Abstract
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.
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Determination of Compounds in Eucommia ulmoides Oliv. Bark and Its Fermentation Products via Headspace Gas Chromatography-ion Mobility Spectrometry
Zhihong Wang,a,b Mijun Peng,a,* Zhigang She,b,* Yu Qiu,a Qiuling Yang,a Minglong Zhang,a Tao Huang,a Shuyun Shi,c and Changwei Zhang d
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.
Keywords: Ion mobility spectrometry; Eucommia ulmoides Oliv. bark; Characteristic volatile compounds; Fermentation product; Partial least squares discrimination analysis
Contact information: a: Guangdong Provincial Key Laboratory of Emergency Test for Dangerous Chemicals, Guangdong Institute of Analysis, Guangzhou 510070, China; b: School of Chemistry, Sun Yat-Sen University, Guangzhou 510275, China; c: College of Chemistry and Chemical Engineer, Central South University, Changsha 410083, China; d: Institute of Chemical Industry of Forest Products, CAF, Nanjing 210042, China; *Corresponding authors: pengmj163@163.com; cesshzhg@mail.sysu.edu.cn
INTRODUCTION
Ion mobility spectrometry (IMS) is a quick response, highly sensitive, and portable analytical technique for characterizing chemical substances based on the velocity of gaseous ions in an electrical field at ambient pressure (Holopainen et al. 2013; Tzschoppe et al. 2016). This method offers an alternative to conventionally used methods for both practical application and laboratory analysis. Ion mobility spectrometry is also more easily adapted to real time monitoring than many other analytical instruments (Márquez-Sillero et al. 2011). Operation of IMS does not require complex pre-processing preparation of the sample, and its efficiency has been demonstrated for analysis and characterization of volatile compounds in samples of diverse nature, environmental, and food samples (Garrido-Delgado et al. 2015; Chouinard et al. 2016; Zou et al. 2016; Gerhardt et al. 2017; Arroyo-Manzanaresa et al. 2018). At the same time, the ion mobility rate of IMS is only related to the substance itself, it is absolute, and the qualitative analysis is accurate. Therefore, the method is widely used in the detection and identification of flavor substances, drugs, explosives, and chemical agents (Hajialigol et al. 2012; Leonhardt 2013; Fink et al. 2014; Gallegos et al. 2017; Gerhardt et al. 2018; Mochalski et al. 2018; Li et al. 2019).
Although IMS has many advantages for complex samples, especially for complex systems in food and agricultural products, the analysis characteristics are often limited. When IMS is used as a detector to analyze complex samples, there is a problem of cross sensitivity, which mainly includes three cases: (i) Several compounds have highly similar mobility, such that it is difficult to distinguish these compounds; (ii) The ions of some compounds will quench each other in the ionization zone; (iii) When one or several compounds are concentrated, it will affect the formation of other compound ions, thus affecting the analysis and identification (Kanu and Hill 2004; Jafari et al. 2012). In contrast, the most prominent feature of conventional gas chromatography for compound detection is its high separation efficiency, which can analyze almost all volatile compounds. However, the analysis time of gas chromatography is generally measured in minutes, which cannot meet the needs of rapid analysis. Additionally, the retention time of gas chromatography (GC) may change with the change of the stationary phase, and it is difficult to qualitatively analyze the complex unknowns based only on the retained values. The combination of IMS with GC technology will overcome these limitations and obtain satisfactory analysis results. The basic analysis principle of GC-IMS is as follows: complex mixed samples are first separated by GC, then they enter the IMS reaction zone as a single component, and corresponding product ions are formed in the ionization zone. The product ions can enter the migration zone and be separated by two dimensions through ion gate pulse action. The separated product ions are detected after reaching the Faraday disk in turn (Limero et al. 2015; Puton and Namieśnik 2016; Zhang et al. 2016). Therefore, GC-IMS technology has a good application prospect in the analysis of volatile components in complex samples.
Taste and aroma are important features of plant resources. Therefore, the study of volatile metabolites can be used to define the sample quality, to characterize the sample, to evaluate changes during the grow process, and also to enable the standardization of sample making with better control of the process (Castro-Muñoz 2019). Availability of new or additional analytical techniques as supporting tools for currently used methods may be helpful to find the difference and characteristic compound from natural plant resources. Natural plant resources are rich in active ingredients and nutrients and have broad prospects for development and utilization. It is worth noting that two-way fermentation (plant matrix-fungal two-way solid fermentation engineering) is one of the effective biotechnologies for development and application of natural plant resources. Microorganisms are characterized by a wide variety and strong metabolic capacity. Biotransformation is currently the most promising method for discovering novel compounds (Akacha and Gargouri 2015). Many microorganisms produce new aroma substances when they grow on a plant-derived bio-based material as a fermentation substrate. There are four main types of flavor compounds produced by microbial fermentation: pyrazines, lactones, terpenes, and esters (Liese and Filho 1999; Akacha and Gargouri 2015; Vajpeyi and Chandran 2015). The basic principle of the technology is that the medicinal fungus is selected as the fermentation strain, and the medicinal material or the medicinal slag is used as the medicinal matrix to form a common fermentation combination, and under suitable conditions, they are subjected to solid fermentation. In this process, the drug matrix provides the nutrients required by the fungus, and is also affected by the enzymes from the fungus to change its own tissues and components, and to produce new chemical ingredients. Meanwhile, the flavor characteristics and appearance of the sample can be significantly improved. The fermentation product is also considered as a development material with high utilization value. Therefore, it is of the utmost research interest (Akacha and Gargouri 2015; Bel-Rhlid et al. 2018).
