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Research Article | Open Access

Model prediction of inactivation of Aeromonas salmonicida grown on poultry in situ by intense pulsed light

Jingwen WangZhenzhen NingYifan ChenXinglian XuHuhu Wang ( )
Jiangsu Collaborative Innovation Center of Meat Production and Processing, Quality and Safety Control, College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China

Peer review under responsibility of Tsinghua University Press.

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Abstract

The aim of this study was to evaluate the factors influencing the inactivation effect of intense pulsed light (IPL) on Aeromonas salmonicida grown on chicken meat and skin, and to further develop prediction models of inactivation. In this work, chicken meat and skin inoculated with meat-borne A. salmonicida isolates were subjected to IPL treatments under different conditions. The results showed that IPL had obvious bactericidal effect in the chicken skin and thickness groups when the treatment voltage and time were 7 V combined with 5 s. In addition, the lethality curves of A. salmonicida were fitted under IPL conditions of 3.5–7.5 V. The comparison of statistical parameters revealed that the Weibull model could best fit the mortality curves and could accurately predict the mortality dynamic of A. salmonicida grown on chicken skin. And further a secondary model between the scale factor b and the treatment voltage in Weibull model was established using linear equations, which determined that the secondary model could accurately predict the inactivation of A. salmonicida. This study provides a theoretical basis for future prediction models of Aeromonas, and also provides new ideas for sterilization approaches of meat-borne Aeromonas.

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Food Science and Human Wellness
Pages 1011-1017

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Cite this article:
Wang J, Ning Z, Chen Y, et al. Model prediction of inactivation of Aeromonas salmonicida grown on poultry in situ by intense pulsed light. Food Science and Human Wellness, 2024, 13(2): 1011-1017. https://doi.org/10.26599/FSHW.2022.9250087

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Received: 25 August 2022
Revised: 06 September 2022
Accepted: 13 September 2022
Published: 25 September 2023
© 2024 Beijing Academy of Food Sciences. Publishing services by Tsinghua University Press.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).