Sub-PPB Detection with Gas-Phase Multiphoton Electron Extraction Spectroscopy under Ambient Conditions.

Multiphoton electron extraction spectroscopy (MEES) is an advanced analytical technique that has demonstrated exceptional sensitivity and specificity for detecting molecular traces on solid and liquid surfaces. Building upon the solid-state MEES foundations, this study introduces the first application of MEES in the gas phase (gas-phase MEES), specifically designed for quantitative detection of gas traces at sub-part per billion (sub-PPB) concentrations under ambient atmospheric conditions. Our experimental setup utilizes resonant multiphoton ionization processes using ns laser pulses under a high electrical field. The generated photoelectron charges are recorded as a function of the laser's wavelength. This research showcases the high sensitivity of gas-phase MEES, achieving high spectral resolution with resonant peak widths less than 0.02 nm FWHM. We present results from quantitative analysis of benzene and aniline, two industrially and environmentally significant compounds, demonstrating linear responses in the sub-PPM and sub-PPB ranges. The enhanced sensitivity and resolution of gas-phase MEES offer a powerful approach to trace gas analysis, with potential applications in environmental monitoring, industrial safety, security screening, and medical diagnostics. This study confirms the advantages of gas-phase MEES over many traditional optical spectroscopic methods and demonstrates its potential in direct gas-trace sensing in ambient atmosphere.

Volatile-Based Diagnosis for Pathogenic Wood-Rot Fungus Fulvifomes siamensis by Electronic Nose (E-Nose) and Solid-Phase Microextraction/Gas Chromatography/Mass Spectrometry.

Wood rot fungus Fulvifomes siamensis infects multiple urban tree species commonly planted in Singapore. A commercial e-nose (Cyranose 320) was used to differentiate some plant and fungi volatiles. The e-nose distinctly clustered the volatiles at 0.25 ppm, and this sensitivity was further increased to 0.05 ppm with the use of nitrogen gas to purge the system and set up the baseline. Nitrogen gas baseline resulted in a higher magnitude of sensor responses and a higher number of responsive sensors. The specificity of the e-nose for F. siamensis was demonstrated by distinctive clustering of its pure culture, fruiting bodies collected from different tree species, and in diseased tissues infected by F. siamensis with a 15-min incubation time. This good specificity was supported by the unique volatile profiles revealed by SPME GC-MS analysis, which also identified the signature volatile for F. siamensis-1,2,4,5-tetrachloro-3,6-dimethoxybenzene. In field conditions, the e-nose successfully identified F. siamensis fruiting bodies on different tree species. The findings of concentration-based clustering and host-tree-specific volatile profiles for fruiting bodies provide further insights into the complexity of volatile-based diagnosis that should be taken into consideration for future studies.

High Density Resistive Array Readout System for Wearable Electronics.

This work presents a wearable sensing system for high-density resistive array readout. The system comprising readout electronics for a high-density resistive sensor array and a rechargeable battery, was realized in a wristband. The analyzed data with the proposed system can be visualized using a custom graphical user interface (GUI) developed in a personal computer (PC) through a universal serial bus (USB) and using an Android app in smartphones via Bluetooth Low Energy (BLE), respectively. The readout electronics were implemented on a printed circuit board (PCB) and had a compact dimension of 3 cm × 3 cm. It was designed to measure the resistive sensor with a dynamic range of 1 KΩ-1 MΩ and detect a 0.1% change of the base resistance. The system operated at a 5 V supply voltage, and the overall system power consumption was 95 mW. The readout circuit employed a resistance-to-voltage (R-V) conversion topology using a 16-bit analog-to-digital converter (ADC), integrated in the Cypress Programmable System-on-Chip (PSoC®) 5LP microcontroller. The device behaves as a universal-type sensing system that can be interfaced with a wide variety of resistive sensors, including chemiresistors, piezoresistors, and thermoelectric sensors, whose resistance variations fall in the target measurement range of 1 KΩ-1 MΩ. The system performance was tested with a 60-resistor array and showed a satisfactory accuracy, with a worst-case error rate up to 2.5%. The developed sensing system shows promising results for applications in the field of the Internet of things (IoT), point-of-care testing (PoCT), and low-cost wearable devices.

