Potential application of quantitative microbiological risk assessment techniques to an aseptic-UHT process in the food industry

被引:21
|
作者
Pujol, Laure [1 ,2 ]
Albert, Isabelle [3 ]
Johnson, Nicholas Brian [4 ]
Membre, Jeanne-Marie [1 ,2 ]
机构
[1] INRA, Secalim UMR1014, F-44307 Nantes, France
[2] LUNAM Univ, Oniris, F-44307 Nantes, France
[3] INRA, Met Risk UR1204, F-75231 Paris 05, France
[4] Nestle Res Ctr, CH-1000 Lausanne, Switzerland
关键词
Risk-based food safety management; Modelling microbial behaviour; Modelling post-thermal-process recontamination; Probabilistic risk assessment; Commercial sterility; Food spoilage; CLEANING-IN-PLACE; SENSITIVITY-ANALYSIS; LISTERIA-MONOCYTOGENES; THERMAL INACTIVATION; CROSS-CONTAMINATION; EXPOSURE ASSESSMENT; ASSESSMENT MODEL; GROWTH; MANAGEMENT; CEREUS;
D O I
10.1016/j.ijfoodmicro.2013.01.021
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Aseptic Ultra-High-Temperature (UHT)-type processed food products (e.g. milk or soup) are ready to eat products which are consumed extensively globally due to a combination of their comparative high quality and long shelf life, with no cold chain or other preservation requirements. Due to the inherent microbial vulnerability of aseptic-UHT product formulations, the safety and stability-related Performance Objectives (POs) required at the end of the manufacturing process are the most demanding found in the food industry. The key determinants to achieving sterility, and which also differentiates aseptic-UHT from in-pack sterilised products, are the challenges associated with the processes of aseptic filling and sealing. This is a complex process that has traditionally been run using deterministic or empirical process settings. Quantifying the risk of microbial contamination and recontamination along the aseptic-UHT process, using the scientifically based process Quantitative Microbial Risk Assessment (QMRA) offers the possibility to improve on the currently tolerable sterility failure rate (i.e. 1 defect per 10,000 units). In addition, benefits of applying QMRA are to implement process settings in a transparent and scientific manner; ii) to develop a uniform common structure whatever the production line, leading to a harmonisation of these process settings, and; iii) to bring elements of a cost-benefit analysis of the management measures. The objective of this article is to explore how QMRA techniques and risk management metrics may be applied to aseptic-UHT-type processed food products. In particular, the aseptic-UHT process should benefit from a number of novel mathematical and statistical concepts that have been developed in the field of QMRA. Probabilistic techniques such as Monte Carlo simulation, Bayesian inference and sensitivity analysis, should help in assessing the compliance with safety and stability-related POs set at the end of the manufacturing process. The understanding of aseptic-UHT process contamination will be extended beyond the current "As-Low-As-Reasonably-Achievable" targets to a risk-based framework, through which current sterility performance and future process designs can be optimised. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:283 / 296
页数:14
相关论文
共 42 条
  • [31] A Supportive Framework for Collaborative Implementation of Quantitative Risk Analysis in the Hazardous Process Industry and Application to Natural Gas Plant
    Yoon, Ik Keun
    Lim, Dong Yun
    Jung, Ho Jin
    Seo, Jae Min
    Oh, Shin Kyu
    JOURNAL OF CHEMICAL ENGINEERING OF JAPAN, 2019, 52 (04) : 349 - 361
  • [32] A fire risk assessment system and application for process industry using fuzzy Petri net and HAZID method
    Chen, Xingbai
    Wang, Ziyun
    Zhang, Cheng
    Xiang, Yue
    Dai, Yiyang
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY, 2024, 238 (05) : 903 - +
  • [33] Quantitative microbiological risk assessment as a tool to obtain useful information for risk managers - Specific application to Listeria monocytogenes and ready-to-eat meat products
    Mataragas, M.
    Zwietering, M. H.
    Skandamis, P. N.
    Drosinos, E. H.
    INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, 2010, 141 : S170 - S179
  • [34] Development and application of a quantitative risk assessment to a very slow moving rock slope and potential sudden acceleration
    Macciotta, Renato
    Martin, C. Derek
    Morgenstern, Norbert R.
    Cruden, David M.
    LANDSLIDES, 2016, 13 (04) : 765 - 785
  • [35] Development and application of a quantitative risk assessment to a very slow moving rock slope and potential sudden acceleration
    Renato Macciotta
    C. Derek Martin
    Norbert R. Morgenstern
    David M. Cruden
    Landslides, 2016, 13 : 765 - 785
  • [36] Microbiological quality assessment of fresh produce: Potential health risk to children and urgent need for improved food safety in school feeding schemes
    Msimango, Thabang
    Duvenage, Stacey
    Du Plessis, Erika M.
    Korsten, Lise
    FOOD SCIENCE & NUTRITION, 2023, 11 (09): : 5501 - 5511
  • [37] Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
    Rehman, Nighat
    Anjum, Rukhshanda
    Petros, Fikre Bogale
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [38] Mathematical modeling of Bacillus cereus in Saengsik, a powdered ready-to-eat food and its application in quantitative microbial risk assessment
    Hwang, Daekeun
    Park, Jin Hwa
    Yoon, Yohan
    Ha, Sang-Do
    Rhee, Min Suk
    Koo, Minseon
    Kim, Hyun Jung
    JOURNAL OF FOOD SAFETY, 2023, 43 (01)
  • [39] Quantitative microbiological risk assessment using individual data on food storage and consumption (Part 1): A case study on listeriosis associated to ready-to-eat foods in France
    Redondo, Hernan G.
    Guillier, Laurent
    Desvignes, Virginie
    Filter, Matthias
    Pires, Sara M.
    Nauta, Maarten
    MICROBIAL RISK ANALYSIS, 2025, 29
  • [40] Risk assessment in the constructions sector of EU countries: Application of a methodological framework using quantitative techniques and occupational accidents' data throughout the period 1996-2011
    Marhavilas P.K.
    Vrountas P.T.
    Journal of Engineering Science and Technology Review, 2018, 11 (01) : 66 - 73