Unraveling the Difference in the Composition/Content of the Aroma Compounds in Different Tobacco Leaves: For Better Use

Yan, Tiejun; Zhou, Ping; Long, Fei; Liu, Jing; Wu, Fengguang; Zhang, Maolin; Liu, Jialei

doi:https://doi.org/10.1155/2022/3293899

Journal of Chemistry

On this page

Abstract Introduction Materials and Methods Results and Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2022 | Article ID 3293899 | https://doi.org/10.1155/2022/3293899

Unraveling the Difference in the Composition/Content of the Aroma Compounds in Different Tobacco Leaves: For Better Use

Tiejun Yan,¹Ping Zhou,¹Fei Long,¹Jing Liu,²Fengguang Wu,¹Maolin Zhang,³and Jialei Liu³

Academic Editor: Isabel Lara

Received09 Sept 2022

Revised29 Nov 2022

Accepted15 Dec 2022

Published29 Dec 2022

Abstract

The composition/content of aroma compounds in tobacco leaves in the different producing areas varies too much, and it is very meaningful to develop advanced analysis techniques to investigate the composition/content-producing area correlation. Here, gas chromatography-ion mobility spectroscopy (GC-IMS) was used to analyze the composition/content of aroma compounds in tobacco samples from eight different producing areas. With this technique, ion mobility spectrum, differential ion mobility spectrum, and fingerprint spectrum were constructed for two-dimensional analysis. Then, the principal component analysis (PCA) and similarity analysis were performed for the eight tobacco samples. The results showed that the GC-IMS can detect 197 volatile aroma compounds in tobacco leaves and 75 of them are well identified. The fingerprint spectrum directly showed the difference in the composition/content of volatile aroma compounds in tobacco leaves from different producing areas. PCA and similarity analysis can clearly distinguish tobacco samples from different producing areas. This work demonstrated that the application of GC-IMS in analyzing the composition/content of aroma compounds in tobacco leaves is efficient. GC-IMS is a very powerful tool to give a direct and visual comparison of the composition/content of aroma compounds in tobacco leaves from different producing areas. The relationship between the composition/content of aroma compounds and producing areas could be established by this advanced technology. This work offers the possibility of planting or grading tobacco with different taste and smell more precisely in the future.

1. Introduction

As an industrial crop, tobacco is widely planted in more than 120 countries and regions in the world, which contributed too much to the local economy [1–3]. As the raw material of cigarettes, tobacco leaves contain very rich aroma compounds including alcohols, lipids, carbonyl groups, nitrogen heterocyclic groups, phenols, and acids, and many of these aroma compounds are closely related to the taste and smell of cigarettes [4–6]. For example, phenethyl alcohol endows the cigarette with the scent of flowers and acids can reduce the offensive smell of cigarette smoke. Therefore, identifying the composition/content of the aroma compounds in tobacco leaves and the corresponding influence factor is very important. To date, studies focused on the effect of the maturation stage and stalk position on the aroma compounds’ composition/content in tobacco leaves have been reported [7–9]. Since the climate and soil conditions of each producing area varies a lot, the impact of producing areas on the composition/content of these aroma compounds in tobacco leaves should be investigated carefully. Indeed, producing areas are an essential factor in the flavor of tobacco leaves [7, 10–13]. However, this kind of study is rare and not deep enough. Significantly, precisely detecting the composition/content of aroma compounds in tobacco leaves will offer basic data and will be further used, from the molecular level, in the producing areas-flavor of tobacco leaves study. Undoubtedly, the study will be essential for planting and efficiently utilizing tobacco. To achieve this, advanced analytical equipment and technique are the prerequisites to comprehensively understand the relationship between producing areas and the taste/smell of cigarettes.

