HS-GC-IMS Analysis of Volatile Organic Compounds in Different Varieties and Harvesting Times of Rhizoma gastrodiae (Tian Ma) in Yunnan Province

Headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS) coupled with principal component analysis (PCA) was used to investigate the differences in volatile organic compounds (VOCs) in four different varieties of Yunnan Huang Tian Ma (containing both winter and spring harvesting times), Yunnan Hong Tian Ma, Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma. The results showed that the flavor substances of different varieties and different harvesting times of Rhizoma gastrodiae were mainly composed of aldehydes, alcohols, ketones, heterocycles, esters, acids, alkenes, hydrocarbons, amines, phenols, ethers, and nitrile. Among them, the contents of the aldehydes, alcohols, ketones, and heterocyclic compounds are significantly higher than those of other substances. The results of cluster analysis and fingerprint similarity analysis based on principal component analysis and Euclidean distance showed that there were some differences between different varieties of Yunnan Rhizoma gastrodiae and different harvesting times. Among them, Yunnan Lv Tian Ma and Wu Tian Ma contained the richest volatile components. Winter may be the best harvesting season for Tian Ma. At the same time, we speculate that the special odor contained in Tian Ma should be related to the aldehydes it is rich in, especially benzene acetaldehyde, Benzaldehyde, Heptanal, Hexanal, Pentanal, and butanal, which are aldehydes that contain a strong and special odor and are formed by the combination of these aldehydes.