Comparison of Cheese Aroma Intensity Measured Using an Electronic Nose (E-Nose) Non-Destructively with the Aroma Intensity Scores of a Sensory Evaluation: A Pilot Study.

Cheese aroma is known to affect consumer preference. One of the methods to measure cheese aroma is the use of an electronic nose (e-nose), which has been used to classify cheese types, production areas, and cheese ages. However, few studies have directly compared the aroma intensity scores derived from sensory evaluations with the values of metal oxide semiconductor sensors that can easily measure the aroma intensity. This pilot study aimed to investigate the relationship between sensory evaluation scores and e-nose values with respect to cheese aroma. Five types of processed cheese (two types of normal processed cheese, one type containing aged cheese, and two types containing blue cheese), and one type of natural cheese were used as samples. The sensor values obtained using the electronic nose, which measured sample aroma non-destructively, and five sensory evaluation scores related to aroma (aroma intensity before intake, during mastication, and after swallowing; taste intensity during mastication; and remaining flavor after swallowing (lasting flavor)) determined by six panelists, were compared. The e-nose values of many of the tested cheese types were significantly different, whereas the sensory scores of the one or two types of processed cheese containing blue cheese and those of the natural cheese were significantly different. Significant correlations were observed between the means of e-nose values and the medians of aroma intensity scores derived from the sensory evaluation testing before intake, during mastication, and after swallowing. In particular, the aroma intensity score during mastication was found to have a linear relationship with the e-nose values (Pearson's R = 0.983). In conclusion, the e-nose values correlated with the sensory scores with respect to cheese aroma intensity and could be helpful in predicting them.

Analysis of Volatile Compounds in Sea Bass (Lateolabrax japonicus) Resulting from Different Slaughter Methods Using Electronic-Nose (E-Nose) and Gas Chromatography-Ion Mobility Spectrometry.

Sea bass (Lateolabrax japonicus) is known for its unique flavor and high nutritional value. In this study, the influence of slaughter methods on the volatile compounds (VOCs) in sea bass was investigated using electronic nose (E-nose) technology and gas chromatography-ion mobility spectrometry (GC-IMS). VOCs in raw and cooked sea bass resulting from different slaughter methods were effectively distinguished using both techniques. Aldehydes, ketones, and alcohols were associated with the basic flavor of sea bass, whereas esters, organic acids, and furans enriched the aroma. In raw sea bass, the fishy odor was the strongest in the HSD group (head shot control death), followed by that in the IFD (ice faint to death) and BDS (bloodletting to death) groups. The VOC content increased and stabilized after steaming, enhancing pleasant odors such as fatty and fruity aromas. In cooked sea bass, the content of diacetyl and ethanol was the highest in the EAD group (eugenol anesthesia to death), which may be a residue of eugenol, imparting a distinct irritating chemical odor. Furthermore, abundant (E)-2-octenal, 2-heptanone, benzaldehyde, and esters in the BDS group imparted a strong, pleasant aroma. The findings indicate that heart puncture and bloodletting is the preferred slaughter method to maintain sea bass quality, providing new insights into the volatile changes in sea bass induced by different slaughter methods.

Comparison of Volatiles in Different Jasmine Tea Grade Samples Using Electronic Nose and Automatic Thermal Desorption-Gas Chromatography-Mass Spectrometry Followed by Multivariate Statistical Analysis.

Chinese jasmine tea is a type of flower-scented tea, which is produced by mixing green tea with the Jasminum sambac flower repeatedly. Both the total amount and composition of volatiles absorbed from the Jasminum sambac flower are mostly responsible for its sensory quality grade. This study aims to compare volatile organic compound (VOC) differences in authoritative jasmine tea grade samples. Automatic thermal desorption-gas-chromatography-mass spectrometry (ATD-GC-MS) and electronic nose (E-nose), followed by multivariate data analysis is conducted. Consequently, specific VOCs with a positive or negative correlation to the grades are screened out. Partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) show a satisfactory discriminant effect on rank. It is intriguing to find that the E-nose is good at distinguishing the grade difference caused by VOC concentrations but is deficient in identifying essential aromas that attribute to the unique characteristics of excellent grade jasmine tea.

