Development of an automated food compression system for food texture analysis considering various mechanical stimuli on teeth during mastication

抄録

Texture evaluation has still been challenging for the past five decades, particularly for foods with similar textures. Additionally, it is the same situation for foods with different sizes and/or shapes. In this study, we investigated a method to evaluate texture in more detail by compressing food using a teeth-shaped test fixture that mimics mastication and acquiring six times the amount of information compared to conventional methods. The purpose is to investigate the effect of a teeth-shaped fixture on food compression test, and to develop an automated food compression system toward food texture evaluation based on deep learning.