HS-GC-IMS Detection Of Volatile Organic Compounds in Cistanche Powders Under Different Treatment Methods
Jul 13, 2022
3.3. Gallery plots of cistanche with different treatments processing
To clearly to compare the differences in specific volatile substances in cistanche from each treatment, select all peaks below for fingerprint comparison (Fig. 4). Each row in Fig. 4 represents all the signal peaks selected in the sample, and each column represents the signal intensity of the same volatile substance in different samples, the shade of the color of the individual points represents the content of the substance in the sample, and the brighter the color indicates the higher the content of the volatile component in the sample. The figures in Fig. 4 represent substances that have not yet been characterized in the migration spectrum library detected in the sample.
Fig. 4. Fingerprint of volatile compounds of cistanche. a: synergistic cistanche powder, b: fresh cistanche powder, c: super micro meat cistanche powder, d: the water extract of Cistanches Herba powder, e: the ethanol extract of Cistanches Herba powder.
As shown in Fig. 4, a has the least VOC species and concentrations, and b has the most volatile substances and most of the concentrations. It can be seen that synergistic treatment will accelerate the volatilization of volatile substances in cistanche, so that the content and types of volatile substances retained in cistanche are reduced. As can be seen from Fig. 4, the volatile substances detected in acetoin are mainly acetoin, marked as region A in the figure. About b, the volatile substances detected are 2-methylpropanol, 3-methylbutyral, 2-methylbutyral, valeraldehyde, propyl acetate, phenylacetaldehyde, linalool, E−2-caprylyl, E−2-heptanal, E−2-hexanal, E−2-valeraldehyde, methylheptenone, octanal, 2-pentylfuran, etc., marked as B region in Fig. 4, among them, E−2-hexanal, E−2-heptanal, 2-methylbutyraldehyde, E−2-caprylyl, E−2-valeraldehyde, octanaldehyde, methylheptenone and 2-methylpropanol have monomer and dimer forms. The volatile substances detected in c include heptanal, 2,3-butanedione, nonaldehyde and E−2-nonal, etc., which are labeled as region C in Fig. 4, wherein nonaldehyde and heptanal have two forms: monomer and dimer. The volatile substances detected in d are methylpropionaldehyde, 3-methylthioalcuraldehyde and furfural, etc. Which are marked as region D in Fig. 4, among them, methylpropionaldehyde and furfural exist in two forms. The volatile substances detected in e are ethyl acetate and n-propanol, etc, which are labeled as the E region in Fig. 4, ethyl acetate is present in monomer form.
From Fig. 4, it can be found that the characteristic volatile substance of cistanche with synergistic treatment was acetoin, the characteristic volatile substances of fresh cistanche are mainly alcohols, aldehydes and ketones, and the volatile substances of cistanche after ultra-micro treatment are mainly aldehydes, and the characteristic components of cistanche water powder are also mainly aldehydes, but they are different from the aldehyde substances in ultra-microtreatment. The cistanche alcohol powder contains esters and alcohols, which are more recognizable in flavor and have a special flavor. In related studies, it was found that an increase in alcohol concentration contributed to an increase in ester content and variety, this may be one of the reasons for the volatile organic compounds that affect cistanche(Wei, Ma, Cao, Sun, & Fang, 2018). Most of the ketones have a taste of milky and fruity(Feng, Wang, Ji, Min, & Yan, 2021), which can be used as an index to evaluate the oxidized flavor, and the characteristic volatile ingredient in the synergistic cistanche powder is acetone, which can be considered to enhance the fruity flavor of cistanche, but there is a disadvantage of easy oxidation. Moreover, cistanche may undergo chemical changes between various chemicals during the cooking process, which may be one of the reasons for the reduction of chemical content and types in synergistic cistanche(Ai, Zhang, Li, Sun, & Liu, 2021). In the study of the volatile components of yellow tea, it was found that geraniol and linalool are high and are the main volatile compounds with pure, sweet aromas(Shi et al., 2021). Geraniol and linalool have also been reported to be important volatiles in green and black teas, playing an important role in the aroma quality of tea leaves(Joshi & Gulati, 2015; Liu et al., 2018), and among the five samples, linalool content was highest in fresh cistanche, suggesting that fresh cistanche may be more suitable for making sliced cistanche drinks. Ethyl acetate is a volatile component with a fruity flavor, which is often used as an important basis for judging the volatile components of fruit juices and liquors. In flavored liquors, ethyl acetate is one of the key compounds in judging flavor(J. Tang et al., 2021). Ethyl acetate in cistanche is a characteristic volatile compound with a unique fragrance, and according to this characteristic, a series of cistanche wine products can be developed. Nonaldehyde has a sweet taste and fruity flavor(Nunes, Coimbra, Saraiva, & Rocha, 2008), and the content of nonaldehyde in the cistanche water extract is high, which can be considered to have a sweet taste and fruity flavor, and on this basis, powder preparation products can be developed. In addition, quantitative analysis can be carried out according to the characteristic volatile compounds present in cistanche after different treatments, and a volatile compound database can be established to provide a theoretical basis for the quality identification of cistanche-related products.
