Non-contact identification of essential oils with IR sensors and analysis of components with an electronic nose

Abstract In this study, the odour values of rosemary, mint, black cumin, lavender, and thyme oils were determined by an electronic nose working with an Arduino microprocessor. The components of the plants were compared with the sensor data, and the most sensitive sensors were determined by sorting according to the highest components. The study data indicated that the MQ3 sensor exhibited the highest sensitivity for thyme, black cumin, and lavender oils, which contain 63% carvacrol, 38% thymoquinone, and 36% linalool, respectively. Also, MQ7 was the most sensitive sensor for menthone (68%) in mint oil and eucalyptol (45%) in rosemary oil. In addition, a low-cost and non-contact device that works with an infrared sensor has been developed to detect the identity of the oil added into the vial. The study data showed that low-cost Arduino-based IR and odour sensors can determine the identity and component percentage of oils. The fact that the developed device can detect with 100 percent accuracy even in case of peppermint and rosemary oils, which are very similar in appearance, shows that the study data will be an inspiration for contactless determination of oil quality and type.

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Publication Details

Journal
Acta Alimentaria
Published
2024-08-26
DOI
https://doi.org/10.1556/066.2024.00117
Citations
2
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
0.37
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article

Non-contact identification of essential oils with IR sensors and analysis of components with an electronic nose

Emre Yavuzer, Hasan Uslu, Muhammet Köse, M.K. Yalçın
2 citations
Acta Alimentaria
Advanced Chemical Sensor Technologies
0.37
article

Non-contact identification of essential oils with IR sensors and analysis of components with an electronic nose

Emre Yavuzer, Hasan Uslu, Muhammet Köse, M.K. Yalçın
article en
2 citations

Abstract

Abstract In this study, the odour values of rosemary, mint, black cumin, lavender, and thyme oils were determined by an electronic nose working with an Arduino microprocessor. The components of the plants were compared with the sensor data, and the most sensitive sensors were determined by sorting according to the highest components. The study data indicated that the MQ3 sensor exhibited the highest sensitivity for thyme, black cumin, and lavender oils, which contain 63% carvacrol, 38% thymoquinone, and 36% linalool, respectively. Also, MQ7 was the most sensitive sensor for menthone (68%) in mint oil and eucalyptol (45%) in rosemary oil. In addition, a low-cost and non-contact device that works with an infrared sensor has been developed to detect the identity of the oil added into the vial. The study data showed that low-cost Arduino-based IR and odour sensors can determine the identity and component percentage of oils. The fact that the developed device can detect with 100 percent accuracy even in case of peppermint and rosemary oils, which are very similar in appearance, shows that the study data will be an inspiration for contactless determination of oil quality and type.

Acta AlimentariaVol. 53(3)
Niğde Ömer Halisdemir Üniversitesi (TR), Ahi Evran University (TR)
Openalex Percentile: Top 44%
Advanced Chemical Sensor Technologies
0.37
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Non-contact identification of essential oils with IR sensors and analysis of components with an electronic nose — Emre Yavuzer, Hasan Uslu, et al. · Acta Alimentaria (2024) | TGRS Research Map | TGRS