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

Authors: Tiejun Yan; Ping Zhou; Fei Long; Jing Liu; Fengguang Wu; Maolin Zhang; Jialei Liu
Journal: Journal of Chemistry
 (2022)

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## 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.


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## Body

## 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, 500μL 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.


## 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, 500μL 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 Figure1, 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.Figure 1
The ion mobility spectrogram of the eight tobacco samples. The red area represents a high concentration of aroma compound; the deeper the color, the higher concentration it had, and the blue area was the opposite.


### 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 (Figure2). 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.Figure 2
75 marked peaks were qualitatively identified in the ion mobility spectrum of sample YN-QJML-C3F.Table 1
Qualitative analysis results of aroma compounds of the sample YN-QJML-C3F.
CountCompoundCAS#Rt (sec)Dt (RIPrel)Odor11-Hexanol111-27-3370.841.3225Ethereal fusel oil fruity alcoholic sweet green21-Hydroxy-2-propanone116-09-6176.8791.2314Pungent sweet caramelly ethereal31-Pentanol dimer71-41-0243.2741.5114Fusel oil sweet balsam41-Pentanol monomer71-41-0243.6651.2525Fusel oil sweet balsam52, 3-Butandione431-03-8134.9771.1733Strong butter sweet creamy pungent caramel62, 3-Butanediol513-85-9309.3041.3672Fruity creamy buttery72-Acetylfuran1192-62-7414.861.1162Sweet balsam almond cocoa caramel coffee82-Acetylpyridine1122-62-9599.8811.1209Popcorn heavy corn chip fatty tobacco92-Acetylpyrrole1072-83-9719.9751.1059Musty nut skin maraschino cherry coumarin licorice walnut bready102-Butanone78-93-3142.741.2474Acetone-like ethereal fruity camphor112-Ethyl-1-hexanol104-76-7663.2311.4153Citrus fresh floral oily sweet122-Ethylfuran3208-16-0185.4811.3101Sweet burnt earthy malty132-Heptanol543-49-7416.4351.3732Fresh lemongrass herbal sweet floral-fruity green142-Hexenol dimer2305-21-7331.761.5192Fruity green leafy152-Hexenol monomer2305-21-7332.6081.1815Fruity green leafy162-Methyl-1-propanol78-83-1168.7321.1712Ethereal winey cortex172-Methylbutanoic acid116-53-0334.0571.2096Pungent acid roquefort cheese182-Methylbutanol dimer137-32-6216.9551.4844Roasted wine onion fruity fusel alcoholic whiskey192-Methylbutanol monomer137-32-6217.3271.2376Roasted wine onion fruity fusel alcoholic whiskey202-Methyl-propanal dimer78-84-2129.8581.284Fresh aldehydic floral green212-Methyl-propanal monomer78-84-2129.9431.1036Fresh aldehydic floral green222-Octanol123-96-6554.4771.4418Fresh spicy green woody herbal earthy232-Pentanone107-87-9170.771.3711Sweet fruity ethereal wine banana woody242-Pentylfuran3777-69-3574.131.254Fruity green earthy beany vegetable metallic252-Phenylethanol1960/12/8793.6991.291Floral rose dried rose flower rose water263-Methylbutanal590-86-3168.2081.4102Ethereal aldehydic chocolate peach fatty273-Methylvaleric acid dimer105-43-1498.2841.6279Animal sharp acidic cheesy green fruity sweaty283-Methylvaleric acid monomer105-43-1499.2011.283Animal sharp acidic cheesy green fruity sweaty295-Methylfurfuryl alcohol3857-25-8499.0451.567Sweet caramellic306-Methyl-5-hepten-2-one110-93-0566.2031.1776Citrus green musty lemongrass apple31Acetoin513-86-0201.3861.3308Sweet buttery creamy dairy milky fatty32Acetone67-64-1115.9731.1182Solvent