Repetitive Direct Comparison Method for Odor Sensing

Author:

Imamura Gaku12ORCID,Minami Kosuke3ORCID,Yoshikawa Genki34ORCID

Affiliation:

1. International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Japan

2. Graduate School of Information Science and Technology, Osaka University, 1-2 Yamadaoka, Suita 565-0871, Japan

3. Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Japan

4. Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8571, Japan

Abstract

Olfactory sensors are one of the most anticipated applications of gas sensors. To distinguish odors—complex mixtures of gas species, it is necessary to extract sensor responses originating from the target odors. However, the responses of gas sensors tend to be affected by interfering gases with much higher concentrations than target odor molecules. To realize practical applications of olfactory sensors, extracting minute sensor responses of odors from major interfering gases is required. In this study, we propose a repetitive direct comparison (rDC) method, which can highlight the difference in odors by alternately injecting the two target odors into a gas sensor. We verified the feasibility of the rDC method on chocolates with two different flavors by using a sensor system based on membrane-type surface stress sensors (MSS). The odors of the chocolates were measured by the rDC method, and the signal-to-noise ratios (S/N) of the measurements were evaluated. The results showed that the rDC method achieved improved S/N compared to a typical measurement. The result also indicates that sensing signals could be enhanced for a specific combination of receptor materials of MSS and target odors.

Funder

Leading Initiative for Excellent Young Researchers, Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan

Grant-in-Aid for Scientific Research

Leave a Nest Grant, Yoshinoya Award, Leave a Nest Co., ltd.

Yoshinoya Co., Ltd.

Public/Private R&D Investment Strategic Expansion Program

Cabinet Office, Japan

World Premier International Research Center Initiative (WPI) on Materials Nanoarchitectonics (MANA), NIMS

Center for Functional Sensor & Actuator (CFSN), NIMS

Publisher

MDPI AG

Subject

Clinical Biochemistry,General Medicine,Analytical Chemistry,Biotechnology,Instrumentation,Biomedical Engineering,Engineering (miscellaneous)

Reference40 articles.

1. Flavor quality of fruits and vegetables;Kader;J. Sci. Food Agric.,2008

2. Advances of electronic nose and its application in fresh foods: A review;Shi;Crit. Rev. Food Sci. Nutr.,2018

3. Advances in Electronic Nose Development for Application to Agricultural Products;Jia;Food Anal. Methods,2019

4. Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review;Tan;Artif. Intell. Agric.,2020

5. Olfactory Perception: Receptors, Cells, and Circuits;Su;Cell,2009

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