Optimization of GC-IMS parameters and determination of volatile fingerprint of flavors and fragrances using GC-IMS

To investigate the optimum parameters of gas chromatography ion mobility spectrometry (GC-IMS) in determination of flavors and fragrances in tobacco. The effects of reaction parameters such as chromatographic column temperature, incubation temperature, incubation time and injection volume are evaluated with the number of identified characteristic peaks, peak intensity and peak pacing as indexes by an orthogonal L9 (34) test. Furthermore, prediction of test results is conducted based on the PLS method. Particle Swarm Optimization (PSO) is used to optimize the parameters. The collection of 30 different flavors and fragrances are tested by GC – IMS which operation parameters are set according to optimal results. The results show that a total of 60 kinds of the volatile organic compounds (VOCs) are identified across all samples, including aldehydes, ketones, alcohols, esters, ethers and so on. Therefore, by means of fingerprints can infer the general composition of fragrance-base or distinguish flavors and fragrances.

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Publication Details

Journal
CyTA - Journal of Food
Published
2024-08-30
DOI
https://doi.org/10.1080/19476337.2024.2386422
Citations
7
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
1.29

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article

Optimization of GC-IMS parameters and determination of volatile fingerprint of flavors and fragrances using GC-IMS

Bin Chen, Dechun Geng, Yujia Huo, Daoli Lu et al.
7 citations
CyTA - Journal of Food
Advanced Chemical Sensor Technologies
1.29
article

Optimization of GC-IMS parameters and determination of volatile fingerprint of flavors and fragrances using GC-IMS

Bin Chen, Dechun Geng, Yujia Huo, Daoli Lu, Xinyu Chen, Jing Jin
article en
7 citations

Abstract

To investigate the optimum parameters of gas chromatography ion mobility spectrometry (GC-IMS) in determination of flavors and fragrances in tobacco. The effects of reaction parameters such as chromatographic column temperature, incubation temperature, incubation time and injection volume are evaluated with the number of identified characteristic peaks, peak intensity and peak pacing as indexes by an orthogonal L9 (34) test. Furthermore, prediction of test results is conducted based on the PLS method. Particle Swarm Optimization (PSO) is used to optimize the parameters. The collection of 30 different flavors and fragrances are tested by GC – IMS which operation parameters are set according to optimal results. The results show that a total of 60 kinds of the volatile organic compounds (VOCs) are identified across all samples, including aldehydes, ketones, alcohols, esters, ethers and so on. Therefore, by means of fingerprints can infer the general composition of fragrance-base or distinguish flavors and fragrances.

CyTA - Journal of FoodVol. 22(1)
Jiangsu University (CN), China Tobacco (CN), University of Duisburg-Essen (DE)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 22%
Advanced Chemical Sensor Technologies
1.29
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Optimization of GC-IMS parameters and determination of volatile fingerprint of flavors and fragrances using GC-IMS — Bin Chen, Dechun Geng, et al. · CyTA - Journal of Food (2024) | TGRS Research Map | TGRS