Direct authentication of three Chinese materia medica species of the Lilii Bulbus family in terms of volatile components by headspace-gas chromatography-ion mobility spectrometry

2019 ◽  
Vol 11 (4) ◽  
pp. 530-536 ◽  
Author(s):  
Zhi-ying Yuan ◽  
Hao-yu Qu ◽  
Meng-zhou Xie ◽  
Guang Zeng ◽  
Hui-yong Huang ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Rapid Method ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Volatile Components ◽  
Headspace Gas Chromatography ◽  
Chinese Materia Medica ◽  
Materia Medica ◽  
Headspace Gas

This research is aimed at establishing a green, rapid method based on HS-GC-IMS to identify three species of Lilii Bulbus.

scholarly journals Characterization of Volatile Component Changes in Jujube Fruits during Cold Storage by Using Headspace-Gas Chromatography-Ion Mobility Spectrometry

Molecules ◽  
2019 ◽  
Vol 24 (21) ◽  
pp. 3904 ◽  
Author(s):  
Lvzhu Yang ◽  
Jie Liu ◽  
Xinyu Wang ◽  
Rongrong Wang ◽  
Fang Ren ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Cold Storage ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Volatile Component ◽  
Volatile Components ◽  
Headspace Gas Chromatography ◽  
Dipropyl Disulfide ◽  
Headspace Gas ◽  
Zizyphus Jujuba

Volatile components in jujube fruits from Zizyphus jujuba Mill. cv. Dongzao (DZ) and Zizyphus jujuba Mill. cv. Jinsixiaozao (JS) were analyzed under different cold storage periods via headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). Results identified 53 peaks that corresponded to 47 compounds and were mostly alcohols, aldehydes, esters, and ketones. Differences in the volatile components of jujube fruits were revealed in topographic plots and fingerprints. For DZ, 3-pentanone was the characteristic component of fresh fruits. After storage for 15 days, dipropyl disulfide became the most special substance. Moreover, when stored for 30 and 45 days, the fruits had some same volatile components, like 2-pentyl furan and diallyl sulfide. However, for DZ stored for 60 days, esters were the prominent constituent of the volatile components, simultaneously, some new alcohols appeared. For JS, 2-ethyl furan was the representative of fresh fruits, and 2-butoxyethanol content was the most abundant after 15 and 30 days of storage. Different from that in DZ, the content of ester in JS increased after storage for 45 days. Substances such as amyl acetate dimer, methyl salicylate, and linalool greatly contributed to the jujube flavor during the late storage period. Principal component analysis (PCA) showed that fresh samples and refrigerated fruits were effectively distinguished. Heat map clustering analysis displayed the similarity of volatile components in different samples and was in accordance with PCA results. Hence, the volatile components of jujube fruits can be readily identified via HS-GC-IMS, and jujube fruits can be classified at different periods based on the difference of volatile components.

scholarly journals Changes in the Volatile Components of Candied Kumquats in Different Processing Methodologies with Headspace–Gas Chromatography–Ion Mobility Spectrometry

Molecules ◽  
2019 ◽  
Vol 24 (17) ◽  
pp. 3053 ◽  
Author(s):  
Xiao Hu ◽  
Rongrong Wang ◽  
Jiajing Guo ◽  
Keda Ge ◽  
Gaoyang Li ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Principal Component ◽  
Volatile Components ◽  
Headspace Gas Chromatography ◽  
Hot Air Drying ◽  
Air Drying ◽  
Hot Air ◽  
Headspace Gas

The effects of two different processing methods on the volatile components of candied kumquats were investigated via headspace–gas chromatography–ion mobility spectrometry (HS–GC–IMS). The characteristic volatile fingerprints of fresh kumquats (FKs), vacuum sugaring osmosis combined with hot-air drying kumquats (VS-ADKs), and atmospheric pressure sugaring osmosis combined with hot-air drying kumquats (AS-ADKs) were established using 3D topographic plots. From the fingerprints, 40 signal peaks for 22 compounds were confirmed and quantified in all types of kumquats, namely, two terpenes, four esters, seven aldehydes, three ketones, and six alcohols. 3-Pentanone was identified as the major component of FKs; followed by 1-hexanol and the Z-3-hexen-1-ol dimer. The hexanal dimer, 2-hexen-1-ol, and the ethyl acetate dimer were the major markers of VS-ADKs. Benzaldehyde and furfurol were the prominent constituent parts of AS-ADKs. Compared with that in FKs, the pentanal and dimethyl ketone contents of VS-ADKs and AS-ADKs exhibited a dramatic increase (p < 0.05). By contrast, the change in ethanol dimer tended to decrease (p < 0.05). Principal component analysis (PCA) clearly showed that the samples, which were distributed in a separate space could be well-distinguished. Furthermore, the similarity of different processed kumquats and their corresponding volatile components was demonstrated via heat map clustering analysis. The results confirmed the potential of HS–GC–IMS-based approaches to evaluate processed kumquats with various volatile profiles.