Till now, many analytical facilities which were extensively used in organic chemistry have been utilized to study the composition of aroma compounds in tobacco leaves. For instance, two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF-MS) combined with solvent extraction has been demonstrated to quickly and accurately determine free and bound aroma compounds in tobacco [14], Fourier transform near-infrared spectroscopy (FT-IR) combined with partial least squares regression can be effectively used to analyze the chemical components in tobacco [15, 16]. In addition, ultraperformance liquid chromatography (UPLC) [17, 18], ion chromatography (IC) [19], and nuclear magnetic resonance technology (NMR) [20, 21] are also applied to the detection and identification of tobacco chemicals. Although these methods have their characteristics, there are still some limitations of the present analytical facilities and methods. For example, tedious sample preparation, long analysis time, costly, and sophisticated data analysis hindered their practical applications in aroma compounds’ detection. Not only that, these traditional methods cannot offer a direct and visual comparison between tobacco samples, lacking analytical capacity. Hence, it is necessary to develop more powerful technologies to meet the requirement of detecting all aroma compounds in tobacco leaves effectively and precisely with a single testing equipment.

In recent years, a technology integrating the advantages of gas chromatography and ion mobility spectroscopy technology (GC-IMS) attracted our attention because of its high sensitivity, short analysis time, high selectivity, and no need for sample pretreatment detecting ability [22]. Especially, GC-IMS can perform orthogonal two-dimensional analysis. Due to these merits, this technology has been widely used in food detection [23], explosives detection [24], biomedical analysis [25], and environmental monitoring [26]. We assume that the composition/content of tobacco leaves will be effectively analyzed by this technology, resulting in a deep understanding of the relationship between the composition/content of aroma compounds and producing areas. Herein, as a proof-of-concept experiment, GC-IMS was applied to obtain a direct and visual comparison of the composition/content of aroma compounds in tobacco leaves from different producing areas. This kind of detailed comparison is very helpful to build a relationship between the composition/content of aroma compounds and producing areas, then to distinguish samples accurately and clearly from different production regions. More importantly, it is of significance for tobacco flavor control and tobacco leaves grade.

2. Materials and Methods

2.1. Analyzing Materials

The C3F grade tobaccos from QujingMalong, Yunnan province (YN-QJML-C3F), Chuxiong, Yunnan province (YN-CHX-C3F), Zhaotong, Yunnan province (YN-ZHT-C3F), Guangyuan, Sichuan province (SCH-GY-C3F), Liangshanhuidong, Sichuan province (SCH-LSHHD-C3F), Liangshanhuili, Sichuan province (SCH-LSHHL-C3F), Zunyi, Guizhou province (GZH-ZY-C3F), and Qianxi’nan, Guizhou province (GZH-QXXN-C3F), were selected as testing materials.

2.2. Analytical Instruments and Methods

Flavour Spec GC-IMS was purchased from Gesellschaft für analytische Sensorsysteme mbH (Germany). Aroma compounds in tobacco samples from different regions were analyzed by GC-IMS in a positive ion mode. The GC-IMS was equipped with an automatic headspace sampler and a nonpolar chromatographic capillary column FS-SE-54-CB-0.5. The column length and internal diameter are 15 m and 0.53 mm, respectively. Initially, a certain amount of tobacco leave samples was randomly chosen from a place and ground into powder. Then, 1.0 g of the above-prepared tobacco powder was taken and placed in a sample inlet bottle (20 ml) for further injection, which does not require the pretreatment of tobacco samples. After incubation at 80°C for 15 min, 500 μL of the headspace was automatically injected using a heated syringe (80°C) into the heated injector (85°C) of the GC-IMS equipment. The volatile compounds were separated through the GC column at 60°C. The carrier gas (N₂, purity 99.999%) is set at 0–2 mL/min, 2 mL/min, 2–10 mL/min, 2–10 mL/min, 10–20 mL/min, 20–25 mL/min, 10–100 mL/min, and 100–150 mL/min in succession. The drift tube was operated at a constant voltage of 400 V cm⁻¹, a temperature of 45°C, and the drift gas (N₂, purity 99.999%) rate was set at 150 mL/min. The output data were collected in a special software tool that comes with the IMS instrument.

