Objective
Despite improvements in food processing and control of storage and distribution temperatures, food spoilage continues to cause significant loss of revenue to the food industry. It is crucial, for optimisation of quality and consistency of perishable foods, to be able to predict spoilage and hence shelf life. To date there has been no systematic, multidisciplinary scientific approach to prediction of food spoilage and this has been addressed in the attached project proposal.
The general objectives of the proposed work are:
1) to demonstrate that food spoilage can be modelled and a predictive capability developed and;
2) to identify where food spoilage organisms interact, since the growth and spoilage potential of any specific organism will be affected by the presence of other organisms.
The objectives will be achieved by a series of tasks to which each of the four Partners and both Industrial Subcontractors will contribute. The first task involves identifying relevant spoilage organisms, grouping them according to the nature of the spoilage they cause and identifying the volatile metabolites that result in the food becoming spoiled. The second task consists mainly of generating data suitable for modelling, by measuring metabolite accumulation in different environmental conditions of ph, water activity and temperature relevant to foods. Data on activity of microbial exo enzymes and estimates of microbial numbers, in the same environmental conditions, will also be collected. Novel techniques for data capture will be employed including FTIR and GCMS. The MS uses a novel method for simultaneous real time detection and quantification of selected volatiles. Also available is a newly-developed in vitro method for measurement of enzymatic activity. The third task will be to model the data collected, using response surface methodology, with the aim of constructing generic models for food spoilage, as opposed to growth models for food spoilage microorganisms. In task four, the models will be verified using sterile foods inoculated with the same groups of organisms selected for data generation to ensure that they provide valid predictions in real foods. The fifth and final task will be to validate the models in (uninoculated) foods, by generating independent microbiological and organoleptic spoilage data. The overall outcome of the project will provide scientific information regarding the ecology of microbial interactions i.e. Between different groups of spoilage organisms. Some effects of environmental conditions on the evolution of volatiles directly contributing to spoilage, both resulting from the growth of micro organisms and formed by exo-enzymatic activity, will be elucidated. The spoilage models based on the systematic scientific data will have commercial benefits to industry for prediction of shelf life of perishable foods.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences ecology
- natural sciences biological sciences microbiology
- natural sciences biological sciences biochemistry biomolecules proteins enzymes
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
N78DB London
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.