Introduction
The main areas of origin and consumption of Rhizoma gastrodiae (Tian Ma) are in Asian countries [1], and its main distribution areas are shown in Figure 1.In many areas of China, Rhizoma gastrodiae is used by local people as a healthy and tasty food in stews, hot pots, and stir-fries [2].Currently, it is considered that the quality of Tian Ma from Yunnan, China is better and is well-recognized by consumers and the market.Rhizoma gastrodiae can be broadly classified into five species based on the different colors of the flowers, the flower stems, the shape of the tubers, and the water content of the tubers, including Wu Tian Ma (Gastrodia elata Bl. f. glauca S. Chow), Hong Tian Ma (Gastrodia elata Bl. f. elata ex S. Chou et S.C. Chen), Huang Tian Ma (Gastrodia elata Bl. f. flavida S. Chow), Lv Tian Ma (Gastrodia elata Bl. f. viridis Makino), and Song Tian Ma (Gastrodia elata Bl. f. alba).Among them, the species currently cultivated on a large scale are mainly Hong Tian Ma, Wu Tian Ma, and various hybrids of Tian Ma, while Song Tian Ma and Lv Tian Ma are very rare and not cultivated on a large scale, and Song Tian Ma is barely circulating in the market.Therefore, all varieties of Tian Ma except Song Tian Ma were collected and tested in this study.Studies have shown that there are significant differences in the chemical composition and pharmacological activity between different varieties of Rhizoma gastrodiae [3].
chemical composition and pharmacological activity between different varieties of Rhizoma gastrodiae [3].Not only is Rhizoma gastrodiae a food product, but it is also a medicinal plant with a wealth of active substances and health functions.Studies have shown that Rhizoma gastrodiae is rich in gastrodin, p-hydroxybenzyl alcohol, parishin, polysaccharides, sterols, organic acids, and other components [4], which also makes Rhizoma gastrodiae play a better protective role in the central nervous system and can significantly improve diseases such as Alzheimer's disease, vascular dementia, epilepsy, Parkinson's disease, and cerebral ischemia/reperfusion [5][6][7].As a result, Rhizoma gastrodiae has greater potential for development in the functional food and pharmaceutical markets, and Rhizoma gastrodiae-related functional foods are gradually appearing on the market and receiving attention from researchers and consumers alike.Therefore, research on the flavor of Rhizoma gastrodiae is particularly important if we want to develop functional foods that are satisfactory to consumers.However, some studies have shown that different origins and varieties have a greater impact on the active ingredients in fresh Rhizoma gastrodiae [8] and further influence the extent to which Rhizoma gastrodiae can perform its health functions.Also, differences in the volatile components of Rhizoma gastrodiae are among the most important factors affecting consumer acceptance.Flavor determines the organoleptic value of a food product and plays an important role in the identification of its nutritional value.Therefore, in this paper, four varieties of Yunnan Rhizoma gastrodiae, which are more widely distributed in the market and have two harvest seasons, were selected for the analysis and study of flavor components.
In recent years, there has been an increasing amount of research into the use of instrumental analytical techniques for the detection of volatile flavor components in food, which can give more objective analytical data on the substance being tested at the molecular level, complementing sensory analysis.Commonly used instrumental analytical techniques are the electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS).Of these, the E-nose is an intelligent system with rapid detection and high sensitivity [9].GC-IMS has the advantage Not only is Rhizoma gastrodiae a food product, but it is also a medicinal plant with a wealth of active substances and health functions.Studies have shown that Rhizoma gastrodiae is rich in gastrodin, p-hydroxybenzyl alcohol, parishin, polysaccharides, sterols, organic acids, and other components [4], which also makes Rhizoma gastrodiae play a better protective role in the central nervous system and can significantly improve diseases such as Alzheimer's disease, vascular dementia, epilepsy, Parkinson's disease, and cerebral ischemia/reperfusion [5][6][7].As a result, Rhizoma gastrodiae has greater potential for development in the functional food and pharmaceutical markets, and Rhizoma gastrodiae-related functional foods are gradually appearing on the market and receiving attention from researchers and consumers alike.Therefore, research on the flavor of Rhizoma gastrodiae is particularly important if we want to develop functional foods that are satisfactory to consumers.However, some studies have shown that different origins and varieties have a greater impact on the active ingredients in fresh Rhizoma gastrodiae [8] and further influence the extent to which Rhizoma gastrodiae can perform its health functions.Also, differences in the volatile components of Rhizoma gastrodiae are among the most important factors affecting consumer acceptance.Flavor determines the organoleptic value of a food product and plays an important role in the identification of its nutritional value.Therefore, in this paper, four varieties of Yunnan Rhizoma gastrodiae, which are more widely distributed in the market and have two harvest seasons, were selected for the analysis and study of flavor components.
In recent years, there has been an increasing amount of research into the use of instrumental analytical techniques for the detection of volatile flavor components in food, which can give more objective analytical data on the substance being tested at the molecular level, complementing sensory analysis.Commonly used instrumental analytical techniques are the electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS).Of these, the E-nose is an intelligent system with rapid detection and high sensitivity [9].GC-IMS has the advantage of high sensitivity for the characterization of volatile compounds, and it and E-nose are also widely used to distinguish authentic and adulterated samples because of their ease of operation [10][11][12].However, the reproducibility of E-nose assay results is slightly lower and has limitations in some assays [13,14].Studies have shown that GC-IMS is fast, sensitive, and easy to use [15].In addition, GC-IMS has outstanding high separation efficiency compared to GC-MS, allowing analytical results to be obtained in a shorter period, and the 3D spectral results include the retention time, drift time, and signal intensity, making qualitative analysis more accurate [12].In recent years, GC-IMS has been widely used for the study of volatile compounds in food and functional substances [15], e.g., shiitake mushrooms [16], green tea [17], and gum [18].GC-IMS has also been used more frequently in the field of food analysis in recent years and is developing rapidly.It has the advantages of a small sample size, simple operation, high sensitivity, and accurate results, and it is suitable for the characterization of volatile compounds with various properties [19,20].Very few studies have been carried out using HS-GC-IMS for the detection and analysis of volatile components in Rhizoma gastrodiae samples, and Sun et al. used GC-IMS to compare and analyze the differences in volatiles in fresh Rhizoma gastrodiae from different species and origins, which is a convenient and simple method to construct [8].In the same way, Qiu et al. used it for the detection of volatile chemical components in dried Rhizoma gastrodiae in Guizhou and found that the method is simple, rapid, accurate, and has a small sample size [21].However, studies on several species of dried Rhizoma gastrodiae have not been reported.Moreover, Qiu et al.'s study also tested and analyzed only one type of Rhizoma gastrodiae in Guizhou and did not further analyze the flavor variability of multiple varieties of Rhizoma gastrodiae in the region.
The richest source of Rhizoma gastrodiae is mainly in China, and Yunnan Rhizoma gastrodiae is commonly recognized in the Chinese Rhizoma gastrodiae trade, which may be related to the abundance of Rhizoma gastrodiae varieties of Yunnan origin and the maturity of local standardized cultivation and processing techniques.Currently, there are fewer studies on the variability of volatile flavor substances between different varieties of dried Rhizoma gastrodiae products.However, different varieties and harvesting times have a greater impact on the volatile components in Rhizoma gastrodiae and further influence the flavor and nutrition of the product.Therefore, during this comparative study, we compared Yunnan Huang Tian Ma (containing both winter and spring harvesting times), Yunnan Hong Tian Ma, Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma, which are the five Rhizoma gastrodiae species that differ in their volatile organic matter.It is hoped that this will provide some reference value for the processing and nutritional value of Rhizoma gastrodiae functional foods.