Antioxidant activity screening and chemical constituents of the essential oil from rosemary by ultra-fast GC electronic nose coupled with chemical methodology.

BACKGROUND: Traditional chemical methods were mainly used to evaluate the total antioxidant activity of essential oils. How to determine the bioactivity of each compound in mixtures is an interesting research topic. Nowadays, an ultra-fast gas chromatography electronic nose (E-nose) has been gradually used in the detection of volatile compounds, but the screening of the active components of essential oils has not been reported. E-nose coupled with chemical methodology was established using the essential oil from rosemary (EOR) as a specific application example. The proposed method can both identify the chemical constituents of EOR and quickly screen the antioxidant by comparing the change of chromatographic peak area of every component in EOR before and after reaction with free radicals. RESULTS: Among all chemical constituents in EOR, verbenone, eucalyptol and o-cymene showed the strongest scavenging abilities in 1,1'-diphenyl-2-picrylhydrazine (DPPH·), 2,2'-azino-bis(3-ethyl-benzothiazoline-6-sulphonate) (ABTS·+ ) and hydroxyl (·OH) radicals, respectively, with scavenging rates of 67.9%, 39.5%, and 69.9%. The reliability and feasibility of using E-nose to identify chemical constituents of EOR were verified by gas chromatography-tandem mass spectrometry (GC-MS/MS). The GC-MS/MS results showed that the main components of EOR were α-pinene (422.2 µg g-1 ), p-cymene (208.4 µg g-1 ), camphor (203.5 µg g-1 ), verbenone (160.2 µg g-1 ), and eucalyptol (129.1 µg g-1 ). CONCLUSIONS: The E-nose methods can be used as a complementary method to traditional spectrophotometric techniques. Furthermore, this study will be of great significance for the rapid screening of antioxidant active components in essential oils from natural products. © 2020 Society of Chemical Industry.

A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose.

Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.

Development of a Dual MOS Electronic Nose/Camera System for Improving Fruit Ripeness Classification.

Electronic nose (E-nose) systems have become popular in food and fruit quality evaluation because of their rapid and repeatable availability and robustness. In this paper, we propose an E-nose system that has potential as a non-destructive system for monitoring variation in the volatile organic compounds produced by fruit during the maturing process. In addition to the E-nose system, we also propose a camera system to monitor the peel color of fruit as another feature for identification. By incorporating E-nose and camera systems together, we propose a non-destructive solution for fruit maturity monitoring. The dual E-nose/camera system presents the best Fisher class separability measure and shows a perfect classification of the four maturity stages of a banana: Unripe, half-ripe, fully ripe, and overripe.

Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array.

INTRODUCTION: Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning. METHODS: Patients who underwent lung cancer surgery at an academic medical center, Japan, between November 2018 and November 2019 were included. Exhaled breaths were collected just before surgery and about one month after surgery, and analyzed using an MSS array. The array had 12 channels with various receptor materials and provided 12 waveforms from a single exhaled breath sample. Boxplots of the perioperative changes in the expiratory waveforms of each channel were generated and Mann-Whitney U test were performed. An optimal lung cancer prediction model was created and validated using machine learning. RESULTS: Sixty-six patients were enrolled of whom 57 were included in the analysis. Through the comprehensive analysis of the entire dataset, a prototype model for predicting lung cancer was created from the combination of array five channels. The optimal accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.809, 0.830, 0.807, 0.806, and 0.812, respectively. CONCLUSION: Breath analysis with MSS and machine learning with careful control of both samples and measurement conditions provided a lung cancer prediction model, demonstrating its capacity for non-invasive screening of lung cancer.

Electronic nose versus VITEK 2 system for the rapid diagnosis of bloodstream infections.

