A review of quantitative methods to describe efficacy of pulsed light generated inactivation data that embraces the occurrence of viable but non culturable state microorganisms

The purpose of this timely review is to critically appraise and to assess the potential significance of best-published microbial inactivation kinetic data generated by pulsed light (PL). The importance of selecting different inactivation models to describe the PL inactivation kinetics is highlighted. Current methods for the detection of viable-but-nonculturable (VBNC) organisms post PL-treatments are outlined along with the limitations of these methods within food microbiology. Greater emphasis should be placed on elucidating appropriate inactivation kinetic model(s) to cater for the occurrence of these VBNC organisms that are underestimated in number using traditional culture-based enumeration methods. Finally, the importance of further molecular and combinational research to tackle the potential threat posed by VBNC organisms with regard to kinetic inactivation modelling and nexus to public health and food safety is presented.Ciencias de la Alimentació

Identification of non-linear microbial inactivation kinetics under dynamic conditions

In this study dynamic microbial inactivation experiments are exploited for performing parameter identification of a non-linear microbial model. For that purpose microbial inactivation data are produced and a differential equation exhibiting a shoulder and a loglinear phase is employed. The derived parameter estimates from this method were used to perform predictions on an independent experimental set at fluctuating temperature. Joint confidence regions and asymptotic confidence intervals of the estimated parameters were compared with previous studies originating from parameter identification under isothermal conditions. The developed approach can provide more reliable estimates for realistic conditions compared to the usual or standard two step approach.[**]status: publishe

Development of a novel approach for secondary modelling in predictive microbiology: incorporation of microbiological knowledge in black box polynomial modelling

This research deals with the development of a novel secondary modelling procedure within the framework of predictive microbiology. The procedure consists of three steps: (i) careful formulation of the available microbiological information, both from literature and from the experimental case study at hand, (ii) translation of these requirements in mathematical terms under the form of partial derivatives throughout the complete interpolation region of the experimental design, and (iii) determination of parameter values with suitable optimisation techniques for a flexible black box modelling approach, e.g., a polynomial model or an artificial neural network model. As a vehicle for this procedure, the description of the maximum specific growth rate of Lactobacillus sakei in modified BHI-broth as influenced by suboptimal temperature, water activity, sodium lactate and dissolved carbon dioxide concentration is under study. The procedure results in a constrained polynomial model with excellent descriptive and interpolating features in comparison with an extended Ratkowsky-type model and classical polynomial model, by combining specific properties of both model types. The developed procedure is illustrated on the description of the lag phase as well. It is stressed how the confrontation with experimental data is very important to appreciate the descriptive and interpolating capacities of new or existing models, which is nowadays not always carefully performed. Alternatively, the first two steps of the novel procedure can be used as a tool to demonstrate clearly (possible) interpolative shortcomings of an existing model with straightforward spreadsheet calculations. (C) 2003 Elsevier B.V. All rights reserved.status: publishe

Development of predictive modelling approaches for surface temperature and associated microbiological inactivation during hot dry air decontamination

This research deals with the development of predictive modelling approaches in the field of heat transfer and microbial inactivation. Upon making some backstage microbiological considerations, surface temperature predictions during hot dry air decontaminations are incorporated in a microbial inactivation model, in order to describe inactivation kinetics under realistic (time-varying) temperature conditions. In the present study, the following parts are presented. (i) First, a one-dimensional heat transfer model is developed taking into account exchanges by convection, radiation and evaporation. The model is subsequently validated on a laboratory setup and on a test rig, assuming no water activity changes. This test rig is developed for studying-at a later stage-surface pasteurisation treatment on food products with the use of hot dry air. (ii) Isothermal inactivation data of Escherichia coli K12 MG1655 have been collected and inactivation parameters are accurately estimated by using a primary and a secondary model in a global modelling approach. (iii) Microbiological considerations such as microbial growth effects during come-up times, initial temperature of inactivation, and heat resistance effects, based on experimental observations and on literature studies, are formulated in order to evaluate possible microbial effects arising under the dynamic temperature conditions modelled in step (i). (iv) Microbial inactivation simulations with the incorporation of surface temperature predictions are presented. (v) Finally, the level of the microbial decontamination in an example based on the design of an industrial installation is presented, outlining the importance of the combination of surface temperature and microbial inactivation modelling approaches.status: publishe