Analysis of Volatile Components in Different Rhizoma gastrodiae Samples by HS-GC-IMS
HS-GC-IMS was used to analyze the VOCs in five samples of Rhizoma gastrodiae.Figure 2 shows the 3D spectra generated by HS-GC-IMS, which contains data such as the retention time, drift time, and peak intensity, and different peak intensities are represented by the different sample VOCs.It can be visually observed in Figure 2 that there is some variation in the volatile chemical composition of the different Rhizoma gastrodiae samples.The differences in the peak intensities between the different species are circled in red in Figure 2.
The 3D spectrograms enabled an initial, but rather crude, observation of the general variability between the samples.Therefore, a 2D top view of the VOCs in the five Rhizoma gastrodiae samples was plotted using the Reporter plug-in (Figure 3), enabling a detailed comparison of the differences in VOCs between the different Rhizoma gastrodiae samples.The vertical coordinate indicates the retention time of the GC, and the horizontal coordinate indicates the drift time and the reactive ion peak (RIP.)The different-colored points on either side of the RIP represent the different VOCs detected.As can be seen from Figure 3A, most of the signal occurred at retention times of 80-970 s and drift times of 1.0-1.9ms.And the difference in color on either side of the peak elucidates the signal intensity of the different volatiles detected in each Rhizoma gastrodiae sample.The red signal indicates a higher concentration of the detected volatiles, and the darker the color, the higher the intensity, indicating a higher concentration of that volatile substance.The white color indicates lower concentrations of the detected volatiles.The 3D spectrograms enabled an initial, but rather crude, observation of the general variability between the samples.Therefore, a 2D top view of the VOCs in the five Rhizoma gastrodiae samples was plotted using the Reporter plug-in (Figure 3), enabling a detailed comparison of the differences in VOCs between the different Rhizoma gastrodiae samples.The vertical coordinate indicates the retention time of the GC, and the horizontal coordinate indicates the drift time and the reactive ion peak (RIP.)The different-colored points on either side of the RIP represent the different VOCs detected.As can be seen from Figure 3A, most of the signal occurred at retention times of 80-970 s and drift times of 1.0-1.9ms.And the difference in color on either side of the peak elucidates the signal intensity of the different volatiles detected in each Rhizoma gastrodiae sample.The red signal indicates a higher concentration of the detected volatiles, and the darker the color, the higher the intensity, indicating a higher concentration of that volatile substance.The white color indicates lower concentrations of the detected volatiles.
A differential contrast model was used to compare the differences between samples, using the Y-YS sample as the reference contrast and the remaining sample minus the reference.If the two VOCs agree, the background after subtraction is white; if it is red, it means that the substance concentration is higher than the reference, and blue means it is lower than the reference.In the differential contrast model plot (Figure 3B), the concentrations of the volatile substances can be seen.As can be seen in Figure 3B, there were large differences in the volatiles in the samples of Rhizoma gastrodiae of different species and different harvesting times.Comparing the samples Y-YS, Y-YW, and YR, in the range of 290-310 s for the retention time and 1.3-1.8ms for the drift time, Isovaleric acid, Hexanal, 2,3-Butanediol, and the concentrations of Octanal and 3-Octanol were significantly higher in Y-YW and YR than in Y-YS in the range of 590-610 s for the retention time and 1.7-2.3ms for the drift time.For 1.3-1.8ms, the VOC concentrations of 2-heptanone, Heptanal, n-Hexanol, pentanoic acid, N-nitrosodiethylamine and (E)-2hexenal were significantly higher in YB than in Y-YS.A comparison of the samples Y-YS and YG showed that the concentration of volatile components in the sample YG was significantly higher than that in the sample Y-YS.These data differences indicate that there is a greater variation in the volatile components of different varieties of Rhizoma gastrodiae.A differential contrast model was used to compare the differences between samples, using the Y-YS sample as the reference contrast and the remaining sample minus the reference.If the two VOCs agree, the background after subtraction is white; if it is red, it means that the substance concentration is higher than the reference, and blue means it is lower than the reference.In the differential contrast model plot (Figure 3B), the concentrations of the volatile substances can be seen.As can be seen in Figure 3B, there were large differences in the volatiles in the samples of Rhizoma gastrodiae of different species and different harvesting times.Comparing the samples Y-YS, Y-YW, and YR, in the range of 290-310 s for the retention time and 1.3-1.8ms for the drift time, Isovaleric acid, Hexanal, 2,3-Butanediol, and the concentrations of Octanal and 3-Octanol were significantly higher in Y-YW and YR than in Y-YS in the range of 590-610 s for the retention time and 1.7-2.3ms for the drift time.For 1.3-1.8ms, the VOC concentrations of 2-heptanone, Heptanal, n-Hexanol, pentanoic acid, N-nitrosodiethylamine and (E)-2-hexenal were significantly higher in YB than in Y-YS.A comparison of the samples Y-YS and YG showed that the concentration of volatile components in the sample YG was significantly higher than that in the sample Y-YS.These data differences indicate that there is a greater variation in the volatile components of different varieties of Rhizoma gastrodiae.This also indirectly suggests that under the present experimental conditions, Lv Tian Ma contains more flavor substances compared to other regions, which explains why it has a more pronounced aroma in all samples.
Previously, Sun et al. used GC-IMS to detect the differences in volatile components between three fresh Rhizoma gastrodiae varieties, namely, Hong Tian Ma, Wu Tian Ma, and the hybrid Rhizoma gastrodiae, and found that Wu Tian Ma was richer in volatile components than the two varieties of Rhizoma gastrodiae [8].Meanwhile, Cao et al. conducted a comparative study on the volatile components of Wu Tian Ma in different harvesting seasons based on E-nose and GC-IMS and found that winter was the suitable harvesting period for harvesting Rhizoma gastrodiae [22].Our study found that the YG samples contained the highest content of volatile substances and more species, followed by YB, and that winter-harvested Rhizoma gastrodiae had a higher content of volatile substances and species compared to spring-harvested Rhizoma gastrodiae.Our study's results are like the results of the previous study.It also shows from the side that under the present experimental conditions, Yunnan Lv Tian Ma and Wu Tian Ma have better quality compared to other origins and species of Rhizoma gastrodiae.The winter harvest of Rhizoma gastrodiae is its best harvesting period.