ethereal apple pear33Alpha-methylbenzenemethanol98-85-1691.941.1933Fresh sweet acetophenone gardenia hyacinth34Alpha-terpieol10482-56-1959.0641.2856Lilac floral terpenic35Benzaldehyde dimer100-52-7498.0521.4695Strong sharp sweet bitter almond cherry36Benzaldehyde monomer100-52-7498.0521.1491Strong sharp sweet bitter almond cherry37Benzenemethanol100-51-6662.631.3237Floral rose phenolic balsamic38Cyclohexanone108-94-1331.5971.4537Minty acetone39Dimethyl disulphide624-92-0238.6641.1472Sulfurous vegetable cabbage onion40E-2-hexen-1-ol928-95-0324.7951.1757Fresh green leafy fruity unripe banana41(E, Z)-2, 6-nonadienal557-48-2874.6851.3705Green fatty dry cucumber violet leaf42Ethyl-2-methylbutanoate7452-79-1295.4521.2425Sharp sweet green apple fruity43Ethyl acetate141-78-6148.5781.3374Ethereal fruity sweet weedy green44Ethyl butyrate105-54-4297.0651.5575Fruity juicy fruit pineapple cognac45Ethyl pentanoate539-82-2393.11.6844Sweet fruity apple pineapple green tropical46Ethyl propanoate105-37-3194.5871.1507Sweet fruity rum juicy fruit grape pineapple47Furfural dimer1998/1/1305.7141.3334Sweet woody almond fragrant baked bread48Furfural monomer1998/1/1307.1591.0829Sweet woody almond fragrant baked bread49Gamma-butyrolactone dimer96-48-0423.4831.3024Creamy oily fatty caramel50Gamma-butyrolactone monomer96-48-0428.1341.0823Creamy oily fatty caramel51Heptanal dimer111-71-7399.9621.6938Fresh aldehydic fatty green herbal wine-lee ozone52Heptanal monomer111-71-7398.9641.3305Fresh aldehydic fatty green herbal wine-lee ozone53Hexanal dimer66-25-1270.351.5626Fresh green fatty aldehydic grass leafy fruity sweaty54Hexanal monomer66-25-1270.6131.2518Fresh green fatty aldehydic grass leafy fruity sweaty55Isoamyl acetate dimer123-92-2364.4951.7505Sweet fruity banana solvent56Isoamyl acetate monomer123-92-2365.851.3075Sweet fruity banana solvent57Isopentanol123-51-3239.5111.1195Fusel oil alcoholic whiskey fruity banana58Linalool78-70-6776.3371.2204Citrus floral sweet bois de rose woody green blueberry59Methional3268-49-3372.5221.0868Musty potato tomato earthy vegetable creamy60Acetic acid, methyl ester79-20-9122.6561.1938Ether sweet fruity61Methyl-5-furfural620-02-0512.5071.1275Spice caramel maple62n-Nonanal dimer124-19-6782.3021.9402Waxy aldehydic rose fresh orris orange peel fatty peely63n-Nonanal monomer124-19-6783.1051.472Waxy aldehydic rose fresh orris orange peel fatty peely64Octanal124-13-0600.4381.4018Aldehydic waxy citrus orange peel green fatty65Pentanal dimer110-62-3190.1971.4247Fermented bready fruity nutty berry66Pentanal monomer110-62-3190.4131.1796Fermented bready fruity nutty berry67Pentanoic acid109-52-4404.261.2271Sickening putrid acidic sweaty rancid68Phenylacetaldehyde dimer122-78-1670.4111.5386Green sweet floral hyacinth clover honey cocoa69Phenylacetaldehyde monomer122-78-1668.1931.2532Green sweet floral hyacinth clover honey cocoa70Phenylacetic acid103-82-21010.291.3311Sweet honey floral honeysuckle sour waxy civet71Propanal123-38-6109.4011.0436Earthy alcohol wine whiskey cocoa nutty72Propanoic acid1979/9/4232.8341.1038Pungent acidic cheesy vinegar73Propylsulfide111-47-7376.9511.1582Garlic onion74Toluene108-88-3228.1121.018Sweet75Z-3-hexen-1-ol928-96-1340.9591.5085Fresh green cut grass foliage vegetable herbal oilyThe retention time of a certain compound in the sample was determined by using the standard curves, the detected compounds in this work were referred to the IMS database. The odor data of these compounds are referred to the standard database of the Perflavory information system.


