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Classification of Soymilk and Tofu with Diffuse Reflection Light Using a Deep Learning Technique

1
Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
2
Graduate School of Agriculture, Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-ku, Kyoto 606-8502, Japan
*
Author to whom correspondence should be addressed.
AgriEngineering 2019, 1(2), 235-245; https://doi.org/10.3390/agriengineering1020017
Received: 2 April 2019 / Revised: 6 May 2019 / Accepted: 13 May 2019 / Published: 15 May 2019
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Abstract

Tofu is an ancient soybean product that is produced by heating soymilk containing a coagulation agent. Owing to its benefits to human health, it has become popular all over the world. An important index that determines the final product’s (tofu’s) quality is firmness. Coagulants such as CaSO4 and MgCl2 affect the firmness. With the increasing demand for tofu, a monitoring methodology that ensures high-quality tofu is needed. In our previous paper, an opportunity to monitor changes in the physical properties of soymilk by studying its optical properties during the coagulation process was implied. To ensure this possibility, whether soymilk and tofu can be discriminated via their optical properties should be examined. In this study, a He–Ne laser (Thorlabs Japan Inc., Tokyo, Japan, 2015) with a wavelength of 633 nm was emitted to soymilk and tofu. The images of the scattered light on their surfaces were discriminated using a type of deep learning technique. As a result, the images were classified with an accuracy of about 99%. We adjusted the network architecture and hyperparameters for the learning, and this contributed to the successful classification. The construction of a network that is specific to our task led to the successful classification result. In addition to this monitoring method of the tofu coagulation process, the classification methodology in this study is worth noting for possible use in many relevant agricultural fields.
Keywords: coagulation; deep learning; diffuse reflection; firmness; machine learning; scattering coefficient; soymilk; soybean; tofu; transfer learning coagulation; deep learning; diffuse reflection; firmness; machine learning; scattering coefficient; soymilk; soybean; tofu; transfer learning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Itakura, K.; Saito, Y.; Suzuki, T.; Kondo, N.; Hosoi, F. Classification of Soymilk and Tofu with Diffuse Reflection Light Using a Deep Learning Technique. AgriEngineering 2019, 1, 235-245.

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