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Establishing Equivalence for Microbial-Growth-Inhibitory Effects ("Iso-Hurdle Rules") by Analyzing Disparate Listeria monocytogenes Data with a Gamma-Type Predictive Model
- Pujol, Laure, Kan-King-Yu, Denis, Le Marc, Yvan, Johnston, Moira D., Rama-Heuzard, Florence, Guillou, Sandrine, McClure, Peter, MembrÃ©, Jeanne-Marie
- Applied and environmental microbiology 2012 v.78 no.4 pp. 1069-1080
- Listeria monocytogenes, acetic acid, control methods, databases, experimental design, food pathogens, industry, microbial growth, models, outputs, salts, sorbic acid, temperature
- Preservative factors act as hurdles against microorganisms by inhibiting their growth; these are essential control measures for particular food-borne pathogens. Different combinations of hurdles can be quantified and compared to each other in terms of their inhibitory effect ("iso-hurdle"). We present here a methodology for establishing microbial iso-hurdle rules in three steps: (i) developing a predictive model based on existing but disparate data sets, (ii) building an experimental design focused on the iso-hurdles using the model output, and (iii) validating the model and the iso-hurdle rules with new data. The methodology is illustrated with Listeria monocytogenes. Existing data from industry, a public database, and the literature were collected and analyzed, after which a total of 650 growth rates were retained. A gamma-type model was developed for the factors temperature, pH, aw, and acetic, lactic, and sorbic acids. Three iso-hurdle rules were assessed (40 logcount curves generated): salt replacement by addition of organic acids, sorbic acid replacement by addition of acetic and lactic acid, and sorbic acid replacement by addition of lactic/acetic acid and salt. For the three rules, the growth rates were equivalent in the whole experimental domain (Î³ from 0.1 to 0.5). The lag times were also equivalent in the case of mild inhibitory conditions (Î³ â¥ 0.2), while they were longer in the presence of salt than acids under stress conditions (Î³ < 0.2). This methodology allows an assessment of the equivalence of inhibitory effects without intensive data generation; it could be applied to develop milder formulations which guarantee microbial safety and stability.