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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 31, Number 7(3) (2019)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 2357-2365
S&M1938 Research Paper of Special Issue https://doi.org/10.18494/SAM.2019.2342 Published: July 30, 2019 Food Texture Quantification of Tempura Using Magnetic Food Texture Sensor and Time-series Data [PDF] Ninomae Souda, Hiroyuki Nakamoto, Futoshi Kobayashi, Yuya Nagahata, and Yoriyasu Hirosue (Received February 22, 2019; Accepted May 22, 2019) Keywords: sensor, food texture, time-series data, dynamic time warping, tempura
Food texture is one of the characteristics of food and is an important factor in food development. In this paper, a method of food texture quantification based on expressions for texture instead of physical properties is proposed. The method obtains two sets of time-series data of force and vibration during food compression using a magnetic food texture sensor. Dynamic time warping (DTW) matches the time-series data and standard data and calculates the degree of texture similarity. The standard data are determined by DTW barycenter averaging (DBA). The experimental results for tempura showed that the degree of texture similarity based on the vibration data had a strong correlation with the sensory evaluation data.
Corresponding author: Hiroyuki Nakamoto  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Ninomae Souda, Hiroyuki Nakamoto, Futoshi Kobayashi, Yuya Nagahata, and Yoriyasu Hirosue, Food Texture Quantification of Tempura Using Magnetic Food Texture Sensor and Time-series Data, Sens. Mater., Vol. 31, No. 7, 2019, p. 2357-2365. |
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