scholarly journals Chemometric Discrimination of Philippine Civet Coffee Using Electronic Nose and Gas Chromatography Mass Spectrometry

2012 ◽  
Vol 47 ◽  
pp. 977-980 ◽  
Author(s):  
E. Ongo ◽  
M. Falasconi ◽  
G. Sberveglieri ◽  
A. Antonelli ◽  
G. Montevecchi ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Gas Chromatography Mass Spectrometry ◽  
Chromatography Mass Spectrometry

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.

scholarly journals Discrimination of Two Cultivars of Alpinia Officinarum Hance Using an Electronic Nose and Gas Chromatography-Mass Spectrometry Coupled with Chemometrics

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 572 ◽  
Author(s):  
Qin Long ◽  
Zhong Li ◽  
Bin Han ◽  
Hamid Gholam Hosseini ◽  
Huaying Zhou ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Principal Component ◽  
Gas Chromatography Mass Spectrometry ◽  
Volatile Components ◽  
Alpinia Officinarum ◽  
Chromatography Mass Spectrometry ◽  
Detection Technology ◽  
Highly Correlated

Background: Alpinia officinarum Hance is both an herbal medicine and a condiment, and generally has different cultivars such as Zhutou galangal and Fengwo galangal. The appearance of these A. officinarum cultivars is similar, but their chemical composition and quality are different. It is therefore important to discriminate between different A. officinarum plants to ensure the consistency of the efficacy of the medicine. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two cultivars for fast and robust discrimination. Methods: Odor and volatile components of all A. officinarum samples were detected by the E-nose and gas chromatography-mass spectrometry (GC-MS), respectively. The E-nose sensors and GC-MS data were analyzed respectively by principal component analysis (PCA), the correlation between E-nose sensors and GC-MS data were analyzed by partial least squares (PLS). Results: It was found that Zhutou galangal and Fengwo galangal can be discriminated by combining the E-nose with PCA, and the E-nose sensors S2, S6, S7, S9 were important sensors for distinguishing different cultivars of A. officinarum. A total of 56 volatile components of A. officinarum were identified by the GC-MS analysis, and the composition and content of the volatile components from the two different A. officinarum cultivars were different, in particular the relative contents of 1,8-cineole and α-farnesene. The classification result by PCA analysis based on GC-MS data was consistent with the E-nose results. The PLS analysis demonstrated that the volatile terpene, alcohol and ester components primarily interacted with the sensors S2 and S7, indicating that particular E-nose sensors were highly correlated with some aroma constituents. Conclusions: Combined with advanced chemometrics, the E-nose detection technology can discriminate two cultivars of A. officinarum, with GC-MS providing support to determine the material basis of the E-nose sensors’ response.

scholarly journals Characterization and Discrimination of Chinese Marinated Pork Hocks by Volatile Compound Profiling Using Solid Phase Microextraction Gas Chromatography-Mass Spectrometry/Olfactometry, Electronic Nose and Chemometrics

Molecules ◽  
2019 ◽  
Vol 24 (7) ◽  
pp. 1385 ◽  
Author(s):  
Dong Han ◽  
Si Mi ◽  
Chun-Hui Zhang ◽  
Juan Li ◽  
Huan-Lu Song ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Solid Phase Microextraction ◽  
Solid Phase ◽  
Principal Component ◽  
Gas Chromatography Mass Spectrometry ◽  
Active Compounds ◽  
Volatile Constituents ◽  
Chromatography Mass Spectrometry

The primary aim of this study was to investigate volatile constituents for the differentiation of Chinese marinated pork hocks from four local brands, Dahongmen (DHM), Daoxiangcun (DXC), Henghuitong (HHT) and Tianfuhao (TFH). To this end the volatile constituents were evaluated by gas chromatography-mass spectrometry/olfactometry (GC-MS/O), electronic nose (E-nose) and chemometrics. A total of 62 volatile compounds were identified and quantified in all pork hocks, and 24 of them were considered as odour-active compounds because their odour activity values (OAVs) were greater than 1. Hexanal (OAV at 3.6–20.3), octanal (OAV at 30.3–47.5), nonanal (OAV at 68.6–166.3), 1,8-cineole (OAV at 36.4–133.3), anethole (OAV at 5.9–28.3) and 2-pentylfuran (OAV at 3.5–29.7) were the key odour-active compounds contributing to the integral flavour of the marinated pork hocks. According to principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) of GC-MS/O and E-nose data, the results showed that the marinated pork hocks were clearly separated into three groups: DHM, HHT, and DXC-TFH. Nine odour-active compounds, heptanal, nonanal, 3-carene, d-limonene, β-phellandrene, p-cymene, eugenol, 2-ethylfuran and 2-pentylfuran, were determined to represent potential flavour markers for the discrimination of marinated pork hocks. This study indicated the feasibility of using GC-MS/O coupled with the E-nose method for the differentiation of the volatile profile in different brands of marinated pork hocks.

scholarly journals Determination of volatile organic compounds in Slovak bryndza cheese by the electronic nose and the headspace solid-phase microextraction gas chromatography-mass spectrometry

10.5219/1300 ◽  
2020 ◽  
Vol 14 ◽  
pp. 767-773
Author(s):  
Jana Štefániková ◽  
Július Árvay ◽  
Michal Miškeje ◽  
Miroslava Kačániová
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Solid Phase Microextraction ◽  
Solid Phase ◽  
Gas Chromatography Mass Spectrometry ◽  
Chromatography Mass Spectrometry ◽  
Volatile Organic

The aim of the present study was to describe volatile organic compounds of the traditional Slovak bryndza cheese determined by using an electronic nose (e-nose) and a gas chromatography mass spectrometry (GCMS) with head-space solid phase microextraction (HS-SPME). For the first time, e-nose based on the gas chromatography principle with a flame ionization detector was described to identify and quantify aroma active compounds of bryndza cheese from Slovakia. The e-nose detects aroma compounds of very small concentrations in real-time of a few minutes and identifies them by comparing Kovats´ retention indices with the NIST library. Bryndza cheese produced from unpasteurized ewe´s milk and from a mixture of raw ewe´s and pasteurized cow´s types of milk were collected from 2 different Slovak farms beginning in May through to September 2019. The flavour and aroma of bryndza cheese are apparently composed of compounds contained in milk and the products of fermentation of the substrate by bacteria and fungi. Regarding volatile organic compounds, 25 compounds were detected and identified by an electronic nose with a discriminant >0.900 with ethyl acetate, isopentyl acetate, 2-butanone, acetic acid, butanoic acid, and butane-2,3-dione confirmed by gas chromatography. We confirm the suitability of the electronic nose to be used for monitoring of bryndza cheese quality.

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