Infectious diseases that spread through the bloodstream, known as bloodstream infections (BSIs), are a major global health problem. Positive outcomes for patients with sepsis are typically the result of prompt treatment started after an early diagnosis of BSIs. In this study, we evaluated the capabilities of a portable electronic nose (E-Nose) to detect BSIs with two commonly isolated Gram-negative bacterial species, E. coli and K. pneumonia. One hundred and five blood samples were randomly collected for blood culture examinations using BACTEC and VITEK 2 system, and headspace analysis by an E-Nose from June to December 2021. Classification accuracy of E. coli, K. pneumonia, and negative controls was measured using principal component analysis, area under the receiver operating characteristic curve, sensitivity, and specificity analysis. After incubation for 24 h, cluster plots generated using principal component analysis demonstrated that E-Nose could accurately diagnose the presence of E. coli and K. pneumonia in BACTEC blood culture bottles with a sensitivity and specificity of 100% in just 120 s. The E-Nose method has been shown to be an immediate, precise, and cost-effective alternative to automated blood culture BACTEC and VITEK 2 systems for the fast detection of the causative bacterial pathogens of BSIs in clinical practice. Thus, patients with such Gram-negative bacteremia can have guided empirical antimicrobial therapy on the same day of BSIs diagnosis, which can be lifesaving.

Study on the Development and Functional Characteristics of Salted Egg with Liquid Smoke.

In this study, the duck eggs were salted with none or 2.5% and 5.0% (v/v) of liquid smoke (LS), respectively. As a control, samples salted without LS were used. The 2-thiobarbituric acid (TBA) values, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging ability, and reducing power of the three groups were tested at 0, 7, 14, and 21 and 28 days to determine the effects of LS on the antioxidant activity of treated eggs. In addition, gas chromatography-mass spectrometry (GC-MS) and electronic nose (E-Nose) were used to analyze the volatile flavor components of fresh duck eggs, LS, control, and salted duck eggs enriched with 2.5% (v/v) LS after 28 days of salting. The TBA value considerably increased with an increase in salting period, and the treated egg's TBA value significantly associated with LS concentration. The TBA value decreased as the LS concentration increased. The amount of LS present was highly associated with their capacity to scavenge DPPH radicals. The reducing power of the samples was substantially correlated with the LS concentration, and the reducing power increased with increasing LS concentration. The GC-MS data revealed that phenols and ketones were the predominant chemicals present in the LS, and they were also found in the eggs added to the LS even though they were absent in the fresh eggs and control. The flavor of the control group and treated eggs with LS differed significantly, according to the principal component analysis and radar map of the E-nose. The texture study results revealed that the LS significantly impacted the hardness, cohesiveness, and chewiness of eggs.

Breath VOC analysis and machine learning approaches for disease screening: a review.

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

Measurement of Volatile Fatty Acids in Silage through Odors with Nanomechanical Sensors.

The measurement of volatile fatty acids (VFAs) is of great importance in the fields of food and agriculture. There are various methods to measure VFAs, but most methods require specific equipment, making on-site measurements difficult. In this work, we demonstrate the measurements of VFAs in a model sample, silage, through its vapor using an array of nanomechanical sensors-Membrane-type Surface stress Sensors (MSS). Focusing on relatively slow desorption behaviors of VFAs predicted with the sorption kinetics of nanomechanical sensing and the dissociation nature of VFAs, the VFAs can be efficiently measured by using features extracted from the decay curves of the sensing response, resulting in sufficient discrimination of the silage samples. Since the present sensing system does not require expensive, bulky setup and pre-treatment of samples, it has a great potential for practical applications including on-site measurements.

Remove Non-hydrated Phospholipids in Okra Seed Oil by Silicon Dioxide.

