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Article

Classification and Identification of Essential Oils from Herbs and Fruits Based on a MOS Electronic-Nose Technology

1
Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199, Iran
2
Pathology Department, Southern Hardwoods Laboratory, Center for Forest Genetics & Ecosystems Biology, Southern Research Station, USDA Forest Service, 432 Stoneville Road, Stoneville, MS 38776, USA
3
Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland
4
Faculty of Production and Power Engineering, University of Agriculture in Kraków, Balicka 116B, 30-149 Kraków, Poland
*
Authors to whom correspondence should be addressed.
Academic Editor: Simonetta Capone
Chemosensors 2021, 9(6), 142; https://doi.org/10.3390/chemosensors9060142
Received: 19 May 2021 / Revised: 10 June 2021 / Accepted: 13 June 2021 / Published: 16 June 2021
The frequent occurrence of adulterated or counterfeit plant products sold in worldwide commercial markets has created the necessity to validate the authenticity of natural plant-derived palatable products, based on product-label composition, to certify pricing values and for regulatory quality control (QC). The necessity to confirm product authenticity before marketing has required the need for rapid-sensing, electronic devices capable of quickly evaluating plant product quality by easily measurable volatile (aroma) emissions. An experimental MAU-9 electronic nose (e-nose) system, containing a sensor array with 9 metal oxide semiconductor (MOS) gas sensors, was developed with capabilities to quickly identify and classify volatile essential oils derived from fruit and herbal edible-plant sources. The e-nose instrument was tested for efficacy to discriminate between different volatile essential oils present in gaseous emissions from purified sources of these natural food products. Several chemometric data-analysis methods, including pattern recognition algorithms, principal component analysis (PCA), and support vector machine (SVM) were utilized and compared. The classification accuracy of essential oils using PCA, LDA and QDA, and SVM methods was at or near 100%. The MAU-9 e-nose effectively distinguished between different purified essential oil aromas from herbal and fruit plant sources, based on unique e-nose sensor array responses to distinct, essential-oil specific mixtures of volatile organic compounds (VOCs). View Full-Text
Keywords: artificial olfaction; electronic nose; essential oils; plant product authentication; product adulteration testing; quality control; volatile organic compounds (VOCs) artificial olfaction; electronic nose; essential oils; plant product authentication; product adulteration testing; quality control; volatile organic compounds (VOCs)
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MDPI and ACS Style

Rasekh, M.; Karami, H.; Wilson, A.D.; Gancarz, M. Classification and Identification of Essential Oils from Herbs and Fruits Based on a MOS Electronic-Nose Technology. Chemosensors 2021, 9, 142. https://doi.org/10.3390/chemosensors9060142

AMA Style

Rasekh M, Karami H, Wilson AD, Gancarz M. Classification and Identification of Essential Oils from Herbs and Fruits Based on a MOS Electronic-Nose Technology. Chemosensors. 2021; 9(6):142. https://doi.org/10.3390/chemosensors9060142

Chicago/Turabian Style

Rasekh, Mansour, Hamed Karami, Alphus D. Wilson, and Marek Gancarz. 2021. "Classification and Identification of Essential Oils from Herbs and Fruits Based on a MOS Electronic-Nose Technology" Chemosensors 9, no. 6: 142. https://doi.org/10.3390/chemosensors9060142

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