3. Results and Discussion

3.1. The Ion Mobility Spectrogram of the Tobacco Samples

Initially, the aroma compounds of the eight different tobacco samples were detected by carrying out GC-IMS analysis. As shown in Figure 1, a high density of reactive ion peak (RIP) points was marked in the coordinate system. The position of these peak points was determined by the retention time and drift time of the detected aroma compounds during the GC-IMS analysis. In the ion mobility spectrum, one peak point represents one aroma compound. In a selected tobacco sample, as high as 197 peak points could be counted. Moreover, the concentration of certain aroma compound was displayed by the colorized difference method. The red area indicated that the concentration of the aroma compound is high, the deeper the color, the higher concentration it had, and the blue area was the opposite. Based on this rule, the aroma compounds’ distribution and concentration information in a tobacco sample were obtained visually. In addition, the difference among the eight tobacco samples can also be reflected through the direct comparison. By comparing the rectangular area in Figure 1, it was found that the difference in concentrations of some aroma compounds in tobacco is significant in different provinces. By comparing the circular area in Figure 1, obvious differences were also found that the concentrations of some aroma compound in tobacco samples from different cities in the same province.

3.2. Qualitative Analysis of Volatile Compounds in Tobacco

The qualitative analysis of aroma compounds in tobacco is the first step to understand the relationship between origins and tobacco taste. As discussed above, taking the YN-QJML-C3F as the reference sample, 197 peak points could be obtained in the ion mobility spectrum (Figure 2). In the figure, the x-axis represents drift time, the y-axis is the retention time. As is displayed, 75 of the peak points could be qualitatively analyzed, including alcohols, ketones, aldehydes, acids, lipids, furans, phenylalanine degradation products, and browning products. To be noted, some peak points correspond to the same compound because of the existence of monomers and dimers. This could be explained by the high content of the compound in the sample. The details of the identified volatile compounds are summarized in Table 1. In the table, the name of specific compounds and their corresponding peak positions in the ion mobility spectrum were revealed. The determination of the peak position and drift time of a certain compound can act as the reference and facilitate qualitative analysis of a tobacco leaf sample from an unknown producing area. Moreover, the odors of each compound are also clearly listed for reference [27]. These compounds presented different degrees of plant aroma. For example, some compounds presented pungent odors, and some presented tobacco odors, which are associated with the rich aroma compounds of tobacco. Aroma acids in tobacco can directly volatilize into smoke, which has a direct impact on taste and aroma compounds. Alcohol compounds in tobacco have a great influence on the quality of flue gas, such as benzyl alcohol and phenethyl alcohol, which can increase the fragrance of flowers in roasted tobacco [28, 29]. Carbonyl aroma compounds, including aldehydes, ketones, and quinones, have an important impact on the quality and flavor of tobacco [29]. Benzaldehyde can increase almond flavor in smoke, and 3-hydroxy-2-butanone can increase cream flavor in smoke. Lipid aroma compounds in tobacco also have important effects on aroma and taste. Amyl acetate can increase the banana smell in smoke, and ethyl valerate can increase the apple smell in smoke [30]. Overall, all of these aroma compounds together consist of the thick scent of the aroma of tobacco samples.

