Abstract
Data obtained with gas chromatography coupled with ion mobility spectrometry (GC-IMS) was explored to investigate the characteristics of volatile compounds from edible fungus, from Eucommia ulmoides Oliv. leaves (EUl) that served as growth medium, and from their fermentation products. A total of 162 signal peaks were found, of which 68 compounds were identified, including alcohols, aldehydes, ketones, acids, and esters. There were differences in the volatile constituents of the edible fungi. EUl also contained special volatile components. The volatile components in the fermentation product were different compared to the raw material, and the difference in composition and content of the characteristic compounds was also obvious. The best classification performance was obtained by principal component analysis (PCA) based on the signal intensity of the characteristic volatile compounds. The results clearly showed that the samples (edible fungi, EUl and fermentation products) in a relatively independent space would be well distinguished. This further illustrated that the composition and content of volatile components of EUl could be changed by different microbial strains through biofermentation technology. Combining the signal intensity of the flavor substance, the difference was also clearly observed. This result suggested that the flavor compounds fingerprint could be established by GC-IMS and PCA.
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Development of a Flavor Fingerprint by Gas Chromatography Ion Mobility Spectrometry with Principal Component Analysis for Volatile Compounds from Eucommia ulmoides Oliv. Leaves and its Fermentation Products
Zhihong Wang,a,b Mijun Peng,a,* Zhigang She,b,* Minglong Zhang,a and Qiuling Yang a
Data obtained with gas chromatography coupled with ion mobility spectrometry (GC-IMS) was explored to investigate the characteristics of volatile compounds from edible fungus, from Eucommia ulmoides Oliv. leaves (EUl) that served as growth medium, and from their fermentation products. A total of 162 signal peaks were found, of which 68 compounds were identified, including alcohols, aldehydes, ketones, acids, and esters. There were differences in the volatile constituents of the edible fungi. EUl also contained special volatile components. The volatile components in the fermentation product were different compared to the raw material, and the difference in composition and content of the characteristic compounds was also obvious. The best classification performance was obtained by principal component analysis (PCA) based on the signal intensity of the characteristic volatile compounds. The results clearly showed that the samples (edible fungi, EUl and fermentation products) in a relatively independent space would be well distinguished. This further illustrated that the composition and content of volatile components of EUl could be changed by different microbial strains through biofermentation technology. Combining the signal intensity of the flavor substance, the difference was also clearly observed. This result suggested that the flavor compounds fingerprint could be established by GC-IMS and PCA.
Keywords: Eucommia ulmoides Oliv. leaves; Gas chromatography-ion mobility spectrometry; Fermentation product; Characteristic volatile compounds; Principal component analysis
Contact information: a: Guangdong Provincial Key Laboratory of Emergency Test for Dangerous Chemicals, Guangdong Institute of Analysis (China National Analytical Center Guangzhou), Guangdong Academy of Sciences, Guangzhou, 510070, China; b: School of Chemistry, Sun Yat-Sen University, Guangzhou 510275, China;
* Corresponding authors: pengmj163@163.com; cesshzhg@mail.sysu.edu.cn
INTRODUCTION
Ion mobility spectrometry (IMS) technology was developed in recent years and was initially used for rapid detection of drugs, explosives, and chemical agents (Shvartsburg 2010; Armenta et al. 2011). The working principle of IMS is that the sample to be tested is vaporized by the ion source and becomes a gaseous molecule, which is chemically ionized and carries a certain amount of electric charge. Then, different target ions will produce corresponding ion spectra in the electric field. This method has the advantages of fast detection speed and high sensitivity (Karpas 2013). However, for complex samples systems in food and agricultural products, the analysis process is often limited (Arce et al. 2014). The combination with gas chromatography (GC) technology will overcome the limitations of IMS separation efficiency, and at the same time give full play to the advantages of different instruments (Bunkowski et al. 2010). Under this condition, the ion mobility spectrum enriches the chemical information obtained by chromatographic separation by drift time information; meantime, the ion mobility spectrum signal response is significantly improved in mass and quantity after pre-separation by GC (Zhang et al. 2016; Garrido-Delgado et al. 2018). The three-dimensional matrix (migration time, retention time, and signal strength) obtained by gas chromatography-ion mobility spectrometry (GC-IMS) provides richer chemical information for more comprehensive data processing (Garrido-Delgado et al. 2012; Hajialigol et al. 2012; Zhang et al. 2016; Garrido-Delgado et al. 2018). Research results show that GC-IMS technology combined with chemometric methods is being gradually applied in the field of food testing and natural active ingredient analysis (Fink et al. 2014; Gallegos et al. 2015; Garrido-Delgado et al. 2015a, 2015b; Gallegos et al. 2017; Gerhardt et al. 2017, 2018; Mochalski et al. 2018). In this process, principal component analysis (PCA) is a commonly used feature for extraction and application of data dimensionality reduction in chemometrics (Jourdren et al. 2017; Pu et al. 2019).