### 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 Figure3, 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.Figure 3
The fingerprint spectrum of aroma compounds in the tobacco samples from eight producing areas.


### 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 Figure4, 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.Figure 4
The principal component analysis of each sample.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 Table2. 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.Table 2
The similarity between samples.
Matching (%)YN-QJML-C3FYN-QJML-C3FYN-CHX-C3FYN-CHX-C3FYN-ZHT-C3FYN-ZHT-C3FSCH-LSHHD-C3FSCH-LSHHD-C3FSCH-GY-C3FSCH-GY-C3FSCH-LSHHL-C3FSCH-LSHHL-C3FGZH-QXXN-C3FGZH-QXXN-C3FGZH-ZY-C3FGZH-ZY-C3FYN-QJML-C3F100979090878889897777747483838888YN-QJML-C3F971009090878889897979777685858988YN-CHX-C3F909010099919287877878767785859090YN-CHX-C3F909099100919287877878767785869089YN-ZHT-C3F878791911009685858080787885858685YN-ZHT-C3F888892929610086868079787886868786SCH-LSHHD-C3F898987878586100987776727381819089SCH-LSHHD-C3F898987878586981007979747582829089SCH-GY-C3F777978788080777910099888886867777SCH-GY-C3F777978788079767999100898986867777SCH-LSHHL-C3F747776767878727488891009886867372SCH-LSHHL-C3F747677777878737588899810086867373GZH-QXXN-C3F838585858586818286868686100988282GZH-QXXN-C3F838585868586818286868686981008282GZH-ZY-C3F888990908687909077777373828210098GZH-ZY-C3F888890898586898977777273828298100


## 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 Figure1, 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.Figure 1
The ion mobility spectrogram of the eight tobacco samples. The red area represents a high concentration of aroma compound; the deeper the color, the higher concentration it had, and the blue area was the opposite.


