Coupling gas chromatography and electronic nose detection for detailed cigarette smoke aroma characterization

Rambla-Alegre, Maria; Tienpont, Bart; Mitsui, Kazuhisa; Masugi, Eri; Yoshimura, Yuta; Nagata, Hisanori; David, Frank; Sandra, Pat

doi:10.1016/j.chroma.2014.09.015

Cited by 12 publications

(6 citation statements)

References 34 publications

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“…Fox 4000 Electronic Nose (Alpha M.O.S., France), Metal Oxide Sensor PCA and Discriminant factor analysis (DFA) [72] Analyze the exhaled gas of smokers at different time points to assess the effect of smoking on the VOC characteristics of exhaled gas.…”

Section: Miniaturization Low Power Consumption Fast Response Timesmentioning

confidence: 99%

Applications of electronic nose technology in the tobacco industry: a comprehensive review

Du,

Xi,

Chen

et al. 2023

Meas. Sci. Technol.

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Electronic nose (E-nose) technology has emerged as a promising tool for rapid and objective analysis of complex odor profiles in various industries, including the tobacco sector. This review paper provides a comprehensive overview of the applications of E-noses in the tobacco industry, focusing on their potential for enhancing quality control, optimizing blend formulations, monitoring processing conditions, and assuring the quality of finished products. We discuss the basic principles, working mechanisms, sensor types, and data processing techniques employed in E-noses, as well as the challenges and limitations associated with their adoption in the tobacco industry. These challenges include sensor drift, calibration, interference from environmental factors, the complexity of tobacco aroma and flavor profiles, and regulatory and ethical considerations. The paper concludes by highlighting the need for further research and development in E-nose technology, with an emphasis on addressing technical challenges, refining sensor systems, and fostering collaboration among researchers, industry stakeholders, and regulatory agencies. By overcoming these hurdles, E-nose technology has the potential to revolutionize the tobacco industry, ensuring consistent product quality, and meeting the changing demands of consumers while addressing public health concerns and regulatory requirements.

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Section: Miniaturization Low Power Consumption Fast Response Timesmentioning

confidence: 99%

Applications of electronic nose technology in the tobacco industry: a comprehensive review

Du,

Xi,

Chen

et al. 2023

Meas. Sci. Technol.

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“…Fast GC has been an active area of study for reducing analysis time and increasing sample throughput [7][8][9][10][11][12][13][14][15][16][17]. A recent review by Tranchida and Mondello [18] discusses the use of microbore capillary columns for fast GC, and another recent review by Wang et al [19] outlines the use of resistive heating for fast GC.…”

Section: Introductionmentioning

confidence: 97%

Evaluation of injection methods for fast, high peak capacity separations with low thermal mass gas chromatography

Fitz

Mannion

et al. 2015

Journal of Chromatography A

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“…Fortunately, advanced gas detection technologies, such as the portable electronic nose (E-nose), have become widely available to tackle the issues. Some researchers have applied E-nose technology to inspect the quality of food, including fruits [11,12], meat [13,14], rice [15,16], tea [17], cigarettes [18], Chinese herbal medicines [19], and others plant crops [20]. The latest reports show that an E-nose can be applied to the process of harmful gas detection [21,22,23], the medical industry [24,25], and space applications [26,27,28].…”

Section: Introductionmentioning

confidence: 99%

Classification and Identification of Industrial Gases Based on Electronic Nose Technology

Luo

Sun

et al. 2019

Sensors

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Rapid detection and identification of industrial gases is a challenging problem. They have a complex composition and different specifications. This paper presents a method based on the kernel discriminant analysis (KDA) algorithm to identify industrial gases. The smell prints of four typical industrial gases were collected by an electronic nose. The extracted features of the collected gases were employed for gas identification using different classification algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), PCA + LDA, and KDA. In order to obtain better classification results, we reduced the dimensions of the original high-dimensional data, and chose a good classifier. The KDA algorithm provided a high classification accuracy of 100% by selecting the offset of the kernel function c = 10 and the degree of freedom d = 5. It was found that this accuracy was 4.17% higher than the one obtained using PCA. In the case of standard deviation, the KDA algorithm has the highest recognition rate and the least time consumption.

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Coupling gas chromatography and electronic nose detection for detailed cigarette smoke aroma characterization

Cited by 12 publications

References 34 publications

Applications of electronic nose technology in the tobacco industry: a comprehensive review

Applications of electronic nose technology in the tobacco industry: a comprehensive review

Evaluation of injection methods for fast, high peak capacity separations with low thermal mass gas chromatography

Classification and Identification of Industrial Gases Based on Electronic Nose Technology

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