Publication: Monitoring of microbial canned food spoilage and contamination based on e-nose for smart home
Issued Date
2015-08-17
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2-s2.0-84957025555
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Mahidol University
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SCOPUS
Bibliographic Citation
ECTI-CON 2015 - 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology. (2015)
Suggested Citation
Phunvira Chongthanaphisut, Thara Seesaard, Teerakiat Kerdcharoen Monitoring of microbial canned food spoilage and contamination based on e-nose for smart home. ECTI-CON 2015 - 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology. (2015). doi:10.1109/ECTICon.2015.7206960 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/35805
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Title
Monitoring of microbial canned food spoilage and contamination based on e-nose for smart home
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Abstract
© 2015 IEEE. In this paper, we have developed an electronic nose (e-nose) consisting of four gas sensors based on functionalized single-walled carbon nanotubes (f-SWNTs) and polymer nanocomposites, aiming to be a convenient monitoring device for microbial spoilage and contaminants in canned food. The gas sensing signals were used as early indicators of the spoilage to help prevent harmful effects on human's health. The gas sensor array has been tested to observe the specific response with various volatile organic compounds (VOCs) in a static system. These sensors are appropriate for detecting the microbial spoilage of canned food because they show a good sensing response to ammonia, which is one of the gases produced from micro-organisms. Canned tuna in mineral water, which was used as our sample, was opened and placed at room temperature (25°C). Then, the odor associated with the spoilage of canned tuna was monitored by e-nose for ten days. Discrimination of microbial canned tuna spoilage status and analysis of the smell-print of specific level of ammonia contamination were visualized using principal component analysis (PCA), which was found to be able to track changes in the canned tuna deterioration, thereby showing its potential to be applied for quality assurance of canned food in daily life of a person living in a smart home.