For the GC-IMS technology, the complex sample is initially separated by GC technology, and then it is analyzed by an IMS detector. This combination technology can greatly improve the accuracy of mixture detection. Additionally, because GC separation is completed in seconds to minutes, while IMS detection time is measured in milliseconds, the detection time is greatly reduced compared with conventional chromatography, so it can meet the needs of the field of rapid analysis. (Politis et al. 2010; Jafari et al. 2012; Liedtke et al. 2018). The sample can be treated by GC prior to testing, which also effectively reduces the effect of humidity on IMS. Finally, a three-dimensional spectrum containing retention time, drift time, and signal strength can be obtained, which also makes the qualitative analysis more accurate. And both GC and IMS can operate under atmospheric pressure, they are easy to operate, and low in cost (Jafari et al. 2012). So the combined technology of GC and IMS has been widely considered.
At present, GC-IMS is considered an important technology for detecting volatile components from complex samples. Meanwhile, volatile components (flavor substances) are an important factor in the popularity of food, consumer acceptance, and are a vital indicator of the difference between different types of food (Cohen et al. 2015; Fang et al. 2017). Microbial conversion is a method with the most potential to improve taste and flavor. Compared with common chemical synthesis technology, this technology has the advantages of high chemical specificity, positional specificity, and stereospecificity. And the simple operation process makes it more economical and environmentally friendly (Akacha and Gargouri 2015). In addition, edible fungi can produce characteristic volatile components through their own metabolism (Vajpeyi and Chandran 2015).
Modern biofermentation technology is based on the fermentation method of traditional Chinese medicine processing and combined with micro-ecological research results and modern microbial engineering technology to form a new sample processing method (Liese and Filho 1999). On the basis of solid fermentation, the bi-directional solid-state fermentation technology of medicinal fungi is studied and developed, this method mainly refers to the use of medicinal plants or residues with active ingredients as a matrix of active ingredients instead of traditional nutrient bases, and the preferred strains are added for microbial transformation, which will form a special fermentation product. In this process, fermentation 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 flavor substances and active ingredients. It is of great significance to increase the utilization of biomass resources and broaden the scope of its application (Bel-Rhlid et al. 2018).
As is well known, Eucommia ulmoides Oliv. is one of the oldest nourishing herbs in traditional Chinese medicine (He et al. 2014). Eucommia ulmoides leaves (EUl) contain many active ingredients, such as flavonoids, iridoids, lignans, phenylpropanoids, and polysaccharides, which have the effects of lowering blood pressure, regulating blood lipids, preventing osteoporosis, lowering blood sugar, calming nerves, and resisting fatigue. The resources are rich and also have high utilization value (He et al. 2014; Hirata et al. 2014; Zhu and Sun 2018). In recent years, the chemical composition, activity, and bioavailability of EUl have continually been the focus of attention, but there have been relatively few studies on the characteristic volatile components of EUl, especially with the use of GC-IMS technology (Hirata et al. 2014). Further, the investigation of volatile components from fermentation product has rarely been reported. It is worth noting that Ganoderma lucidum (GL) strain, Hericium erinaceus (HE) strain, and Griflola frondosa (GF) strain are important edible fungi (Xu et al. 2010; He et al. 2017; Zhao et al. 2017) and have obvious health benefits and medicinal value. Based on the above mentioned, solid-state fermentation of different edible fungi and EUl may produce some interesting results, this phenomenon is worth exploring, and it is also necessary to analyze the characteristic volatile components by GC-IMS technology.
The objective of this study was to first develop a simple and rapid method for the investigation of the characteristic volatile components of EUl, different edible fungi, and their fermentation products using GC-IMS technology. Differences were compared by the fingerprinting of different sample compounds obtained and PCA techniques. Furthermore, some of the marked compounds were identified throughout the spectrum, and the composition and relative content in different samples were analyzed. This would provide a theoretical basis for the development of new fermentation products with special activity.
EXPERIMENTAL
Materials
EUl were obtained from Cili Du-zhong Forestry Centre (Zhangjiajie, China). The fresh leaves were dried at 60 °C, and then the sample was prepared and stored at 4 °C until 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 the reagents used in the experiment were of analytical grade. Ultrapure water (Milli-Q Plus system, Millipore, Bedford, MA, USA) was used throughout the work.