3.3. Fingerprint Analysis

Although a large number of aroma compounds were qualitatively identified and also their odor taste was clarified in the tobacco sample, it is still not easy to know how much contribution of each aroma compound to the whole flavor of tobacco leaves, which further led to some difficulties in the comparative analysis of the influence of producing areas. To investigate the content of certain aroma compounds more comprehensively in a tobacco sample, the gallery plot plug-in of LAV software developed by G. A. S. was used to select all the peaks in the ion mobility spectrum and automatically generate the fingerprint spectrum. The fingerprint spectrum enables easy and fast comparisons of different samples, differences in concentrations or presence/absence of marker peaks can be easily seen. The fingerprint spectrum of the sixteen batches of tobacco samples is shown in Figure 3, where the X-axis is the type of aroma compounds, and the Y-axis is the tobacco samples. In the Y-axis, two parallel samples from the same producing area were selected for the comparative analysis. In addition to the fingerprint spectrum, the specific data of the peak position and the area of identified compounds in the fingerprint spectrum were also revealed for the comparison in Table S1. As shown in Figure 3, the similarity of the fingerprint spectrum of different batches of tobacco samples but the same producing area is high. This result verified that this analytic method is reproducible and reliable. For the tobacco samples from different producing areas, the variation in the content of aroma compounds is obvious. For instance, compounds 3-methylvaleric acid dimer, isoamyl acetate monomer, and 2-methylbutanol dimer are lower in samples SCH-GY-C3F with a peak area of ≈288 and SCH-LSHHL-C3F with a peak area of ≈269 in comparison to those from other places (peak area are more than 600). The sample YN-QJML-C3F showed a much higher content of ethyl 2-methylbutanoate and isoamyl acetate dimmer than other samples. Especially for the compound ethyl 2-methylbutanoate (peak area: ≈880), its highest content in the sample YN-QJML-C3F can act as an important indicator to distinguish it from other tobacco samples (most of their peak area is below 150). Samples SCH-LSHHD-C3F and GZH-ZY-C3F have more similarities in aroma compounds even though they are from different provinces. Both of them have a higher content of the compound Z-3-hexen-1-ol than other tobacco samples, these two samples can be distinguished from other ones easily. To further distinguish samples SCH-LSHHL-C3F from GZH-ZY-C3F, carefully checking the content of (E, Z)-2, 6-nonadienal in these two samples is helpful. According to the fingerprint spectrum, the sample has a higher content of (E, Z)-2, 6-nonadienal is SCH-LSHHD-C3F with a peak area of ≈180, the lower one is GZH-ZY-C3F with a peak area of ≈70. To be noted, even in the tobacco samples from the same province but different countries or cities, a distinct difference in the concentrations of aroma compounds between these samples also existed. For example, samples from Yunnan Province YN-QJML-C3F, YN-ZHT-C3F, and YN-CHX-C3F, each have their own characteristic aroma compounds. The same phenomenon was observed between samples GZH-ZY-C3F and GZH-QXXN-C3F from Guizhou province. Other compounds, such as 2-methylbutanoate acid, (E, Z)-2, 6-nonadienal, pentanal dimer, ethyl propanoate, 2, 3-butandiol, and isoamyl acetate dimer are various much among the samples from different producing areas. These results demonstrated the big influences of producing areas on aroma compound compositions in tobacco samples. The difference in the concentrations of different aroma compounds between producing areas are significant. Apart from the difference in the content of a certain compound in the tested samples, there are some compounds, such as γ-butyrolactone dimer, γ-butyrolactone monomer, acetoin, 2-methylbutanol monomer, methyl ester acetic acid, and acetone, are all rich in all tobacco samples. It means that the content of these compounds will not be affected by the producing areas, the intrinsic factor decides their content. As discussed above, the fingerprint analysis could help us to find out which tobacco sample has low or high concentrations of a certain aroma compound easily. Moreover, the fingerprint analysis can also be used to compare the concentrations of different aroma compounds in the same sample. Thus, the fingerprint spectrum and its related analysis is a very powerful tool to correlate the content of aroma compounds with the producing area.

3.4. Principal Component and Similarity Analysis

To further analyze the relationship among samples, principal component analysis (PCA) was conducted based on the information acquired for all volatile aroma compounds in tobacco samples. The results are shown in Figure 4, in which the contribution rate of the first principal component was 54%. The contribution rate of the second principal component was 16%, and the cumulative contribution rate of the two principal components reached 70%. Judging from Figure 4, each sample from a different province had its characteristics, and the determination of the first and second principal components rate could be used to clearly distinguish eight tobacco samples from each other. The dispersion degree of tobacco samples was high in samples SCH-GY-C3F, SCH-LSHHD-C3F, SCH-LSHHL-C3F, GZH-ZY-C3F, and GZH-QXXN-C3F, but low in YN-QJML-C3F, YN-CHX-C3F, and YN-ZHT-C3F. The similarity between the two parallel samples in SCH-LSHHL-C3F was very high. Conversely, the two parallel samples in other cities had a certain difference, which could be caused by the tiny difference in soil constituents and temperature, and the variation of environmental humidity because of the long distance between the two cities.