Identification of Volatile Components in Different Rhizoma gastrodiae Samples
In this study, HS-GC-IMS was used to analyze the differences in volatile organi compounds in Yunnan Huang Tian Ma (containing both winter and spring harvesting times), Yunnan Hong Tian Ma, Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma, fou species, and two harvest times, giving qualitative characterization information.As shown in Figure 4, the horizontal coordinates indicate the differential time, the vertica coordinates indicate the resolution time, and the red numbers correspond to the
Molecules 2023, 28, x FOR PEER REVIEW 7 of 19 Heptanal, 2-heptanone, pentan-1-ol, Hexanal, 3-methylbutanal, and butanal exist in monomeric and dimeric forms.Previously, Sun et al. used GC-IMS to analyze the differences in volatile compounds in three varieties of fresh Rhizoma gastrodiae, and a total of 75 volatile compounds were detected.Of these, 45 substances could be identified, including 16 aldehydes, 9 esters, 6 alcohols, 5 ketones, and 3 acids [8].Qiu et al. used HS-GC-IMS to identify 25 volatile components in Rhizoma gastrodiae and found that the most abundant compounds were aldehydes [21].Whereas our study similarly found that aldehydes were the most abundant component in Rhizoma gastrodiae, we detected a greater abundance of volatile components, presumably because Lv Tian Ma contributed a richer number of volatile components related to this.Previously, Sun et al. used GC-IMS to analyze the differences in volatile compounds in three varieties of fresh Rhizoma gastrodiae, and a total of 75 volatile compounds were detected.Of these, 45 substances could be identified, including 16 aldehydes, 9 esters, 6 alcohols, 5 ketones, and 3 acids [8].Qiu et al. used HS-GC-IMS to identify 25 volatile components in Rhizoma gastrodiae and found that the most abundant compounds were aldehydes [21].Whereas our study similarly found that aldehydes were the most abundant component in Rhizoma gastrodiae, we detected a greater abundance of volatile components, presumably because Lv Tian Ma contributed a richer number of volatile components related to this.