scholarly journals Determination of compounds in Eucommia ulmoides Oliv. bark and its fermentation products via headspace gas chromatography-ion mobility spectrometry

BioResources ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 6941-6959
Author(s):  
Zhihong Wang ◽  
Mijun Peng ◽  
Zhigang She ◽  
Yu Qiu ◽  
Qiuling Yang ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Signal Intensity ◽  
Volatile Components ◽  
Eucommia Ulmoides ◽  
Headspace Gas Chromatography ◽  
Edible Fungi ◽  
Fermentation Products ◽  
Headspace Gas

The flavor fingerprint of Eucommia ulmoides Oliv. bark (EUb) and its fermentation product were investigated, and volatile compounds were analyzed using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with partial least squares discrimination analysis (PLS-DA). A total of 71 peaks were identified, of which 51 target compounds were characterized, including alcohols, aldehydes, acids, and esters. The gallery plot contained 186 signal peaks. The results indicate there were significant differences in the volatile constituents of the three edible fungi. Furthermore, EUb also had its own unique composition of volatile components, and after fermentation with different edible fungi, the volatile components in the product changed significantly compared to the raw materials. A PLS-DA was performed based on the signal intensity of the target volatile compounds obtained; the results clearly showed that the samples (edible fungi, EUb, and different fermentation products) in a relatively independent space were well distinguished. This further illustrated that the composition and content of volatile components from EUb were significantly changed by microorganisms through bio-fermentation. Combining the signal intensity of the flavor substance, the difference between the different fermentation products was also clearly observed, and the flavor compound’s fingerprint was established by HS-GC-IMS and PLS-DA methods.

scholarly journals A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

2021 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Bahareh Sarmadi ◽  
Paul Kilmartin
Keyword(s):  
Gas Chromatography ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Aroma Compounds ◽  
Headspace Gas Chromatography ◽  
Static Headspace ◽  
Simultaneous Quantification ◽  
Static Headspace Gas Chromatography ◽  
Boltzmann Function ◽  
Headspace Gas

A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. Potential pitfalls that would cause inaccurate quantification i.e., effects of ethanol content and competitive ionization, were also discussed. The performance of the SHS-GC-IMS method was subsequently compared against a currently established method, namely, GC-MS, using actual wine samples. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.

scholarly journals Untargeted Headspace-Gas Chromatography-Ion Mobility Spectrometry in Combination with Chemometrics for Detecting the Age of Chinese Liquor (Baijiu)

Foods ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2888
Author(s):  
Shuang Chen ◽  
Jialing Lu ◽  
Michael Qian ◽  
Hongkui He ◽  
Anjun Li ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Goodness Of Fit ◽  
Accurate Method ◽  
Headspace Gas Chromatography ◽  
Least Squares Regression ◽  
Chinese Liquor ◽  
Headspace Gas ◽  
Discriminant Models

This paper proposes the combination of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and chemometrics as a method to detect the age of Chinese liquor (Baijiu). Headspace conditions were optimized through single-factor optimization experiments. The optimal sample preparation involved diluting Baijiu with saturated brine to 15% alcohol by volume. The sample was equilibrated at 70 °C for 30 min, and then analyzed with 200 μL of headspace gas. A total of 39 Baijiu samples from different vintages (1998–2019) were collected directly from pottery jars and analyzed using HS-GC-IMS. Partial least squares regression (PLSR) analysis was used to establish two discriminant models based on the 212 signal peaks and the 93 identified compounds. Although both models were valid, the model based on the 93 identified compounds discriminated the ages of the samples more accurately according to the goodness of fit value (R2) and the root mean square error of prediction (RMSEP), which were 0.9986 and 0.244, respectively. Nineteen compounds with variable importance for prediction (VIP) scores > 1, including 11 esters, 4 alcohols, and 4 aldehydes, played vital roles in the model established by the 93 identified compounds. Overall, we determined that HS-GC-IMS combined with PLSR could serve as a rapid and accurate method for detecting the age of Baijiu.

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