## 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 (Figure2). 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.Figure 2
75 marked peaks were qualitatively identified in the ion mobility spectrum of sample YN-QJML-C3F.Table 1
Qualitative analysis results of aroma compounds of the sample YN-QJML-C3F.
CountCompoundCAS#Rt (sec)Dt (RIPrel)Odor11-Hexanol111-27-3370.841.3225Ethereal fusel oil fruity alcoholic sweet green21-Hydroxy-2-propanone116-09-6176.8791.2314Pungent sweet caramelly ethereal31-Pentanol dimer71-41-0243.2741.5114Fusel oil sweet balsam41-Pentanol monomer71-41-0243.6651.2525Fusel oil sweet balsam52, 3-Butandione431-03-8134.9771.1733Strong butter sweet creamy pungent caramel62, 3-Butanediol513-85-9309.3041.3672Fruity creamy buttery72-Acetylfuran1192-62-7414.861.1162Sweet balsam almond cocoa caramel coffee82-Acetylpyridine1122-62-9599.8811.1209Popcorn heavy corn chip fatty tobacco92-Acetylpyrrole1072-83-9719.9751.1059Musty nut skin maraschino cherry coumarin licorice walnut bready102-Butanone78-93-3142.741.2474Acetone-like ethereal fruity camphor112-Ethyl-1-hexanol104-76-7663.2311.4153Citrus fresh floral oily sweet122-Ethylfuran3208-16-0185.4811.3101Sweet burnt earthy malty132-Heptanol543-49-7416.4351.3732Fresh lemongrass herbal sweet floral-fruity green142-Hexenol dimer2305-21-7331.761.5192Fruity green leafy152-Hexenol monomer2305-21-7332.6081.1815Fruity green leafy162-Methyl-1-propanol78-83-1168.7321.1712Ethereal winey cortex172-Methylbutanoic acid116-53-0334.0571.2096Pungent acid roquefort cheese182-Methylbutanol dimer137-32-6216.9551.4844Roasted wine onion fruity fusel alcoholic whiskey192-Methylbutanol monomer137-32-6217.3271.2376Roasted wine onion fruity fusel alcoholic whiskey202-Methyl-propanal dimer78-84-2129.8581.284Fresh aldehydic floral green212-Methyl-propanal monomer78-84-2129.9431.1036Fresh aldehydic floral green222-Octanol123-96-6554.4771.4418Fresh spicy green woody herbal earthy232-Pentanone107-87-9170.771.3711Sweet fruity ethereal wine banana woody242-Pentylfuran3777-69-3574.131.254Fruity green earthy beany vegetable metallic252-Phenylethanol1960/12/8793.6991.291Floral rose dried rose flower rose water263-Methylbutanal590-86-3168.2081.4102Ethereal aldehydic chocolate peach fatty273-Methylvaleric acid dimer105-43-1498.2841.6279Animal sharp acidic cheesy green fruity sweaty283-Methylvaleric acid monomer105-43-1499.2011.283Animal sharp acidic cheesy green fruity sweaty295-Methylfurfuryl alcohol3857-25-8499.0451.567Sweet caramellic306-Methyl-5-hepten-2-one110-93-0566.2031.1776Citrus green musty lemongrass apple31Acetoin513-86-0201.3861.3308Sweet buttery creamy dairy milky fatty32Acetone67-64-1115.9731.1182Solvent ethereal apple pear33Alpha-methylbenzenemethanol98-85-1691.941.1933Fresh sweet acetophenone gardenia hyacinth34Alpha-terpieol10482-56-1959.0641.2856Lilac floral terpenic35Benzaldehyde dimer100-52-7498.0521.4695Strong sharp sweet bitter almond cherry36Benzaldehyde monomer100-52-7498.0521.1491Strong sharp sweet bitter almond cherry37Benzenemethanol100-51-6662.631.3237Floral rose phenolic balsamic38Cyclohexanone108-94-1331.5971.4537Minty acetone39Dimethyl disulphide624-92-0238.6641.1472Sulfurous vegetable cabbage onion40E-2-hexen-1-ol928-95-0324.7951.1757Fresh green leafy fruity unripe banana41(E, Z)-2, 6-nonadienal557-48-2874.6851.3705Green fatty dry cucumber violet leaf42Ethyl-2-methylbutanoate7452-79-1295.4521.2425Sharp sweet green apple fruity43Ethyl acetate141-78-6148.5781.3374Ethereal fruity sweet weedy green44Ethyl butyrate105-54-4297.0651.5575Fruity juicy fruit pineapple cognac45Ethyl pentanoate539-82-2393.11.6844Sweet fruity apple pineapple green tropical46Ethyl propanoate105-37-3194.5871.1507Sweet fruity rum juicy fruit grape pineapple47Furfural dimer1998/1/1305.7141.3334Sweet woody almond fragrant baked bread48Furfural monomer1998/1/1307.1591.0829Sweet woody almond fragrant baked bread49Gamma-butyrolactone dimer96-48-0423.4831.3024Creamy oily fatty caramel50Gamma-butyrolactone monomer96-48-0428.1341.0823Creamy oily fatty caramel51Heptanal dimer111-71-7399.9621.6938Fresh aldehydic fatty green herbal wine-lee ozone52Heptanal monomer111-71-7398.9641.3305Fresh aldehydic fatty green herbal wine-lee ozone53Hexanal dimer66-25-1270.351.5626Fresh green fatty aldehydic grass leafy fruity sweaty54Hexanal monomer66-25-1270.6131.2518Fresh green fatty aldehydic grass leafy fruity sweaty55Isoamyl acetate dimer123-92-2364.4951.7505Sweet fruity banana solvent56Isoamyl acetate monomer123-92-2365.851.3075Sweet fruity banana solvent57Isopentanol123-51-3239.5111.1195Fusel oil alcoholic whiskey fruity banana58Linalool78-70-6776.3371.2204Citrus floral sweet bois de rose woody green blueberry59Methional3268-49-3372.5221.0868Musty potato tomato earthy vegetable creamy60Acetic acid, methyl ester79-20-9122.6561.1938Ether sweet fruity61Methyl-5-furfural620-02-0512.5071.1275Spice caramel maple62n-Nonanal dimer124-19-6782.3021.9402Waxy aldehydic rose fresh orris orange peel fatty peely63n-Nonanal monomer124-19-6783.1051.472Waxy aldehydic rose fresh orris orange peel fatty peely64Octanal124-13-0600.4381.4018Aldehydic waxy citrus orange peel green fatty65Pentanal dimer110-62-3190.1971.4247Fermented bready fruity nutty berry66Pentanal monomer110-62-3190.4131.1796Fermented bready fruity nutty berry67Pentanoic acid109-52-4404.261.2271Sickening putrid acidic sweaty rancid68Phenylacetaldehyde dimer122-78-1670.4111.5386Green sweet floral hyacinth clover honey cocoa69Phenylacetaldehyde monomer122-78-1668.1931.2532Green sweet floral hyacinth clover honey cocoa70Phenylacetic acid103-82-21010.291.3311Sweet honey floral honeysuckle sour waxy civet71Propanal123-38-6109.4011.0436Earthy alcohol wine whiskey cocoa nutty72Propanoic acid1979/9/4232.8341.1038Pungent acidic cheesy vinegar73Propylsulfide111-47-7376.9511.1582Garlic onion74Toluene108-88-3228.1121.018Sweet75Z-3-hexen-1-ol928-96-1340.9591.5085Fresh green cut grass foliage vegetable herbal oilyThe retention time of a certain compound in the sample was determined by using the standard curves, the detected compounds in this work were referred to the IMS database. The odor data of these compounds are referred to the standard database of the Perflavory information system.