It is well known that Eucommia ulmoides Oliv. has always been one of the most nourishing herbs in China. Eucommia ulmoides Oliv. bark (EUb) contains many active ingredients, such as lignans, iridoids, flavonoids, phenylpropanoids, and polysaccharides, which have the effects of lowering blood pressure, regulating blood lipids, preventing osteoporosis, lowering blood sugar, calming nerves, and resisting fatigue (He et al. 2014; Hirata et al. 2014; Li et al. 2016; Zhu and Sun 2018). It has a high utilization value and is widely used in food, pharmaceutical, and cosmetic industries. In recent years, the chemical composition, activity, and bioavailability of EUb has continually been the focus of attention (Zhu and Sun 2018), but the composition of volatile components in EUb is often ignored. Moreover, the powerful potential of GC-IMS technology has not been previously adopted for the analysis of EUb, and the investigation of volatile components from fermentation products has rarely been reported. At the same time, the Ganoderma lucidum (GL) strain, Hericium erinaceus (HE) strain, and Griflola frondosa (GF) strain are important edible fungi and have obvious health benefits and medicinal value (Xu et al. 2010; He et al. 2017; Zhao et al. 2017) because the two-way fermentation of natural plants plays an important role in increasing the activity of raw materials and broadening the range of applications. Solid-state fermentation of different edible fungi and EUb may produce some novel compounds. Meanwhile, the separation of GC-IMS is based on the specific drift times that ionized compounds need to pass a fixed distance in a defined electric field. Therefore, this phenomenon is worth exploring, and it is also necessary to analyze the characteristic volatile components of EUb and its fermentation products using the GC-IMS method.
The objective of this study is to develop a quick and simple method to detect volatile substances and investigate the characteristics of volatile compounds from EUb and different edible fungi and fermentation products using the IMS technology. Fingerprints of different samples were established based on the composition of the characteristic compounds detected. Differences between the samples were also analyzed by fingerprints obtained and the partial least squares discrimination analysis (PLS-DA) model. Furthermore, some of the marked compounds were identified throughout the spectrum, and the composition and relative content in different samples were analyzed. These results will provide a reference for an in-depth understanding of the chemical composition of Eucommia ulmoides Oliv. resources and the application of EUb fermentation products.
EXPERIMENTAL
Materials
Eucommia ulmoides Oliv. bark was collected from Cili Du-zhong Forestry Centre (Zhangjiajie, China). The fresh bark was dried at 60 °C, and then the sample was pulverized and stored at 4 °C before use.
Ganoderma lucidum (GL) preservation strain (strain number GDMCC5.250), Hericium erinaceus (HE) preservation strain (strain number GDMCC5.66), and Griflola frondosa (GF) preservation strain (strain number GDMCC5.63) were purchased from Guangdong Institute of Microbiology Culture Collection (Guangzhou, China).
All of the reagents used in the experiment were of analytical grade. Ultrapure water (18 MΩ/cm, Milli-Q Plus system; Millipore, Bedford, MA, USA) was used throughout the work. Nitrogen gas with a purity of 5.0 was utilized during the samples analysis process.
Methods
Solid state fermentation process
The prepared sample of EUb powder was selected, and then an appropriate amount of water was added until the sample was wet. Then the sample was placed in the cultivation bag after being uniformly stirred. These samples were bandaged after being covered with a cotton plug and sterilized for 50 min at 121 °C. After the sample was cooled to room temperature, under aseptic conditions, the Ganoderma lucidum strain, Hericium erinaceus strain, Griflola frondosa strain, and Ganoderma lucidum-Griflola frondosa complex strain were inoculated into the fermentation medium of the EUb sample. Four fermentation groups were selected for experiments, and cultured in the dark at 24 to 28 °C until the mycelium was overgrown with the cultivation bag to stop the fermentation. Then, the sample was removed to obtain a different fermented fungus substance. These fermentation products were stored in low temperature conditions until analyzed. There were eight types of samples in the experiment: Ganoderma lucidum microbial strain (GL-M), Hericium erinaceus microbial strain (HE-M), Griflola frondosa microbial strain (GF-M), Eucommia ulmoides Oliv. bark (EUb), Ganoderma lucidum and Eucommia ulmoides Oliv. bark fermentation group (GL-EUb-F), Hericium erinaceus and Eucommia ulmoides Oliv. bark fermentation group (HE-EUb-F), Griflola frondosa and Eucommia ulmoides Oliv. bark fermentation group (GF-EUb-F), and Ganoderma lucidum-Griflola frondosa and Eucommia ulmoides Oliv. bark fermentation group (GL-GF-EUb-F).
