing insect chitosan

An exposure assessment model for industrial use has been developed by using kinetic data from inactivation and growth of spores. It can provide a valuable tool for estimating the concentration of after a storage period of 24 h at a specified temperature (20 °C) and for an estimation of the percentag...

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Veröffentlicht in:Food science and technology international 2024-10, p.10820132241289325
Hauptverfasser: Valdez-Narváez, María Inés, Fernández-Felipe, M Teresa, Rodrigo, Dolores
Format: Artikel
Sprache:eng
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Zusammenfassung:An exposure assessment model for industrial use has been developed by using kinetic data from inactivation and growth of spores. It can provide a valuable tool for estimating the concentration of after a storage period of 24 h at a specified temperature (20 °C) and for an estimation of the percentage of contaminated portions according to the input data of the model. This model considers a rice-derived product that has undergone a standard cooking process at 95 °C for 20 min. According to the results, the presence of chitosan affects the final microbial load after storage, potentially serving as an additional control measure in the event of cold chain abuse or break. Chitosan's antimicrobial properties likely play a role in reducing microbial growth during storage, thereby contributing to enhanced food safety. In practical terms, this suggests that incorporating chitosan into food products, especially those susceptible to microbial contamination like rice derivatives, could help mitigate risks associated with temperature abuse or cold chain disruptions. By acting as a protective barrier against microbial proliferation, chitosan offers a preventive measure to maintain product quality and safety throughout the supply chain. Considering two scenarios, 10 or 10 as initial contamination the model estimated that the 55 and 100% of portions would be respectively contaminated, according to a Performance Criteria of 4 log reductions.
ISSN:1082-0132
1532-1738
1532-1738
DOI:10.1177/10820132241289325