To improve the accuracy of the analysis of tobacco samples from different producing areas, all volatile material information were used to calculate the similarity of each sample. Two parallel samples from the same producing area were also selected for the comparison. The results are shown in Table 2. Reasonably, the similarity between the two parallel tobacco samples is high, which achieved 96% at the lowest and 99% at the highest coinciding with the fingerprint spectrum analysis. For the tobacco samples YN-CHX-C3F and YN-ZHT-C3F, YN-CHX-C3F, and YN-QJML-C3F from the same province, their similarity was located between 90 and 92%. However, the tobacco samples YN-ZHT-C3F and YN-QJML-C3F were relatively low (87–88%), even though they are produced in the same province. To our surprise, most of the tobacco samples’ similarity is low (72–89%) in Sichuan province. The highest similarity value is only (88–89%), which is obtained from samples SCH-LSHHL-C3F and SCH-GY-C3F. The same phenomenon happened to samples GZH-QXXN-C3F and GZH-ZY-C3F from Guizhou province, resulting in a similarity of 82%. By comparing and analyzing the similarity between tobacco samples from different regions. Interestingly, the similarity between tobacco samples GZH-ZY-C3F and YN-CHX-C3F, GZH-ZY-C3F, and SCH-LSHHD-C3F reached 90%. This is not normal because the similarity between two tobacco samples from other regions was lower than 90%. The high similarity between the two samples from different provinces may originate from the similar planting climate, soil condition, moisture, sunshine condition. All of the above discussion indicates that the aroma compounds in tobacco samples were greatly affected by the producing area.

4. Conclusion

In this study, GC-IMS technology was used for the qualitative analysis of aroma compounds in tobacco samples from eight different producing areas. Moreover, owing to the two-dimensional analytic ability of this technology, the relationship between the composition/content of tobacco leaves and their producing areas was well-built. In tobacco leaves of this work, as high as 197 volatile aroma compounds were detected and 75 of them were well identified, including 23 alcohols, 20 aldehydes, 6 acids, 8 ketones, 9 lipids, and 3 furans. In addition to the qualitative analysis of the aroma compounds in a certain tobacco sample, the ion mobility spectrum and its corresponding fingerprint spectrum were successfully applied to directly reveal the content of the 75 identified compounds in the tobacco samples varying with producing areas. With these two advanced spectrums, the content of aroma compounds in the tobacco leaves is compared and discussed in detail in the light of different producing areas. This kind of comparison facilitates us to understand the impact of producing areas at the molecular level, bridging the gap between the macro tobacco-producing areas and the micro aroma compounds composition/content. Furthermore, PCA and similarity analysis were used to distinguish samples accurately and clearly from different production regions, as well as to identify the origin of unknown samples. This work provides an example of the analysis of the composition/content of aroma compounds in tobacco leaves from different producing areas by GC-IMS for tobacco flavor control and tobacco leaves grade.

Data Availability

The data used to support the findings of this study are included in Supplementary Materials.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This research was supported by the Finance Science and Technology Project of Hainan Province (No. ZDYF2020084) and Central Public-Interest Scientific Institution Basal Research Fund (No. BSRF202105).

Supplementary Materials

The peak position and area of identified compounds in the fingerprint spectrum of tobacco samples from eight producing areas (Table S1) are included in Supplementary Materials. (Supplementary Materials)