## 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 Figure3, 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.Figure 3
The fingerprint spectrum of aroma compounds in the tobacco samples from eight producing areas.


## 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 Figure4, 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.Figure 4
The principal component analysis of each sample.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 Table2. 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.Table 2
The similarity between samples.
Matching (%)YN-QJML-C3FYN-QJML-C3FYN-CHX-C3FYN-CHX-C3FYN-ZHT-C3FYN-ZHT-C3FSCH-LSHHD-C3FSCH-LSHHD-C3FSCH-GY-C3FSCH-GY-C3FSCH-LSHHL-C3FSCH-LSHHL-C3FGZH-QXXN-C3FGZH-QXXN-C3FGZH-ZY-C3FGZH-ZY-C3FYN-QJML-C3F100979090878889897777747483838888YN-QJML-C3F971009090878889897979777685858988YN-CHX-C3F909010099919287877878767785859090YN-CHX-C3F909099100919287877878767785869089YN-ZHT-C3F878791911009685858080787885858685YN-ZHT-C3F888892929610086868079787886868786SCH-LSHHD-C3F898987878586100987776727381819089SCH-LSHHD-C3F898987878586981007979747582829089SCH-GY-C3F777978788080777910099888886867777SCH-GY-C3F777978788079767999100898986867777SCH-LSHHL-C3F747776767878727488891009886867372SCH-LSHHL-C3F747677777878737588899810086867373GZH-QXXN-C3F838585858586818286868686100988282GZH-QXXN-C3F838585868586818286868686981008282GZH-ZY-C3F888990908687909077777373828210098GZH-ZY-C3F888890898586898977777273828298100


## 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.



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*Source: 3293899-2022-12-29.xml*