Understanding Food Texture Using Masticatory Robots

  • Weiliang Xu
  • John E. Bronlund
Part of the Studies in Computational Intelligence book series (SCI, volume 290)


One of the key applications of masticatory robots is for the characterisation of food texture. Traditional methods to evaluate food texture employ human panels using sensory science techniques, or instrumental measures. Each of these approaches present limitations. Sensory techniques are semi-quantitative and can be used to describe both initial food properties and the textural change during mastication, however subject variability, time and cost can be prohibitive. Instrumental methods are quantitative but are difficult to apply across a wide range of products and are not easily correlated with sensory texture perception. Because masticatory robots are designed to mimic human chewing, they can potentially provide information on the changing texture of foods during mastication and be used as a tool for developing understanding of the interactions between mastication behaviour, food structure and mechanical properties. This chapter summarises the key physical processes that occur to food during mastication in order to define the functionality that mastication robots must incorporate. The current mastication robots are then reviewed with respect to these requirements.


Occlusal Surface Particle Size Reduction Food Bolus Lower Tooth Food Texture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Weiliang Xu
    • John E. Bronlund

      There are no affiliations available

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