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Inactivation model and risk-analysis design for apple juice processing by high-pressure CO2

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Abstract

Sigmoidal microbial survival curves are observed in high-pressure carbon dioxide (HPCD) pasteurization treatments. The objectives of this study were to use the Gompertz primary model to describe the inactivation in apple juice of the pathogen Escherichia coli CGMCC1.90 and to apply probabilistic engineering to select HPCD treatments meeting at least 5 log10 reductions (SV ≥ 5) at 95% confidence. This required secondary models for the temperature (T, °C) and pressure (P, MPa) dependence of the Gompertz model parameters. The expressions \( b\left( {T,P} \right) = 14.21 + 0.011P - 0.67T + 0.0085T^{2} \) and \( c\left( {T,P} \right) = - 0.10 + 0.0023P + 0.0037T \) selected using goodness-of-fit measures and assessments based on Akaike and Bayesian information criteria were consistent with proposed mechanistic models for HPCD bactericidal effects. Monte Carlo simulations accounting for the variability and uncertainty of the parameter b and c estimates were used to predict SV values for a given time, temperature and CO2 pressure combination and desired confidence boundary. A similar approach used to estimate process times meeting SV ≥ 5 at 95% confidence for a given temperature and CO2 pressure combination, showed that HPCD processes met this requirement only for relatively long processing times, i.e., 35–124 min in the experimental range of 32–42 °C and 10–30 MPa. Therefore, further HPCD research is required to reduce processing time.

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Acknowledgements

This project was supported by Formula Grants 2011-31200-06041/2012-31200-06041328 from the USDA National Institute of Food and Agriculture, Fondo Nacional de Ciencia y Tecnología de Chile (FONDECYT Grant 1151025), Research Office of Universidad Andrés Bello (DI-641-15/R 2015), and Tecnológico de Monterrey (Research chair funds GEE 1A01001375).

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Authors and Affiliations

  1. Food Process Engineering Group, Department of Food Science and Technology, Oregon State University, Corvallis, OR, 97331, USA

    Kai Deng, Xulei Wu & J. Antonio Torres

  2. Gut Microbiota and Clostridia Research Group, Departamento de Ciencias Biológicas, Facultad de Ciencias Biológicas, Universidad Andrés Bello, Santiago, Chile

    Kai Deng & Daniel Paredes-Sabja

  3. Tecnológico de Monterrey, Escuela de Ingeniería y Ciencias, Centro de Biotecnología FEMSA, Monterrey, Mexico

    Vinicio Serment-Moreno, Jorge Welti-Chanes & J. Antonio Torres

  4. Department of Statistics, Oregon State University, Corvallis, OR, 97331, USA

    Claudio Fuentes

  5. School of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR, 97331, USA

    Xulei Wu

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  1. Kai Deng
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  2. Vinicio Serment-Moreno
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  3. Jorge Welti-Chanes
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  4. Daniel Paredes-Sabja
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  5. Claudio Fuentes
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  6. Xulei Wu
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  7. J. Antonio Torres
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Correspondence to Daniel Paredes-Sabja or J. Antonio Torres.

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Deng, K., Serment-Moreno, V., Welti-Chanes, J. et al. Inactivation model and risk-analysis design for apple juice processing by high-pressure CO2 . J Food Sci Technol 55, 258–264 (2018). https://doi.org/10.1007/s13197-017-2933-9

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  • DOI: https://doi.org/10.1007/s13197-017-2933-9

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