References

D. Makoka, J. Drope, A. Appau et al., “Costs, revenues and profits: an economic analysis of smallholder tobacco farmer livelihoods in Malawi,” Tobacco Control, vol. 26, no. 6, pp. 634–640, 2017.
View at: Publisher Site | Google Scholar
J. R. DiFranza and J. J. Librett, “State and federal revenues from tobacco consumed by minors,” American Journal of Public Health, vol. 89, no. 7, pp. 1106–1108, 1999.
View at: Publisher Site | Google Scholar
A. A. Laverty, C. R. Li, K. C.-M. Chang, C. Millett, and F. T. Filippidis, “Cigarette taxation and price differentials in 195 countries during 2014–2018,” Tobacco Control, vol. 2021, Article ID 056682, 2021 pages, 2021.
View at: Publisher Site | Google Scholar
R. L. Stedman, “Chemical composition of tobacco and tobacco smoke,” Chemistry Review, vol. 68, no. 2, pp. 153–207, 1968.
View at: Publisher Site | Google Scholar
V. Popova, V. Gochev, T. Girova, I. Iliev, T. Ivanova, and A. Stoyanova, “Extraction products from tobacco – aroma and bioactive compounds and activities,” Current Bioactive Compounds, vol. 11, no. 1, pp. 31–37, 2015.
View at: Publisher Site | Google Scholar
A. Thielen, H. Klus, and L. Müller, “Tobacco smoke: unraveling a controversial subject,” Experimental & Toxicologic Pathology, vol. 60, no. 2-3, pp. 141–156, 2008.
View at: Publisher Site | Google Scholar
B. Xia, M. Feng, G. Xu et al., “Investigation of the chemical compositions in tobacco of different origins and maturities at harvest by GC–MS and HPLC–PDA-QTOF-MS,” Journal of Agricultural and Food Chemistry, vol. 62, no. 22, pp. 4979–4987, 2014.
View at: Publisher Site | Google Scholar
M. R. Stiff, A. K. Weissinger, and D. A. Danehower, “Analysis of CoQ10 in cultivated tobacco by a high-performance liquid chromatography–ultraviolet method,” Journal of Agricultural and Food Chemistry, vol. 59, no. 17, pp. 9054–9058, 2011.
View at: Publisher Site | Google Scholar
W. Sun, Z. Zhou, Y. Li, Z. Xu, W. Xia, and F. Zhong, “Differentiation of flue-cured tobacco leaves in different positions based on neutral volatiles with principal component analysis (PCA),” European Food Research and Technology, vol. 235, no. 4, pp. 745–752, 2012.
View at: Publisher Site | Google Scholar
B. Liu, X. Zhang, Y. Zhang et al., “Effects of meteorological factors on aroma precursors contents of high aroma flue-cured tobacco,” Chinese Journal of Eco-Agriculture, vol. 24, no. 9, p. 1214, 2016.
View at: Google Scholar
J. B. Henry, M. Vann, I. McCall, P. Cockson, and B. E. Whipker, “Nutrient disorders of burley and flue-cured tobacco: Part 2—micronutrient disorders,” Crop, Forage & Turfgrass Management, vol. 4, no. 1, pp. 1–7, 2018.
View at: Publisher Site | Google Scholar
Z. Tang, L. Chen, Z. Chen et al., “Climatic factors determine the yield and quality of Honghe flue-cured tobacco,” Scientific Reports, vol. 10, no. 1, Article ID 19868, 2020.
View at: Publisher Site | Google Scholar
Z. Xiang, K. Cai, G. Liang et al., “Analysis of volatile flavour components in flue-cured tobacco by headspace solid-phase microextraction combined with GC×GC-TOFMS,” Analytical Methods, vol. 6, no. 10, pp. 3300–3308, 2014.
View at: Publisher Site | Google Scholar
Y. Ding, L. Zhu, S. Liu, H. Yu, and Y. Dai, “Analytical method of free and conjugated neutral aroma components in tobacco by solvent extraction coupled with comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry,” Journal of Chromatography A, vol. 1280, pp. 122–127, 2013.
View at: Publisher Site | Google Scholar
J. Duan, Y. Huang, Z. Li et al., “Determination of 27 chemical constituents in Chinese southwest tobacco by FT-NIR spectroscopy,” Industrial Crops and Products, vol. 40, pp. 21–26, 2012.
