Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 432469
Title Multiple regression model for thermal inactivation of Listeria monocytogenes in liquid food products
Author(s) Lieverloo, J.H.M.; Roode, M. de; Fox, M.B.; Zwietering, M.H.; Wells-Bennik, M.H.J.
Source Food Control 29 (2013)2. - ISSN 0956-7135 - p. 394 - 400.
Department(s) Food Microbiology Laboratory
Publication type Refereed Article in a scientific journal
Publication year 2013
Keyword(s) sublethal heat-shock - escherichia-coli o157-h7 - growth temperature - scott-a - pseudomonas-aeruginosa - salmonella-typhimurium - resistance - milk - ph - thermotolerance
Abstract A multiple regression model was constructed for thermal inactivation of Listeria monocytogenes in liquid food products, based on 802 sets of data with 51 different strains and 6 cocktails of strains published from 1984 to 2010. Significant variables, other than inactivation temperature, were pH, sodium chloride content, sugar content, the temperature of growth or storage before inactivation, in addition to a heat shock before inactivation. The constructed model for thermal inactivation of L. monocytogenes has a reduced variability as these variables are known to influence the thermal resistance (and these are known or controllable in practice). Mean simulation results of inactivation of L. monocytogenes during pasteurisation (20 s, 76 °C) of raw milk (calculated mean level after growth 14 cfu/l) were comparable with results of a single regression model constructed from inactivation data found in experiments in milk only (175 data sets, 18 strains/cocktails). Both models predicted a probability of survival of less than 1 in a billion litres. The study shows that multiple regression modelling can be used to obtain a model from all data available, with a limited and realistic uncertainty level, while retaining the variability of heat resistance due to the 51 strains and 6 cocktails of strains (unknown and not controllable in practice).
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