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Hydrocolloid clustering based on their rheological properties.

Ali Alghooneh1, Seyed M A Razavi1, Stefan Kasapis2

  • 1Food Hydrocolloids Research Center, Department of Food Science and Technology, Ferdowsi University of Mashhad, Mashhad, Iran.

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|September 25, 2018
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Summary

This study objectively classifies hydrocolloids using rheological data and fuzzy logic clustering, revealing four distinct groups based on their flow and structural properties. This classification aids researchers in selecting appropriate tests and designing hydrocolloid formulations for specific applications.

Keywords:
biopolymerclassificationdynamic shearrheologysteady sheartransient shear

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Area of Science:

  • Rheology and Material Science
  • Food Science and Technology
  • Polymer Science

Background:

  • Hydrocolloids are crucial for modifying rheology in various industries, particularly in food systems.
  • There is a continuous demand for novel hydrocolloids with specific functionalities.
  • Understanding structure-function relationships is key to rationally designing hydrocolloid formulations.

Purpose of the Study:

  • To propose an objective classification system for commercial and novel hydrocolloids.
  • To identify distinct rheological patterns among different hydrocolloid types.
  • To provide a framework for selecting appropriate rheological tests and designing hydrocolloid applications.

Main Methods:

  • Generated 74 rheological parameters from steady, dynamic, and transient shear measurements.
  • Employed agglomerative hierarchical clustering with >60% similarity index for categorization.
  • Utilized fuzzy c-means classification to extract patterns within each identified class.

Main Results:

  • Successfully classified 11 hydrocolloids (7 commercial, 4 novel) into four distinct groups based on rheological properties.
  • Identified specific hydrocolloids within each of the four classes: Class 1 (κ-carrageenan, agar gum), Class 2 (high methoxyl pectin, xanthan, sage seed gum, basil seed gum), Class 3 (alginate gum, Balangu-Shirazi seed gum), Class 4 (guar gum, cress seed gum, carboxymethyl cellulose).
  • Demonstrated that fuzzy logic clustering allows for partial membership, offering a nuanced classification compared to traditional methods.

Conclusions:

  • The proposed classification method provides a valuable map for researchers to select optimal rheological tests.
  • This approach facilitates the rational design of hydrocolloid-based formulations by understanding their rheological behavior.
  • The study offers insights into the structure-function relationships of hydrocolloids, aiding in the development of new sources with specific functionalities.