Topographic Results and Analysis of Five Rhizoma gastrodiae Samples
To compare differences in specific volatiles from each Rhizoma gastrodiae sample, the peaks of all samples were selected for fingerprint comparison (Figure 5).Each row of the graph represents the substance detected, and each column represents the signal intensity of the same volatile substance in different Rhizoma gastrodiae samples.Each dot represents a volatile substance, the shade of the color represents the level of the detected volatile substance, and the brighter the color, the higher the level.

Dynamics of the Sample
Principal component analysis (PCA) is a multivariate statistical analysis method that transforms the original correlated variables into linearly uncorrelated variables through multiple correlation transformations, providing researchers with a way to reduce the dimensionality of the data, thereby eliminating non-essential information [25,26] and more clearly reflecting the relationships between variables [27].Figure 6 shows the results of PCA analysis for all samples.In this case, the different colors represent different samples of Rhizoma gastrodiae, the distance between individual points represents the level of similarity, and the dispersion of the same points represents the homogeneity of the same sample.The results in Figure 6 show that the total contribution of the two principal components, Dim1 and Dim2, was 64.3%.Moreover, the volatile components of the different varieties of Rhizoma gastrodiae were significantly different, with the Yunnan Wu Tian Ma and Yunnan Hong Tian Ma samples clustered into one group and the Yunnan Lv Tian Ma showing significant differences from the other samples.The two samples of Yunnan Huang Tian Ma were clustered at a certain distance from each other at the time of harvesting.This also suggests that there were some previous differences between the two.Methyl isobutyl ketone, 5-methylfurfural, ortho-guaiacol, acetophenone, 1-heptanol, 3-methylthiopropanal, oct-1-en-3-ol, ethyl hexanoate, 2-methylpropanoic acid, ethyl 2hydroxypropanoate, ethylpyrazine, ethyl propanoate, 1-octen-3-one, hydroxyacetone, decalin, 2-acetylpyrazine, n -hexanol, 2,6-dimethylpyrazine, 3-methylbutyric acid, Nnitrosodiethylamine, pentanoic acid, 1,2-dimethylbenzene, furfural, ethyl butyrate, 2,4,5trimethylthiazole, and 2,3-butanediol were the characteristic substances of the samples except for Yunnan Lv Tian Ma (Box A).
Once again, the above results show that Yunnan Lv Tian Ma is the richest in volatile organic compounds, followed by aconite.For the species of Huang Tian Ma, winterharvested Rhizoma gastrodiae had more volatile components than spring-harvested Rhizoma gastrodiae, and ethylpyrazine was a unique volatile component of spring-harvested Rhizoma gastrodiae.Octanal, Butanoic acid methyl ester, and 3-Methyl-3-buten-1-ol are volatile components specific to the winter harvest.

Cluster Analysis of the Volatile Components of Five Rhizoma gastrodiae Samples 2.4.1. Dynamics of the Sample
Principal component analysis (PCA) is a multivariate statistical analysis method that transforms the original correlated variables into linearly uncorrelated variables through multiple correlation transformations, providing researchers with a way to reduce the dimensionality of the data, thereby eliminating non-essential information [25,26] and more clearly reflecting the relationships between variables [27].Figure 6 shows the results of PCA analysis for all samples.In this case, the different colors represent different samples of Rhizoma gastrodiae, the distance between individual points represents the level of similarity, and the dispersion of the same points represents the homogeneity of the same sample.The results in Figure 6 show that the total contribution of the two principal components, Dim1 and Dim2, was 64.3%.Moreover, the volatile components of the different varieties of Rhizoma gastrodiae were significantly different, with the Yunnan Wu Tian Ma and Yunnan Hong Tian Ma samples clustered into one group and the Yunnan Lv Tian Ma showing significant differences from the other samples.The two samples of Yunnan Huang Tian Ma were clustered at a certain distance from each other at the time of harvesting.This also suggests that there were some previous differences between the two.