Water degumming, mainly removes hydrated phospholipids, is the most common method applying in traditional edible oil production. Silicon dioxide (SiO2) adsorption has been proved as a green and efficient method for removing phospholipids from rapeseed oil. But both methods exhibited poor effect on okra seed oil. Based on a hypothesis that SiO2 can adsorb non-hydrated phospholipids, removal effect of non-hydrated phospholipids in okra seed oil was studied. Single factor test and response surface design were used to optimize the SiO2 adsorbing process in water-degummed oil. Meanwhile, the qualities and flavor changes of okra seed oil before and after degumming were compared and analyzed. The results showed that the optimized degumming procedure was: 1.43% (w/w) of SiO2 added into the water-degummed oil, and the mixture was stirred at 33.52℃ for 30.47 min. The maximum non-hydrated phospholipids removal rate reached 43.3%. Comparing with crude okra seed oil, the optimal degumming method resulted in the increase of peroxide value and the decrease of induction period (IP) of the oil. However, it had the same safety as the water and the SiO2 degumming methods. It could retain 62% of total phenols, which was less than the water and the SiO2 degumming methods (both about 79%). The differences of E-nose sensors among oils were most likely caused by the pyrazines. It is necessary to study the composition and properties of phospholipids and develop new methods to further improve the phospholipids removal rate of okra seed oil.

Artificial Olfactory Neuron for an In-Sensor Neuromorphic Nose.

A neuromorphic module of an electronic nose (E-nose) is demonstrated by hybridizing a chemoresistive gas sensor made of a semiconductor metal oxide (SMO) and a single transistor neuron (1T-neuron) made of a metal-oxide-semiconductor field-effect transistor (MOSFET). By mimicking a biological olfactory neuron, it simultaneously detects a gas and encoded spike signals for in-sensor neuromorphic functioning. It identifies an odor source by analyzing the complicated mixed signals using a spiking neural network (SNN). The proposed E-nose does not require conversion circuits, which are essential for processing the sensory signals between the sensor array and processors in the conventional bulky E-nose. In addition, they do not have to include a central processing unit (CPU) and memory, which are required for von Neumann computing. The spike transmission of the biological olfactory system, which is known to be the main factor for reducing power consumption, is realized with the SNN for power savings compared to the conventional E-nose with a deep neural network (DNN). Therefore, the proposed neuromorphic E-nose is promising for application to Internet of Things (IoT), which demands a highly scalable and energy-efficient system. As a practical example, it is employed as an electronic sommelier by classifying different types of wines.

Volatolomic urinary profile analysis for diagnosis of the early stage of lung cancer.

Currently, in clinical practice there is a pressing need for potential biomarkers that can identify lung cancer at early stage before becoming symptomatic or detectable by conventional means. Several researchers have independently pointed out that the volatile organic compounds (VOCs) profile can be considered as a lung cancer fingerprint useful for diagnosis. In particular, 16% of volatiles contributing to the human volatilome are found in urine, which is therefore an ideal sample medium. Its analysis through non-invasive, relatively low-cost and straightforward techniques could offer great potential for the early diagnosis of lung cancer. In this study, urinary VOCs were analysed with a gas chromatography-ion mobility spectrometer (GC-IMS) and an electronic nose (e-nose) made by a matrix of twelve quartz microbalances complemented by a photoionization detector. This clinical prospective study involved 127 individuals, divided into two groups: 46 with lung cancer stage I-II-III confirmed by computerized tomography or positron emission tomography-imaging techniques and histology (biopsy), and 81 healthy controls. Both instruments provided a multivariate signal which, after being analysed by a machine learning algorithm, identified eight VOCs that could distinguish lung cancer patients from healthy ones. The eight VOCs are 2-pentanone, 2-hexenal, 2-hexen-1-ol, hept-4-en-2-ol, 2-heptanone, 3-octen-2-one, 4-methylpentanol, 4-methyl-octane. Results show that GC-IMS identifies lung cancer with respect to the control group with a diagnostic accuracy of 88%. Sensitivity resulted as being 85%, and specificity was 90%-Area Under the Receiver Operating Characteristics: 0.91. The contribution made by the e-nose was also important, even though the results were slightly less sensitive with an accuracy of 71.6%. Moreover, of the eight VOCs identified as potential biomarkers, five VOCs had a high sensitivity (p⩽ 0.06) for early stage (stage I) lung cancer.

Identification and characterization of volatile compounds in Lentinula edodes during vacuum freeze-drying.

