IJAT Vol.16 No.4 pp. 421-426
doi: 10.20965/ijat.2022.p0421

Technical Paper:

Food Texture Measurement System Using Rod Type Actuator for Imitation of Human Mastication

Hiroyuki Nakamoto*,†, Yuya Nagahata**, and Futoshi Kobayashi*

*Kobe University
1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo 657-8501, Japan

Corresponding author

**J-Oil Mills, Inc., Tokyo, Japan

November 8, 2021
January 5, 2022
July 5, 2022
food texture, texture measurement, rod-type actuator, mastication, food evaluation

Food texture is one of the most important factors in determining the personal palatability of foods, so food companies require food texture measurement and evaluation in developing novel food products. However, instruments are not fast enough or strong enough to imitate human mastication. To measure the textures of different foods, this study proposes a sensor stand that uses a rod-type actuator. The target speed and force of the sensor stand are 100 mm/s and 100 N, respectively. A food texture sensor that imitates the structure of a human tooth is attached to the sensor stand. The sensor stand and a desktop computer make up the measurement system. Using the system, the fundamental characteristics of the sensor stand with the texture sensor are demonstrated. Verification experiments confirm that the sensor stand satisfies the target values of speed and force. Experiments on actual food items also demonstrate the effectiveness of the measurement system in evaluating food textures.

Cite this article as:
H. Nakamoto, Y. Nagahata, and F. Kobayashi, “Food Texture Measurement System Using Rod Type Actuator for Imitation of Human Mastication,” Int. J. Automation Technol., Vol.16, No.4, pp. 421-426, 2022.
Data files:
  1. [1] K. Toko, “A taste sensor,” Meas. Sci. and Technol., Vol.9, No.12, pp. 1919-1936, doi: 10.1088/0957-0233/9/12/001, 1998.
  2. [2] K. Toko, “Taste sensor,” Sens. and Actuators B: Chem., Vol.64, No.1, pp. 205-215, doi: 10.1016/S0925-4005(99)00508-0, 2000.
  3. [3] Intelligent Sensor Technology, Inc., “What is a Taste Sensor?.” [Accessed November 1, 2021]
  4. [4] P. Dani and T. Nakamoto, “Sensory Evaluation of Odor Approximation Using NMF with Kullback-Leibler Divergence and Itakura-Saito Divergence in Mass Spectrum Space,” J. of The Electrochem. Soc., Vol.167, No.16, 167520, doi: 10.1149/1945-7111/abd110, 2020.
  5. [5] R. Yatabe, A. Shunori, B. Wyszynski, Y. Hanai, A. Nakao, M. Nakatani, A. Oki, H. Oka, T. Washio, and K. Toko, “Odor Sensor System Using Chemosensitive Resistor Array and Machine Learning,” IEEE Sens. J., Vol.21, No.2, pp. 2077-2083, doi: 10.1109/JSEN.2020.3016678, 2021.
  6. [6] K. Nishinari, “Rheology, Food Texture and Mastication,” J. of Texture Stud., Vol.35, No.2, pp. 113-124, doi: 10.1111/j.1745-4603.2004.tb00828.x, 2004.
  7. [7] N. Matsumoto and A. Matsumoto, “Taste of Food,” J. of Cookery Sci. of Japan, Vol.10, No.2, pp. 97-101, doi: 10.11402/cookeryscience1968.10.2_97, 1977 (in Japanese).
  8. [8] H. Tanaka, N. Koizumi, U. Uema, and M. Inami, “Chewing Jockey: Augmented Food Texture by Using Sound Based on the Cross-Modal Effect,” SIGGRAPH Asia 2011 Emerg. Technol., 18, 2011.
  9. [9] H. Endo, H. Kaneko, S. Ino, and W. Fujisaki, “An Attempt to Improve Food/Sound Congruity Using an Electromyogram Pseudo-Chewing Sound Presentation System,” J. Adv. Comput. Intell. Intell. Inform., Vol.21, No.2, pp. 342-349, doi: 10.20965/jaciii.2017.p0342, 2017.
  10. [10] A. S. Szczesniak, “Classification of Textural Characteristics,” J. of Food Sci., Vol.28, No.4, pp. 385-389, doi: 10.1111/j.1365-2621.1963.tb00215.x, 1963.
  11. [11] M. C. Bourne, “Chapter 4 – Principles of Objective Texture Measurement,” M. C. Bourne, “Food Texture and Viscosity: Concept and Measurement (2nd Edition),” pp. 107-188, Academic Press, 2002.
  12. [12] T. Takeshita and F. Nakazawa, “Mastication Velocity of the First Molar in Relation to the Mechanical Properties of Food,” J. of Home Econ. of Japan, Vol.58, No.3, pp. 129-137, doi: 10.11428/jhej.58.129, 2007 (in Japanese).
  13. [13] Y. Kinumatsu, Y. Michiwaki, M. Yokoyama, K. Michi, T. Takahashi, and H. Ogoshi, “Food Grouping Based on Human Mastication,” J. of the Jpn. Stomatol. Soc., Vol.51, No.1, pp. 35-42, doi: 10.11277/stomatology1952.51.35, 2002 (in Japanese).
  14. [14] H. Akimoto, N. Sakurai, and D. Shirai, “A new device for acoustic measurement of food texture using free running probe,” J. of Food Eng., Vol.215, pp. 156-160, doi: 10.1016/j.jfoodeng.2017.07.030, 2017.
  15. [15] N. Sakurai, H. Akimoto, and T. Takashima, “Measurement of vertical and horizontal vibrations of a probe for acoustic evaluation of food texture,” J. of Texture Stud., Vol.52, No.1, pp. 25-35, doi: 10.1111/jtxs.12559, 2021.
  16. [16] A. Shimada, Y. Yamabe, T. Torisu, L. Baad-Hansen, H. Murata, and P. Svensson, “Measurement of dynamic bite force during mastication,” J. of Oral Rehabil., Vol.39, No.5, pp. 349-356, doi: 10.1111/j.1365-2842.2011.02278.x, 2012.
  17. [17] H. Nakamoto, D. Nishikubo, and F. Kobayashi, “Food texture evaluation using logistic regression model and magnetic food texture sensor,” J. of Food Eng., Vol.222, pp. 20-28, doi: 10.1016/j.jfoodeng.2017.11.008, 2018.
  18. [18] K. Kusumi, H. Nakamoto, F. Kobayashi, and Y. Nagahata, “Development of Magnetic Food Texture Sensor with Spring and Sliding Mechanism,” 2020 IEEE Sens., pp. 1-4, doi: 10.1109/SENSORS47125.2020.9278861, 2020.
  19. [19] SMC Corporation, Rod Type/Guide Rod Type in WEB Catalog. [Accessed December 20, 2021]

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Last updated on Aug. 05, 2022