Fingerprint Similarity Analysis Based on Euclidean Distance
Euclidean distance is like PCA analysis in that the principle used to determine similarity is the distance coefficient; if the coefficient is large, the difference between the two is also large and shows a positive correlation.Conversely, the smaller the coefficient, the smaller and more similar the difference between the two [28].The quality of the two samples was evaluated by the Euclidean distance similarity algorithm, and the algorithm was found to be accurate and reliable in evaluating the samples [28].Figure 7 shows the fingerprint similarity based on Euclidean distance, and Table S1 represents the Euclidean distance values between the five Rhizoma gastrodiae samples.From the results of the Euclidean distance analysis, it can be found that the distances between the different species of Rhizoma gastrodiae samples can be clearly distinguished.The average Euclidean distance between YG and YB was 14,900,000; the average Euclidean distance between YB and YR was 7,417,990.556;the average Euclidean distance between YR and Y-YW was 5,776,189.222;the average Euclidean distance between Y-YW and Y-YS was 5,332,821.778;and the average Euclidean distance was 28,244,444.444,so the distance between YG and Y-YS was the furthest, i.e., the difference between Yunnan Lv Tian Ma and Yunnan Huang Tian Ma (harvested in spring) was considered to be the most significant.It was also shown that the use of the HS-GC-IMS method was able to distinguish between samples of different species and different harvesting times of Rhizoma gastrodiae.

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Figure 6.Results of the PCA analysis of five Rhizoma gastrodiae samples.

Fingerprint Similarity Analysis Based on Euclidean Distance
Euclidean distance is like PCA analysis in that the principle used to determine similarity is the distance coefficient; if the coefficient is large, the difference between the two is also large and shows a positive correlation.Conversely, the smaller the coefficient, the smaller and more similar the difference between the two [28].The quality of the two samples was evaluated by the Euclidean distance similarity algorithm, and the algorithm was found to be accurate and reliable in evaluating the samples [28].Figure 7 shows the fingerprint similarity based on Euclidean distance, and Table S1 represents the Euclidean distance values between the five Rhizoma gastrodiae samples.From the results of the Euclidean distance analysis, it can be found that the distances between the different species of Rhizoma gastrodiae samples can be clearly distinguished.The average Euclidean distance between YG and YB was 14,900,000; the average Euclidean distance between YB and YR was 7,417,990.556;the average Euclidean distance between YR and Y-YW was 5,776,189.222;the average Euclidean distance between Y-YW and Y-YS was 5,332,821.778;and the average Euclidean distance was 28,244,444.444,so the distance between YG and Y-YS was the furthest, i.e., the difference between Yunnan Lv Tian Ma and Yunnan Huang Tian Ma (harvested in spring) was considered to be the most significant.It was also shown that the use of the HS-GC-IMS method was able to distinguish between samples of different species and different harvesting times of Rhizoma gastrodiae.

Hierarchical Cluster Analysis Heatmap
To further analyze the differences in VOCs between the different Rhizoma gastr samples, a hierarchical cluster analysis (HCA) heatmap was generated.HCA can be to distinguish between two sample clusters [29] and to analyze the degree of differen the composition of the samples tested [30,31].Figure 8 shows the HCA of volatiles in ferent Rhizoma gastrodiae samples.The outer circle represents the volatiles detected, each column at the opening of the circle indicates the name of each sample.The c

Hierarchical Cluster Analysis Heatmap
To further analyze the differences in VOCs between the different Rhizoma gastrodiae samples, a hierarchical cluster analysis (HCA) heatmap was generated.HCA can be used to distinguish between two sample clusters [29] and to analyze the degree of difference in the composition of the samples tested [30,31].Figure 8 shows the HCA of volatiles in different Rhizoma gastrodiae samples.The outer circle represents the volatiles detected, and each column at the opening of the circle indicates the name of each sample.The color indicates a low relative strength, with darker green indicating a stronger strength and a higher content and a lighter color indicating a weaker strength and a lower content.It is clear from Figure 8 that the relative content of volatile substances varied between samples.YG (Yunnan Lv Tian Ma) and YB (Yunnan Wu Tian Ma) samples contained higher and more diverse levels of volatile substances, which were significantly different from the other Rhizoma gastrodiae samples.For Huang Tian Ma, the volatile substances were closer in the two harvest times, winter and spring, but winter-harvested Rhizoma gastrodiae possessed a higher abundance of volatile substances and species than spring-harvested Rhizoma gastrodiae.This study used HS-GC-IMS to analyze VOCs in different Rhizoma gastrodiae samples, which has a more convenient operation, a fast response, a high sensitivity, and a low cost.
Molecules 2023, 28, x FOR PEER REVIEW