Preparation of Fermentation Samples
The sample of EUl prepared was selected, and then an appropriate amount of water was added until the sample was wetted, and the sample was placed in the cultivation bag after being uniformly stirred. These samples needed to be sterilized at 121 °C. After the sample was cooled to room temperature, under aseptic conditions, GL strain, HE strain, GF strain, or GL-GF complex strain were inoculated into the fermentation medium (EUl), and the moisture content of the substrate was about 65%. The mixed fermentation system was cultured in the dark at 25 ± 3 °C until the mycelium was overgrown with the cultivation bag to stop the fermentation, and the sample was taken out to obtain different fermented fungus substance. These samples were stored in low temperature conditions until analyzed. There were eight kinds of samples in the experiment, which were Ganoderma lucidum microbial strain (GL-M), Hericium erinaceus microbial strain (HE-M), Griflola frondosa microbial strain (GF-M), Eucommia ulmoides leaves (EUl), the Ganoderma lucidum and Eucommia ulmoides leaves fermentation group (GL-EUl-F), the Hericium erinaceus and Eucommia ulmoides leaves fermentation group (HE-EUl-F), the Griflola frondosa and Eucommia ulmoides leaves fermentation group (GF-EUl-F), and the Ganoderma lucidum- Griflola frondosa and Eucommia ulmoides leaves fermentation group (GL-GF-EUl-F).
GC-IMS Instrumentation and Analysis Parameters
The experiments were performed on a GC-IMS prototype manufactured by G.A.S. (Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany) based on an Agilent 6890N gas chromatograph (Agilent Technologies, Palo Alto, CA, USA), coupled to a drift time IMS cell. Analyses for the identification of characteristic volatile compounds of the samples were performed on an IMS commercial instrument (FlavourSpec) from Gesellschaft für Analytische Sensorysteme mbH (G.A.S., Dortmund, Germany) fitted with a non-polar column (FS-SE-54-CB) constituted by 94% methyl-5% phenyl-1% vinylsilicone with a 30 m length × 0.32 mm and 0.5 μm film thickness. The injection rate was 100 μL/s, and the carrier flow rate was 5 mL/s.
For analysis, 1.0 g of different samples that needed to be analyzed (edible fungi, EUl, and its different fermentation products) were placed in a 20-mL vial that was closed with magnetic caps. After 20 min of incubation at 80 °C, 200 μL of sample headspace was automatically injected by means of a heated syringe (80 °C) into the heated injector (80 °C) of the GC-IMS equipment. After injection, the nitrogen gas (99.999%) used as carrier gas, passed through the injector inserting the sample into the gas column, which was heated at 40 °C for timely separation. Then, the analytes were eluted in the isothermal mode and driven into the ionization chamber for ionization, prior to spectrometric detection. Molecules were ionized using a tritium source (6.5 keV), and the resulting ions were driven to the drift region via a shutter grid (Bradbury and Nielson design). The drift tube was 5 cm long and operated at a constant voltage of 400 V/cm, a temperature of 45 °C, and a drift gas flow rate of 250 mL/min (nitrogen). Data were acquired via the spectrometer’s built-in computer. Each sample spectra had an average of 32 scans.
Data Analysis
The study of specific volatile compounds to identify them was realized by the software LAV version 2.0.0 from G.A.S. (Dortmund, Germany). Based on the use of the information included in the whole spectral fingerprint, raw IMS data were converted to .csv format using LAV software. Moreover, GC-IMS Library Search software supplied by G.A.S. (Dortmund, Germany) was employed to identify unknown compounds. Chemometric processing of the IMS data was performed with SIMCA-P 14.0 (Umetrics, Umea, Sweden). The processing technique mainly included principal component analysis (PCA). Data were initially subjected to PCA to reduce their dimensions and apply the classifying procedure to a smaller subspace (Garrido-Delgado et al. 2011), and the min-max normalization method was used to perform PCA.
RESULTS AND DISCUSSION
GC-IMS Topographic Plots from Different Samples
In this study, a simpler and quicker GC-IMS technology was proposed for the discrimination of the composition of EUl according to the volatile components. The five batches of Eucommia ulmoides samples mentioned above (EUl, GL-EUl-F, HE-EUl-F, GF-EUl-F, and GL-GF-EUl-F) were investigated using this method, and the signal intensity of some representative peaks were observed and analyzed. Simultaneously, corresponding different edible fungi (GL-M, HE-M, and GF-M) were also analyzed by GC-IMS under the same conditions (Li et al. 2015). All signal peaks determined in this study were consecutively numbered and in the following either termed by their names or by a number from 1 to 162, which summarized the GC-IMS results. These compounds could be expected to distinguish the differences of the samples (Jünger et al. 2012). Notice that one compound can result in more than one signal or spot (monomer or dimer), depending on the concentration. Spectra at different retention times can be obtained in a topographic plot. For example, the analysis results of the EUl sample is shown in Fig. 1. Different peaks are shown and marked. It was worth nothing that each peak was represented by a spot in the topographic plot (Arroyo-Manzanaresa et al. 2018). There were significant differences in the volatile components of the different samples. Furthermore, this was the first time that some of these target compounds had been studied for EUl samples by Headspace-GC-IMS (HS-GC-IMS).
Fig. 1. Imaging of volatile compounds represented by GC-IMS for EUl
Fig. 2. Comparison of ion migration chromatogram of different samples (edible fungi, and Eucommia ulmoides Oliv. leaves, and its fermentation products)