In this study, modified headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) and electronic nose (E-nose) were utilized to investigate the dynamic aroma changes of Lentinula edodes (L. edodes) at different stages of vacuum freeze drying (VFD). The extraction efficiency of volatile compounds from vacuum freeze-dried L. edodes was improved by optimizing five parameters of the HS-SPME. A total of 50 volatiles were identified in L. edodes from different VFD stages by GC-MS. Alcohols, aldehydes, and volatile sulfur-containing compounds (VSCs) were the main flavor constituents of fresh L. edodes, frozen L. edodes, and secondary dried L. edodes. Aldehydes, ketones, and VSCs were the main aroma groups in L. edodes after primary drying. There were 20 volatiles as key odorants with the odor activity values greater than 1, in which esters appeared only before secondary drying of L. edodes. These findings could contribute to a comprehensive insight into the formation mechanism of flavor in the VFD process of L. edodes. PRACTICAL APPLICATIONS: Lentinula edodes is the second most widely cultivated edible fungus worldwide. It is considered a valuable health food not just because of its abundance of nutrients but also because of its delicious taste. This study investigated the regularity regarding the changes of volatile compounds in L. edodes during vacuum freeze drying. The results of the present study offer valuable knowledge for the formation mechanism of volatile substances in the drying process of L. edodes, which can be beneficial to promote the development and utilization of flavor substances in L. edodes.

Electronic-Nose as Non-destructive Tool to Discriminate "Ferrovia" Sweet Cherries Cold Stored in Air or Packed in High CO2 Modified Atmospheres.

This study aimed to explore the applicability of electronic-nose (E-nose) as a rapid method in discriminating samples of sweet cherry cv "Ferrovia" stored in high-CO2 (16% O2 + 20% CO2 + 64% N2) or air (control) up to 21 days. Projection to Latent Structures (PLS) methods applied to E-nose data showed that fresh fruit and the packaged or unpackaged samples can be distinguished, according to both the storage condition and the storage days. Moreover, a correlation analysis between E-nose sensors and 45 volatile compounds were overall, obtained from all the investigated sweet cherry samples by Headspace Solid-Phase Microextraction (HS SPME) coupled to Gas Chromatography-Mass Spectrometry (GC-MS). These methods allowed to associate samples with a specific flavour profile to one or more E-nose sensors. Finally, quality attributes (visual quality, colour, firmness, antioxidant activity, total phenols, and sugar content) were assessed during storage. Among these, visual quality and berry deformation resulted affected by storage conditions, showing that high-CO2 treatment better preserved the fruit quality than control.

Antioxidant compound screening and chemical composition of sweet ginger (Alpinia coriandriodora D. Fang) essential oil and the mechanism of scavenging radicals.

The chemical components of an edible spice, sweet ginger (Alpinia coriandriodora D. Fang) essential oil (AEO) were identified by an ultra-fast gas chromatography electronic nose (E-nose) and the main components were ß-pinene (27.9%), 1,8-cineole (17.3%), p-cymene (13.5%), camphene (7.3%), myrcene (5.4%), and pseudolimonene (4.3%). The antioxidant activity of each component was evaluated and the mechanisms of scavenging free radical were studied by E-nose combined with chemical methodology. Decanal and α-copaene in AEO showed strong scavenging activities against DPPH radical, and the scavenging rates were over 85%. Decanal had a strong scavenging activity for ABTS radical and the scavenging rate was more than 60%. Similarly, terpinen-4-ol and eugenol had strong scavenging abilities to OH radical and the scavenging rates were more than 50%. Gas chromatography-mass spectrography results showed that it was feasible to identify the chemical components of essential oil by E-nose, and the similarity reached 88.9%. PRACTICAL APPLICATIONS: Many essential oils have antioxidant activities and can be used in functional foods. In the present work, the antioxidant active components in AEO were identified and screened by ultra-fast GC E-nose. We aimed to target the components with strong antioxidant activity quickly and efficiently through the analysis of the reaction process of DPPH, ABTS and OH radicals with a high scavenging rate in a short time. These results indicate that ultra-fast GC E-nose can be used to screen the antioxidant active components in the essential oil.