Research Interests 【 display / non-display 】

Research Interests 【 display / non-display 】

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Research Areas 【 display / non-display 】

Research Areas 【 display / non-display 】

Papers 【 display / non-display 】

Papers 【 display / non-display 】

• Combining comparative spectroscopic analysis with machine learning for origin identification and wheat flour blending ratio prediction in buckwheat flour

  Rikuto Akiyama, Rio Chikura, Fumika Itaki, Tsudumi Shimada, Minami Hazuma, Yvan Llave, Takashi Matsumoto , 2026.06

  Journal of Food Measurement and Characterization

  DOI

• Comparative Evaluation of Fluorescence, NIR, and FT-IR Spectroscopy Combined with Machine Learning for Geographical Origin and Species Identification of Brown Algae

  Kana Suzuki, Meryem Taskaya, Sora Hoshino, Rikuto Akiyama, Rio Chikura, Mai Kanetsuna, Yvan Llave and Takashi Matsumoto , 2026.05

  Applied Sciences

  DOI

• Identification of the Geographical Origins of Matcha Using Three Spectroscopic Methods and Machine Learning

  Meryem Taskaya, Rikuto Akiyama, Mai Kanetsuna, Murat Yigit, Yvan Llave and Takashi Matsumoto , 2026.01

  AgriEngineering

  DOI

• Japanese Rice Variety Identification by Fluorescence Fingerprinting, Near-Infrared Spectroscopy, and Machine Learning

  Rikuto Akiyama , Yvan Llave and Takashi Matsumoto , 2025.11

  AgriEngineering

  DOI

• Fluorescence Spectroscopy and a Convolutional Neural Network for High-Accuracy Japanese Green Tea Origin Identification

  Rikuto Akiyama, Kana Suzuki, Yvan Llave and Takashi Matsumoto , 2025.03

  AgriEngineering

  DOI

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Books 【 display / non-display 】

Books 【 display / non-display 】

• 日本大百科全書：ジャパンナレッジJapanKnowledge（有料会員向けサイト）

  松本隆志 , 2025.11

  株式会社小学館クリエイティブ , トレーサビリティ , 0-0

• 日本大百科全書：ジャパンナレッジJapanKnowledge（有料会員向けサイト）

  松本隆志 , 2025.11

  株式会社小学館クリエイティブ , HACCP , 0-0

• 「食品物流」の基本がわかるコース（2025通信教育教材）

  松本隆志 , 2025.04

  株式会社PHP研究所 , 全て , 0-0

• 品質保証の業務と人材育成：2021品質月間テキスト No.453

  松本隆志 , 2021.10

  品質月間委員会（一般財団法人 日本科学技術連盟） , 全体 , 0-0

• 国内外における食品衛生の関連法規と実務対応に向けた基礎知識　第5章

  松本隆志ほか , 2020.12

  株式会社情報機構 , 第5章食品リコール情報の報告制度の創設 P.90-96 , 0-0

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Grant-in-Aid for Scientific Research 【 display / non-display 】

Grant-in-Aid for Scientific Research 【 display / non-display 】

• Development of a next-generation shelf life setting system aimed at reducing food waste

  Project Period (FY)： 2025/04  -  2028/03  Investigator(s): 松本 隆志

  Grant-in-Aid for Scientific Research(C)  Principal Investigator  25K05727 

• Development of a next-generation shelf life setting system aimed at reducing food waste

  Project Period (FY)： 2022/04  -  2025/03  Investigator(s): Matsumoto Takashi

  Grant-in-Aid for Scientific Research(C)  Principal Investigator  22K02156 

  We were able to develop a quick and simple method for setting expiration dates for processed foods, mainly powdered foods. We collected data on approximately 50 features, such as water activity and amino acids, through physicochemical analysis. Using the data obtained, we developed a machine learning model to estimate expiration dates. Furthermore, we developed a multimodal machine learning model that adds fluorescent fingerprint images taken with a spectrofluorophotometer to the features and uses the physicochemical analysis data in combination, thereby improving accuracy.
  We applied the technology and knowledge of setting expiration dates to identify the origin and variety of food. As a result, we were able to use machine learning to identify seafood and agricultural products using fluorescent fingerprint data taken with a spectrofluorophotometer.

Lesson Subject 【 display / non-display 】

Lesson Subject 【 display / non-display 】