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Development of fish-based model systems with various microstructures.

Davy Verheyen1, Maria Baka1, Seline Glorieux2

  • 1BioTeC+ - Chemical and Biochemical Process Technology and Control, KU Leuven, Gebroeders de Smetstraat 1, 9000 Gent, Belgium; OPTEC, Optimization in Engineering Center-of-Excellence, KU Leuven, Belgium; CPMF(2), Flemish Cluster Predictive Microbiology in Foods - www.cpmf2.be, Belgium.

Food Research International (Ottawa, Ont.)
|March 28, 2018
PubMed
Summary

Understanding food microstructure is key to improving predictive microbiology models. This study developed diverse fish-based model systems to investigate how structure impacts microbial behavior, aiding future food safety research.

Keywords:
Food microstructureModel systemsPredictive microbiology

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Area of Science:

  • Food Science
  • Microbiology
  • Rheology

Background:

  • Predictive microbiology models are hindered by incomplete understanding of food microstructure's role in microbial dynamics.
  • Accurate microbial modeling requires data from structured food systems, not just liquid ones.

Purpose of the Study:

  • To develop and characterize fish-based model food systems with distinct microstructures.
  • To isolate and study the impact of food microstructure on microbial growth and inactivation.

Main Methods:

  • Created five model systems: two liquid (with/without xanthan gum), an emulsion, an aqueous gel, and a gelled emulsion.
  • Characterized rheological properties (Newtonian, pseudo-plastic, gel strength) and fat droplet size.
  • Ensured minimal compositional and physico-chemical variations (pH 6.36, aw 0.988) across systems.

Main Results:

  • Model systems exhibited diverse microstructures and rheological behaviors, including Newtonian, pseudo-plastic, and strong gel properties.
  • Fat droplet size was consistent (~1μm) in emulsion-based systems.
  • Systems supported both microbial growth and thermal inactivation studies with homogeneous and surface inoculation.

Conclusions:

  • The developed fish-based model systems effectively represent various food microstructures.
  • These systems are suitable for investigating the influence of food microstructure on microbial dynamics.
  • This research provides a foundation for more accurate predictive microbiology models.