This project aims to develop and validate a novel quantitative method, based on Analysis of Variance techniques, to give an improved prediction of bacterial lag time and growth in food.?This would allow the optimisation of food processing methods, to ensure microbiological safety and quality.?The distribution of the lag times of individual cells/spores will be measured by microscopic (automated image analysis) and turbidometric methods and analysed by stochastic mathematical models.?The obtained distribution will be used to optimise earlier food process and treatment, and to predict the bacterial responses to the subsequent food environment accurately. The proposal addresses problems of variation of the lag time of individual cells that are not addressed by current predictive microbiology.
Objectives:
The purpose of the project is to develop a method based on stochastic mathematical modelling techniques to improve the microbial safety and quality of food.? It has three main objectives: 1.?To optimise the effect of processing methods with respect to microbial safety and quality of the food.? 2.?To predict more accurately the probability of bacterial survival, lag and growth in food.? 3.?To develop a methodology which is able to utilise the information on the variability of individual cells and complements the current techniques of predictive microbiology.
Description of the work:
Date on microbial lag distributions will be collected by microscopic (automated image analysis) and turbidimetic measurement systems.?The data will be put in a systematically formatted database and will be analysed by statistical methods and stochastic mathematical models.?Experiments will be carried out to study the effects of relevant environmental conditions (e.g. storage temperature, pH, NaCl, mild preservatives and pre-treatments) on the lag distribution of individual cells/spores.? Stochastic mathematical technique will be used to develop models to predict the effect of these conditions/treatments on microbial growth.?An improved prediction of the microbial response will enable more effective controls to be implemented so as to ensure product safety and microbiological quality of food.?The validity of the predictive models will be confirmed by conducting tests in selected food systems.?A selection of both spoilage and foodborne pathogens, as well as moulds will be included for study; Listeria monocytogenes, Escherichia coli, Clostricium spp, Bacillus spp; Aspergillus, Penicillium.?The research is principally focussed on the safety and microbiological quality of the so-called 搈inimally processed foods?and this is reflected in the choice of bacterial for study.
Project coordinator:
Dr
J髗sef Baranyi
Institute of Food Research
Food Safety Science Division,
Institute of Food Research
Norwich
United Kingdom
Tel: +44 (1603) 255 000
Fax: ?+44 (1603) 507 723
Email: jozsef.baranyi@bbsrc.ac.uk
Participants:
| Participant Name | Status* | Country |
| Institute of Food Research |
c |
United Kingdom |
| School of Agricultural Sciences, University of Tasmania |
M |
Australia |
| Danone Vitapole, Group Danone |
M |
Denmark |
| Unilever Research Vlaardingen, Unilever Nederland BV |
M |
Netherlands |
| Dept, Nutricion y Bromatolodia III (Higiene y Tecnologia de Los Alimentos), Universidad Complutense de Madrid |
M |
Spain |
| Centre for Surface Biotechnology, Uppsala University |
M |
Sweden |
| School of Food Biosciences, The University of Reading |
M |
United Kingdom |
*C = Co-ordinator; M - Member
Sources: European Commission
