scholarly journals Recording the Fragrance of 15 Types of Medicinal Herbs and Comparing Them by Similarity Using the Electronic Nose FF-2A

Chemosensors ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 20
Author(s):  
Emi Tsuchitani ◽  
Mayumi Nomura ◽  
Miyuki Ota ◽  
Erika Osada ◽  
Nobutake Akiyama ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Human Body ◽  
Complex Mixture ◽  
Medicinal Herbs ◽  
Gas Chromatography Mass Spectrometry ◽  
Absolute Value ◽  
Reference Axis ◽  
Human Sense

Medical herbs have been recognized till now as having different constituents that act on the human body. However, the fragrance of herbs is a complex mixture of odors, which makes it difficult to qualify or quantify the scent objectively on the human sense of smell. In this study, aromas of 15 medicinal herbs were recorded using an electronic nose FF-2A, and their characteristics were compared with aroma samples of wine such as Le Nez du Vin, to determine which wine aromas are similar to each medicinal herb. Thereafter, the aromas of the 15 herbs were standardized to create a reference axis for the aroma of each herb, and the similarity of tea herbs to the reference axis was examined. Additionally, the results were compared with those obtained by gas chromatography-mass spectrometry (GC-MS). In FF-2A, the measured scent is recorded as an absolute value. We succeeded in calculating the similarity of the scents of other herbs with the axes of the scent of each herb by standardizing their scents and creating new axis data. Conversely, although GC-MS is able to identify the components and concentrations of fragrances, an electronic nose can analyze fragrances in a way that is uncommon with GC-MS, such as comparison of similarities between fragrances.

scholarly journals Detecting Pulmonary Oxygen Toxicity Using eNose Technology and Associations between Electronic Nose and Gas Chromatography–Mass Spectrometry Data

Metabolites ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 286
Author(s):  
Thijs T. Wingelaar ◽  
Paul Brinkman ◽  
Rianne de Vries ◽  
Pieter-Jan A.M. van Ooij ◽  
Rigo Hoencamp ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Oxygen Toxicity ◽  
Partial Least Square ◽  
Least Square ◽  
Sensor Data ◽  
Gas Chromatography Mass Spectrometry ◽  
Exhaled Breath ◽  
Chromatography Mass Spectrometry

Exposure to oxygen under increased atmospheric pressures can induce pulmonary oxygen toxicity (POT). Exhaled breath analysis using gas chromatography–mass spectrometry (GC–MS) has revealed that volatile organic compounds (VOCs) are associated with inflammation and lipoperoxidation after hyperbaric–hyperoxic exposure. Electronic nose (eNose) technology would be more suited for the detection of POT, since it is less time and resource consuming. However, it is unknown whether eNose technology can detect POT and whether eNose sensor data can be associated with VOCs of interest. In this randomized cross-over trial, the exhaled breath from divers who had made two dives of 1 h to 192.5 kPa (a depth of 9 m) with either 100% oxygen or compressed air was analyzed, at several time points, using GC–MS and eNose. We used a partial least square discriminant analysis, eNose discriminated oxygen and air dives at 30 min post dive with an area under the receiver operating characteristics curve of 79.9% (95%CI: 61.1–98.6; p = 0.003). A two-way orthogonal partial least square regression (O2PLS) model analysis revealed an R² of 0.50 between targeted VOCs obtained by GC–MS and eNose sensor data. The contribution of each sensor to the detection of targeted VOCs was also assessed using O2PLS. When all GC–MS fragments were included in the O2PLS model, this resulted in an R² of 0.08. Thus, eNose could detect POT 30 min post dive, and the correlation between targeted VOCs and eNose data could be assessed using O2PLS.

scholarly journals Rapid Non-Destructive Quantification of Eugenol in Curdlan Biofilms by Electronic Nose Combined with Gas Chromatography-Mass Spectrometry

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4441
Author(s):  
Lu Han ◽  
Jingyi Zhu ◽  
Xia Fan ◽  
Chong Zhang ◽  
Kang Tu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Prediction Model ◽  
Electronic Nose ◽  
Quantitative Method ◽  
Gas Chromatography Mass Spectrometry ◽  
Support Vector ◽  
Linear Discriminant ◽  
Chromatography Mass Spectrometry ◽  
Non Destructive

Eugenol is hepatotoxic and potentially hazardous to human health. This paper reports on a rapid non-destructive quantitative method for the determination of eugenol concentration in curdlan (CD) biofilms by electronic nose (E-nose) combined with gas chromatography-mass spectrometry (GC-MS). Different concentrations of eugenol were added to the film-forming solution to form a series of biofilms by casting method, and the actual eugenol concentration in the biofilm was determined. Analysis of the odor collected on the biofilms was carried out by GC-MS and an E-nose. The E-nose data was subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) in order to establish a discriminant model for determining eugenol concentrations in the biofilms. Further analyses involving the application of all sensors and featured sensors, the prediction model-based partial least squares (PLS) and support vector machines (SVM) were carried out to determine eugenol concentration in the CD biofilms. The results showed that the optimal prediction model for eugenol concentration was obtained by PLS at R2p of 0.952 using 10 sensors. The study described a rapid, non-destructive detection and quantitative method for determining eugenol concentration in bio-based packaging materials.

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