Proposal of a Gas Sensor-Based Device for Detecting Adulteration in Essential Oil of Cistus ladanifer

Essential oils are a valuable raw material for several industries. Low-cost methods cannot detect its adulteration; specialised equipment is required. In this paper, we proposed the use of gas sensors to detect the adulteration process in the essential oil of Cistus ladanifer. Gas sensors are used i...

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Veröffentlicht in:Sustainability 2023-02, Vol.15 (4), p.3357
Hauptverfasser: Viciano-Tudela, Sandra, Sendra, Sandra, Parra, Lorena, Jimenez, Jose M., Lloret, Jaime
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Sprache:eng
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Zusammenfassung:Essential oils are a valuable raw material for several industries. Low-cost methods cannot detect its adulteration; specialised equipment is required. In this paper, we proposed the use of gas sensors to detect the adulteration process in the essential oil of Cistus ladanifer. Gas sensors are used in a measuring chamber to measure pure and adulterated oils. We compare the suitability of the tested sensors for detecting adulterated oil and the required measuring time. A total of five samples are determined, with a measuring time of 12 h. Each gas sensor is configured to be sensitive to different compounds. Even though sensors are not specific to detect the volatile organic compounds (VOCs) present in the essential oil, our objective is to evaluate if these VOCs might interact with the sensors as an interferent. Results indicate that various gas sensors sensitive to the same chemical compound offered different values. It might indicate that the interaction of VOCs is different among the tested sensors or that the location of the sensors and the heterogeneous distribution of VOCs along the measurement chamber impact the data. Regarding the performed analyses, we can affirm that identifying the adulterated essential oil is possible using the generated data. Moreover, the results suggest that most of the data, even for different compounds and sensors, are highly correlated, allowing a reduction in the studied variables. According to the high correlation, data are reduced, and 100% of correct classification can be obtained even when only the MQ3 and MQ8 are used.
ISSN:2071-1050
2071-1050
DOI:10.3390/su15043357