View at: Publisher Site | Google Scholar
Y. Ma, R. Bai, G. Du et al., “Rapid determination of four tobacco specific nitrosamines in burley tobacco by near-infrared spectroscopy,” Analytical Methods, vol. 4, no. 5, pp. 1371–1376, 2012.
View at: Publisher Site | Google Scholar
B. Fu, X. Ji, M. Zhao et al., “The influence of light quality on the accumulation of flavonoids in tobacco (Nicotiana tabacum L.) leaves,” Journal of Photochemistry and Photobiology B: Biology, vol. 162, pp. 544–549, 2016.
View at: Publisher Site | Google Scholar
H. Ji, Y. Wu, F. Fannin, and L. Bush, “Determination of tobacco alkaloid enantiomers using reversed phase UPLC/MS/MS,” Heliyon, vol. 5, no. 5, Article ID e01719, 2019.
View at: Publisher Site | Google Scholar
J. Qiu and X. Jin, “Development and optimization of organic acid analysis in tobacco with ion chromatography and suppressed conductivity detection,” Journal of Chromatography A, vol. 950, no. 1-2, pp. 81–88, 2002.
View at: Publisher Site | Google Scholar
J. B. Wooten, N. E. Kalengamaliro, and D. E. Axelson, “Characterization of bright tobaccos by multivariate analysis of 13C CPMAS NMR spectra,” Phytochemistry, vol. 70, no. 7, pp. 940–951, 2009.
View at: Publisher Site | Google Scholar
J. Ticha and C. Wright, “Rapid detection of toxic compounds in tobacco smoke condensates using high-resolution 1H-nuclear magnetic resonance spectroscopy,” Analytical Methods, vol. 8, no. 34, pp. 6388–6397, 2016.
View at: Publisher Site | Google Scholar
L. Haley, J. Romeskie, and G. C Ims, “A technology for many applications,” SPIEL, vol. 3575, 1998.
View at: Google Scholar
S. Wang, H. Chen, and B. Sun, “Recent progress in food flavor analysis using gas chromatography–ion mobility spectrometry (GC–IMS),” Food Chemistry, vol. 315, Article ID 126158, 2020.
View at: Publisher Site | Google Scholar
R. G. Ewing, D. A. Atkinson, G. A. Eiceman, and G. J. Ewing, “A critical review of ion mobility spectrometry for the detection of explosives and explosive related compounds,” Talanta, vol. 54, no. 3, pp. 515–529, 2001.
View at: Publisher Site | Google Scholar
C. M. Gryniewicz, J. C. Reepmeyer, J. F. Kauffman, and L. F. Buhse, “Detection of undeclared erectile dysfunction drugs and analogues in dietary supplements by ion mobility spectrometry,” Journal of Pharmaceutical and Biomedical Analysis, vol. 49, no. 3, pp. 601–606, 2009.
View at: Publisher Site | Google Scholar
A. B. Kanu and H. H. Hill, “Ion mobility spectrometry detection for gas chromatography,” Journal of Chromatography A, vol. 1177, no. 1, pp. 12–27, 2008.
View at: Publisher Site | Google Scholar
D. Mao, P. Ma, and M. An, Cigarette Formulations and Flavors, Chemical Industry Press, Beijing China, 2001.
J. A. Piornos, D. P. Balagiannis, L. Methven, E. Koussissi, E. Brouwer, and J. K. Parker, “Elucidating the odor-active aroma compounds in alcohol-free beer and their contribution to the worty flavor,” Journal of Agricultural and Food Chemistry, vol. 68, no. 37, pp. 10088–10096, 2020.
View at: Publisher Site | Google Scholar
D. Pu, W. Duan, Y. Huang et al., “Characterization of the key odorants contributing to retronasal olfaction during bread consumption,” Food Chemistry, vol. 318, Article ID 126520, 2020.
View at: Publisher Site | Google Scholar
S. Torres, A. Pandey, and G. Castro, Banana Flavor: Insights into Isoamyl Acetate Production, Nova Science Publishers, Hauppauge, NY, USA, 2010.

Copyright

Copyright © 2022 Tiejun Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

621

Downloads

542

Citations