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3.4. Clustering analysis of different treatments of cistanche
3.4.1. Dynamic PCA of samples
Principal component analysis (PCA) was a multivariate statistical method. It evaluates the regularity and difference between samples through data dimensionality reduction processing, and is mainly applied to clustering analysis of data and visualization of high-dimensional data(M. Q. Li et al., 2019; Yao et al., 2020). High-quality principal component analysis models are generally considered to be models that have a cumulative contribution rate of 60% or more for PC1 and PC2(Feng, Wang, He, et al., 2021)。
Through the principal component analysis of cistanche, it is found that PC1 is 54%, PC2 is 19%, and the cumulative total contribution rate is 73%, which can be considered as a high-quality model to distinguish the effects of different treatment methods on the volatile substances of cistanche. As shown in Fig. 5, a is located in the negative score of PC2 and the 0 region of PC1, d is located in the positive score of PC2 and the negative score area of PC1, b is located in the positive score of PC2 and the positive value of PC1, e is located in the negative score area of PC2 and the negative score of PC1, c is located in the negative score of PC2 and the positive score area of PC1, there is a clear degree of differentiation between the five, where the position of b, c, d and e is similar to the four quadrants of the coordinate axis, and the position of a position is similar to the negative half axis of the vertical axis, There is a clear distinction between positive and negative regions. The results showed that different treatments had a large difference in the flavor substances of cistanche, and HS-GC-IMS in combination with multivariate statistics is an efficient tool to have an intuitive and fast result of cistanche powder samples. However, the main reflection from this analysis was that there are differences in volatile organic compounds between different treatments of cistanche, and the relationship between each volatile compound and treatment is not clear. In similar research, by analyzing the variation relationship between the main volatile organic compounds of coffee beans from different sources in the roasting process,. It has been clearly found that the dominant chemical components in coffee beans of different origins and the relationship between them have been clearly identified(Gancarz et al., 2022); Khodamoradi et al. (Khodamoradi, Mirzaee-Ghaleh, Dalvand, & Sharifi, 2021) compared PCA analysis with two other analytical methods to identify significant differences in the influence of volatile organic compounds in Basil on nitrogen fertilizer application.
Fig. 5. PCA of Different samples. a: synergistic cistanche powder, b: fresh cistanche powder, c: super micro meat cistanche powder, d: the water extract of Cistanches Herba powder, e: the ethanol extract of Cistanches Herba powder.
3.4.2. Fingerprint similarity analysis by using euclidean distance
Euclidean distance is a cluster analysis method, the principle of determining the similarity of this method is the distance coefficient, if the coefficient is large, the difference between the two is also large, showing a positive correlation. Conversely, the smaller the coefficient, the smaller and more similar the difference between the two(Sun, Yan, Hou, Li, & Wang, 2015; Y. Z.; Tang, 2019). By applying the Euclidean distance similarity algorithm to evaluate the quality of two Chinese medicinal herbs, it was found that the algorithm can accurately and reliably evaluate the quality of Chinese medicines(Q.H., Z., J.Y., & J.W., 2018). Fig. 6 shows fingerprint similarity based on Euclidean distance, and Table 2 represents the Euclidean distance values between the five.
Fig. 6. Fingerprint Similarity based on Euclidean distance of Different samples. a: synergistic cistanche powder, b: fresh cistanche powder, c: super micro meat cistanche powder, d: the water extract of cstanches herba powder, e: the ethanol extract of cistanches herba powder.
4. Conclusion
In summary, the results of the present study demonstrate that the HS-GC-IMS method was used to detect flavor compounds in cistanche powder treated in different ways, with a total of 48 peaks, 32 compounds identified, including 5 ketonesone, 5 alcohol, 17 aldehydesaldehyde, 1 furans, 1lactone lactone, 3 ester ester. Due to the limitations of HS-GS-IMS detection and the fact that 34 signal peaks have not yet been determined, further qualitative analysis can be performed by GC-MS (Gas chromatography-mass spectrometry) or HPLS-MS (High Performance Liquid Chromatography-Mass Spectrometry).
Through spectrogram analysis, it can be intuitively found that the cistanche powder contains more ester compounds, which can be used as one of the characteristics of the product to identify the ethanol extraction cistanche product. At the same time, it was found that the variety of volatile compounds in cistanche after synergistic treatment was reduced, but acetoin could be used as a characteristic marker. Fresh cistanche can preserve more kinds of volatile compounds to a greater extent. If the VOCs are mainly aldehydes found in the test, it may be cistanche after ultra-micro treatment and water extraction treatment. Moreover, through principal component analysis, it was found that the five treatment methods had significant differences in the composition effect of volatile chemicals in cistanche. In the same type of study, esters and olefins were identified as the key volatiles to distinguish the Fuji apple category, and it was found that the bagging environment could reduce the aroma difference between various types of apples(Yudong, Haijing, Zhen, Zhemin, & Xian, 2021). In the analysis of Dongbei Suancai's characteristic volatile substances by HS-GC-IMS and PCA, the difference in VOCs content at each fermentation stage was clarified and 3-methyl butanol was determined to be a characteristic substance produced by fermentation after the addition of the starter culture Lactobacillus plantarum LND 399(Han, Wang, Zhang, Li, & Gao, 2022). To further understand the relationship between the ingredients and the treatment of cistanche, a simple linear relationship can be used in subsequent studies for correlation analysis(Granato, Santos, Escher, Ferreira, & Maggio, 2018). Finally, based on the euclidean distance to judge and analyze the fingerprint similarity, and the volatile substances in fresh cistanche powder and water-lifted cistanche powder were the most significant, and the relationship between each volatile organic component and treatment mode could be further studied in combination with electronic nose or HPLS-MS and GC-MS.
With these advantages, the combination of HS-GC-IMS and PCA serves as a useful tool with which to identify and classify cistanche samples, which has potential application value in the food industry.
