Busschaert P.,CPMF2 |
Busschaert P.,Catholic University of Leuven |
Geeraerd A.H.,CPMF2 |
Geeraerd A.H.,Catholic University of Leuven |
And 3 more authors.
International Journal of Food Microbiology | Year: 2010
A framework using maximum likelihood estimation (MLE) is used to fit a probability distribution to a set of qualitative (e.g., absence in 25. g), semi-quantitative (e.g., presence in 25. g and absence in 1. g) and/or quantitative test results (e.g., 10. CFU/g). Uncertainty about the parameters of the variability distribution is characterized through a non-parametric bootstrapping method. The resulting distribution function can be used as an input for a second order Monte Carlo simulation in quantitative risk assessment. As an illustration, the method is applied to two sets of in silico generated data. It is demonstrated that correct interpretation of data results in an accurate representation of the contamination level distribution. Subsequently, two case studies are analyzed, namely (i) quantitative analyses of Campylobacter spp. in food samples with nondetects, and (ii) combined quantitative, qualitative, semiquantitative analyses and nondetects of Listeria monocytogenes in smoked fish samples. The first of these case studies is also used to illustrate what the influence is of the limit of quantification, measurement error, and the number of samples included in the data set. Application of these techniques offers a way for meta-analysis of the many relevant yet diverse data sets that are available in literature and (inter)national reports of surveillance or baseline surveys, therefore increases the information input of a risk assessment and, by consequence, the correctness of the outcome of the risk assessment. © 2010 Elsevier B.V.
Van Derlinden E.,CPMF2 |
Van Derlinden E.,Catholic University of Leuven |
Boons K.,CPMF2 |
Boons K.,Catholic University of Leuven |
And 2 more authors.
Food Microbiology | Year: 2011
In the past years, we explored the dynamics of Escherichia coli K12 at super-optimal temperatures under static and dynamic temperature conditions (Van Derlinden et al. (2008b, 2009, 2010). Disturbed sigmoid growth curves, i.e., a sequence of growth, inactivation and re-growth, were observed, especially close to the maximum growth temperature. Based on the limited set of experiments (i.e., 2 static temperatures and 2 dynamic temperature profiles), the irregular growth curves were explained by postulating the co-existence of two subpopulations: a more resistant, growing population and a temperature sensitive, inactivating population. In this study, the dynamics of the two subpopulations are studied rigorously at 11 constant temperature levels in the region between 45 °C and 46 °C, with at least five repetitions per temperature. At all temperatures, the total population follows a sequence of growth, inactivation and re-growth. The sequence of different stages in the growth curves can be explained by the two subpopulations. The first growth phase and the inactivation phase reflect the presence of the sensitive subpopulation. Hereafter, the population's dynamics are dominated by the growth of the resistant subpopulation. Generally, cell counts are characterized by a large variability. The dynamics of the two subpopulations are carefully analyzed using a heterogeneous subpopulation type model to study the relation between the kinetic parameters of the two subpopulations and temperature, and to evaluate if the fraction d of resistant cells varies with temperature. Results indicate that the growth rate of the sensitive subpopulation decreases with increasing temperature within the range of 45-46 °C. Furthermore, results point in the direction that the duration of this initial growth phase is approximately constant, i.e., around 2. h. Possibly, the stress resistance of the cells decreases after a certain period because the metabolism is fully adapted to exponential growth. Also, the growth rate of the resistant subpopulation decreases with increasing temperature. Due to the extreme variability in the cell density data, derivation of accurate relations was not possible. From the heterogeneous model implementations, given the experimental set-up, both a constant d value and a temperature dependent d value seem plausible. © 2010.
Baka M.,CPMF2 |
Baka M.,Catholic University of Leuven |
Noriega E.,CPMF2 |
Noriega E.,Catholic University of Leuven |
And 6 more authors.
Food Research International | Year: 2014
Listeria monocytogenes is one of the main target pathogens in the food industry. Novel strategies are continuously being investigated to ensure its absence from food products, such as the use of Lactic Acid Bacteria (LAB). They are known for their inhibitory action against pathogenic species due to the production of antimicrobial compounds and the competition for nutrients. In this work, the combined effect of storage temperature and LAB inoculum level on L. monocytogenes growth and the interaction between both microorganisms is examined on heat-treated Frankfurters. The indigenous LAB isolate from Frankfurter sausages was further identified as Leuconostoc carnosum and characterised as neither a bacteriocinogenic nor H2O2-producing species. However, it produces weak organic acids that acidify the food product and, overall, competes with L. monocytogenes for nutrients. Experiments were performed with vacuum packed, surface inoculated sausages, at different static temperatures (4, 8, 12 and 25°C) and inoculum levels of L. carnosum (102, 103 and 104CFU/g) and 102CFU/g L. monocytogenes. Results showed that at low temperature and high L. carnosum inoculum level, L. monocytogenes stops growing earlier than L. carnosum and the lowest maximum population is reached. The Dens et al. model described species interactions in a mechanistic way, revealing a predominant effect of L. carnosum on L. monocytogenes, and describing the decrease phase of Listeria population. The Baranyi and Roberts model, a special case of the Dens et al. model for monoculture, estimated apparent maximum population levels and brought into question the validity of the Jameson effect at low temperature. Results illustrated that indigenous species of meat products can be protective against foodborne pathogens. © 2014.