Sample Preparation
All Tian Ma samples were produced by Yunnan Zhaotong Xiaocaoba, were p by Yiliang County Xiaocaoba Wild Tian Ma Co, Ltd., and were dried produ appearance of the five species of Tian Ma is shown in Figure 9. Yunnan Huang (spring Harvest), Yunnan Huang Tian Ma (winter harvest), Yunnan Huang T Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma were crushed in a pulverizer and through a 24-mesh sieve to obtain the test samples Y-YS, Y-YW, YR, YB, and YG

Sample Preparation
All Tian Ma samples were produced by Yunnan Zhaotong Xiaocaoba, were provided by Yiliang County Xiaocaoba Wild Tian Ma Co, Ltd., and were dried products.The appearance of the five species of Tian Ma is shown in Figure 9. Yunnan Huang Tian Ma (spring Harvest), Yunnan Huang Tian Ma (winter harvest), Yunnan Huang Tian Ma, Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma were crushed in a pulverizer and filtered through a 24-mesh sieve to obtain the test samples Y-YS, Y-YW, YR, YB, and YG in turn.
by Yiliang County Xiaocaoba Wild Tian Ma Co, Ltd., and were dried products.Th pearance of the five species of Tian Ma is shown in Figure 9. Yunnan Huang Tian (spring Harvest), Yunnan Huang Tian Ma (winter harvest), Yunnan Huang Tian Ma, nan Wu Tian Ma, and Yunnan Lv Tian Ma were crushed in a pulverizer and filt through a 24-mesh sieve to obtain the test samples Y-YS, Y-YW, YR, YB, and YG in t

HS-GC-IMS System
We used the Gas-phase Ion Mobility Spectrum Flavor Spec ® (G.A.S. department of Shandong Province, China; Shandong Hai Neng Science Instrument Co., Ltd.) to analyze six different regions of Rhizoma gastrodiae powder prepared previously.We placed 2 g of Rhizoma gastrodiae powder in a 20 mL top-empty bottle and incubator for 20 min at 70 • C and 500 rpm under a gas phase temperature.Next, we set the temperature of the injection needle to 85 • C and injected 300 microliters of the sample.
Then, we performed gas chromatography separation using an MXT-5 chromatography column (15 m × 0.53 mm × 1 µm) at a column temperature of 60 • C. We set the IMS temperature to 45 • C and used N 2 (purity ≥ 99.999%) as the carrier/drift gas, with a flow rate of 2 mL/min (0-2 min), 10 mL/min (2-10 min), 100 mL/min (10-20 min), and 150 mL/min (20-30 min), stopping the analysis after 30 min.The drift tube is maintained at 45 • C under the N 2 drift gas with a flow rate of 150 mL/min.Three samples are measured for each sample.

Data Analysis
All samples were analyzed in triplicate.GC-IMS library Search software (Version number: 1.0.3) and the Laboratory Analytical Viewer (LAV) are data analysis software (Version number: 2.2.1) that allow different perspectives to be examined.The LAV includes VOCal and three plug-ins, and VOCal is used to view analytical spectra and qualitative and quantitative analysis data.Volatile organic compounds are represented by each point on the graph.With the software's built-in database, qualitative analyses of substances can be performed.A Reporter plug-in can be used to compare the spectral differences between different products, such as 2D top views and sample difference spectra.Using the library plot plug-in, differences in VOCs between the samples were visually compared using inter-sample fingerprinting.
To facilitate the rapid identification of unknown sample types, the peak volume data of the samples were normalized, the dynamic PCA plug-in was used for the cluster analysis of the samples.A principal component analysis was used to investigate the relationship between different samples and VOCs.Using the clustering heat map tool, heat maps were created.