Headspace (HS)-GC-IMS analysis
The GC–IMS instrument used (FlavourSpec®; Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany) was equipped with a heated splitless injector, which enabled direct sampling of the headspace from the samples. For better reproducibility, the instrument was coupled to an automatic sampler unit (CTC-PAL; CTC Analytics AG, Zwingen, Switzerland). Samples were analyzed by an IMS (FlavourSpec®; Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany) with a radioactive ionization source (H3) for ionization. The GC was equipped with a non-polar capillary column (FS-SE-54-CB, 94% methyl, 5% phenyl, and 1% vinyl silicone), with 15 m × 0.53 mm × 0.25 μm film thickness. For IMS measurement, different samples were weighed into 20-mL glass vials that were closed with polypropylene (PP) caps with polytetrafluoro-ethylene (PTFE)/silicon septa, and was incubated at 80 °C for 20 min. Then, a headspace volume of 300 μL was automatically injected via a heated syringe at 80 °C. The carrier gas (nitrogen gas) ramp was programmed as follows: the initial carrier gas flow was 2.0 mL/min, which was held for 2 min, then the flow was increased to 20 mL/min in 8 min, and the carrier gas flow was ramped up to 100 mL/min at 18 mL/min. Subsequently, the flow rate continued to increase to 150 mL/min at a rate of 5 mL/min. In addition, the carrier gas passed through the GC-IMS injector inserting the sample into the GC column. The samples were eluted using isothermal mode and driven to the ionization chamber. In this process, the compounds were ionized by a tritium source at atmospheric pressure. Then, the ions were placed into a drift tube (5-cm length) through the shutter grid. The flow of drift gas (nitrogen gas) flow was set at 150 mL/min. Each spectrum was obtained by an average of 32 scans (Tzschoppe et al. 2016).
Data analysis
Chemometric processing of the ion mobility data was completed with SPSS 19.0 (SPSS, Inc., Chicago, IL, USA) software. The PLS-DA was applied to reduce the dimensionality of the data set retaining the maximum variability present in the original data and eliminating possible dependence between variables. Data analysis of GC-IMS was performed using Laboratory Analytical Viewer (LAV) software (Version 2.000, G.A.S. Gesellschaft für Analytische Sensorsysteme mbH., Dortmund, Germany). An initial exploratory data analysis by PLS-DA was included using the area of different peaks selected from the topographic plot shown in the analysis results. Moreover, the differentiation of the sample by PLS-DA was also carried out using the whole spectral information and using SIMCA-P 14.0 (Umetrics, Umea, Sweden).
The GC-IMS analysis results were shown in a two-dimensional graph in which each analyte is represented by a spot that is characterized by the retention time (measured in seconds, on the y-axis), the drift time (measured in milliseconds, on the x-axis), and the intensity of the signal (Gerhardt et al. 2017; Cavanna et al. 2019).
RESULTS AND DISCUSSION
Topographic Plot of Different Samples
IMS is a simple, portable, and sensitive instrumental analytical technique for the detection and monitoring of volatile and semi-volatile compounds present in the natural extract (Gallegos et al. 2015). This technique is based on the gas-phase separation of the resulting ions under a weak electric field at ambient pressure. The migration velocity depends on the mass, size, structure, and spatial distribution of an internal electric charge. The light compact ions travel faster in the drift tube of the instrument and reach the detector before the heavier ions (Vautz et al. 2006). The IMS presents a faster method to determine quality characteristics of foodstuffs and has already been used to determine the separation of various samples via headspace analysis (Gallegos et al. 2015). Taking the analysis results of EUb as an example, a GC-IMS analysis results in a topographic plot as shown in Fig. 1. It is a two-dimensional map in which the y-axis represents the retention time in the chromatographic column (in seconds), the x-axis represents the drift time in the drift tube (in milliseconds), and the color of the signal intensity shows the relative content of the different compounds.
To improve the accuracy of data analysis, further analysis of retention time and relative content was performed by the software LAV to visualize all data analysis results as much as possible. Therefore, data preprocessing is necessary for data analysis and spectrum presentation. The smoothing procedure and baseline correction were used in the pre-processing (Arroyo-Manzanaresa et al. 2018). The second strategy consisted of the selection of individual signals from the topographic plot (Fig. 1) of the EUb samples to conduct the chemometric treatment.
Fig. 1. Imaging of volatile compounds represented by GC-IMS for EUb
Fig. 2. Comparison of ion migration chromatogram of different samples (edible fungi and Eucommia ulmoides Oliv. bark and its fermentation products)