Traditional foods have delighted us for centuries

Further valorisation of traditional foods

Ensure their quality and safety

• Predictive microbiological models (PMM)

• Environmental conditions (intrinsic and extrinsic)

Dynamic data

• Validate the PMM

• Assess traditional foods shelflife
• Assess traditional foods safety
• Innovation in traditional foods

• Growth of computing power
• Development of web applications
  • Predictive microbiology that are globally available
  • Traditional food producers should benefit
    • Scientific and technological advances
    • Inform their decisions on the safety of their products

Predictive microbioly models

• Microbial growth assessment over time
• Microbiological growth
  • Different instrinsic parameters: pH, salt level, etc.
  • Inoculated with the relevant organism or cocktail of organisms
  • Range of temperatures
  • Dynamic temperatures

• Microbial growth is
  not evaluated
• Growth occurs?

• Spoilage microorganisms
• Pathogenic microorganisms
• Enviromental variables included
  • Storage temperature - fluctuating temperatures
  • pH
  • Salt
  • Water activity
  • Preservatives: nitrite, CO2, lactic and acetic acids
• PMM needs to be validate for the traditional foods

Parameters of interest

• Spoilage microorganisms

• Time to reach a specified target level

• Pathogenic microorganisms
• Time for growth to start (lag time): Salmonella, C. botulinum
• Toxins producers microrganisms - critical level is reached: S. aureus and B. cereus
• Time taken to reach toxins producing levels

• Shelf life: Listeria monocytogenes, level of 100 cfu/g during storage (EU legislation)

Acidified traditional foods

• PMM are used to predict the time to growth rather than growth curves

• Data for predictions
• pH
• water activity
• % salt
• temperature (static or dynamic)

• acidified foods: level of preservative?

Final remarks

• Research is needed considering the traditional foods
  • Acquire data: along the process maceration/fermentation/maturation
  • Food matrix’s intrinsic properties also vary in time
• Dynamic predictive microbiology models
  • Intrinsic properties: water activity, pH, lactic acid concentration
  • Manufacture characteristics (i.e., addition of starter cultures, fermentation/maturation time/temperature)
• Need for interdisciplinar teams
  • Expertise in food microbiology
  • Microbial ecology and physiology (functional cultures, effect of antimicrobial compounds and survival of pathogens)
  • Food technology
  • Food sensory science: maintainance of the organoleptic qualities of the traditional foods
  • predictive microbiology and microbial risk assessment
    • Modelling, simulation and optimisation
    • Informatics - development of the IT tools