Conclusions
In this study, HS-GC-IMS and PCA analyses were used to compare the differences in volatile organic compounds of Yunnan Huang Tian Ma (containing both winter and spring harvesting times), Yunnan Hong Tian Ma, Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma, four species, and two harvesting seasons of Rhizoma gastrodiae.A total of 160 signal peaks were identified and 95 compounds were characterized, including 24 aldehydes, 14 ketones, 15 alcohols, 13 heterocyclic compounds, 9 esters, 5 acids, 4 alkenes, 3 hydrocarbons, 3 amines, 2 phenols, 2 ethers, and 1 nitrile.At present, there are still 65 signal peaks that have not been identified, among which 7 components are unique to Wu Tian Ma, 18 components are unique to Lv Tian Ma, and the remaining signal peaks can be detected in all varieties of Rhizoma gastrodiae, which once again indicates that there is a richer variety of flavor compounds in Lv Tian Ma.However, from the results of the PCA, Euclidean distance, and hierarchical cluster analysis heatmap, the use of HS-GS-IMS can completely and effectively distinguish the two, and these unknown components can be further characterized and determined with the help of other analytical techniques in the future.
The results of the PCA analysis, cluster analysis based on Euclidean distance, and fingerprint similarity analysis showed that different species of Rhizoma gastrodiae contained mainly acetophenone, (E)-2-octenal, 1,2-dimethoxyethane, butanal, 3-methylbutanal, 2-hexanone hexanal, benzaldehyde, 2-methylpropionic acid, alpha-pinene, pyridine,2,4,6-trimethyl-, octanal, benzene acetaldehyde, (E)-hept-2-enal, (E)-hept-2-enal pentanal, nonanal, 2-ethylfuran, heptanal, tert-butylmethylether, isopropyl acetate, isopropyl alcohol, and 2-methylbutan-1-ol.There was some variation between varieties and harvesting seasons, with the YG (Yunnan Lv Tian Ma) and YB (Yunnan Wu Tian Ma) samples containing higher levels of volatile substances, more variety, and better quality.The samples harvested in winter had a higher content and variety of volatile substances compared to those harvested in spring, reflecting the superior quality of the winter-harvested Rhizoma gastrodiae.This suggests that differences in the species and harvesting time affect the results of volatile substances in Rhizoma gastrodiae.At the same time, we presume that the special smell of Rhizoma gastrodiae should be related to its richness in aldehydes, especially benzene acetaldehyde, Benzaldehyde, Heptanal, Hexanal, Pentanal, and butanal, which contain a strong combination of the special smell of aldehydes and the formation of these substances.
In conclusion, HS-GC-IMS was used in this study, which can detect the differences in volatile compounds in different varieties of Yunnan Rhizoma gastrodiae samples with different harvesting seasons for rapid analysis in a simple, rapid, and accurate way.The results of this study can help to provide certain references for the screening of raw materials and the improvement of the nutritional value of functional foods of Yunnan Tian Ma.

Figure 1 .
Figure 1.Schematic representation of the main distribution areas of Rhizoma gastrodiae.

Figure 1 .
Figure 1.Schematic representation of the main distribution areas of Rhizoma gastrodiae.

Figure 3 .
Figure 3. Topographic map of the five Rhizoma gastrodiae samples (A) and a comparative map of the differences between the five Rhizoma gastrodiae samples (B).

Figure 3 .
Figure 3. Topographic map of the five Rhizoma gastrodiae samples (A) and a comparative map of the differences between the five Rhizoma gastrodiae samples (B).

Figure 4 .
Figure 4. HS-GC-IMS profiles of five samples of Rhizoma gastrodiae (the different dots in the figure represent the identified volatile components, and the numbers correspond to the names of the identified volatile components in Table1).

Figure 4 .
Figure 4. HS-GC-IMS profiles of five samples of Rhizoma gastrodiae (the different dots in the figure represent the identified volatile components, and the numbers correspond to the names of the identified volatile components in Table1).

Molecules 2023 , 19 Figure 5 .
Figure 5. Fingerprints of the five Rhizoma gastrodiae samples (A-D) indicate the four discussion areas selected below the letters).

Figure 5 .
Figure 5. Fingerprints of the five Rhizoma gastrodiae samples (A-D) indicate the four discussion areas selected below the letters).

Figure 6 .
Figure 6.Results of the PCA analysis of five Rhizoma gastrodiae samples.

Figure 7 .
Figure 7. Fingerprint similarity based on the Euclidean distance of different samples.

Figure 7 .
Figure 7. Fingerprint similarity based on the Euclidean distance of different samples.

Figure 8 .
Figure 8. HCA of volatile components in five samples of Rhizoma gastrodiae.

Figure 8 .
Figure 8. HCA of volatile components in five samples of Rhizoma gastrodiae.