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REDLOSSES REDucing food LOSSES by microbial spoilage prediction [French ANR Project]

REDucing food LOSSES by microbial spoilage prediction

07 September 2016

Dynamics of bacterial communities and sensorial characteristics to predict meat product spoilage

Spoilage of meat products, induced by bacterial growth and subsequent metabolic activities, causes significant losses and wastes. It represents a major economical issue for food industry. Appearance, texture, odour and taste defects lead to non compliance with quality standards and to food product losses. Meat product spoilage that appears at the end of the process or during shelf life affects the whole production chain performances as well as the sustainability label of the meat sector.
The objective of the project is to reduce food losses for the meat that is the most consumed in France (pork and poultry) by predicting, early in the production process, the onset of bacterial spoilage during storage in order to propose decision-support tools for directing process. Predictive tools will be developed to enable industrials optimising early enough in the process, the processing steps of meat products such as sausages.
Dynamics of bacterial communities will be monitored all along the production (from primary cuts until the end of the shelf-life, or onset of spoilage) and several sensorial markers will be measured. Data will be used to identify accurate spoilage markers and to compute innovative mathematical models for predicting spoilage occurrence as a function of the initial composition of the microbiota (diversity and abundance) and some abiotic factors (storage temperature, modified atmosphere packaging).
The models will be validated on meat products, including the economic aspect in order to propose decision-support tools for the food producers.

Keywords: spoilage - microbiota - modeling - microbial stability - process - meat - poultry - pork

Partners: the project ANR REDLOSSES, is coordinated by Monique Zagorec from UMR SECALIM.  It gathers 10 expert partners in the fields of microbial ecology, bioinformatics, predictive microbiology, food microbiology and economy:

  •     UMR1014 SECALIM (Inra, Oniris),
  •     UMR1319 MICALIS (Inra, AgroParisTech),
  •     UR1404 MAIAGE (Inra),
  •     University of Brest (Lubem, EA3882),
  •     University of Liège (Ulg-DDA, Belgium),
  •     3 technical centers : Aérial, Ifip and Itavi ;
  •     2 industrial partners : Cooperl Innovation and LDC