Resolution-optimized headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) for non-targeted olive oil profiling

GC-IMS-Based Volatile Characteristic Analysis of Hypsizygus marmoreus Dried by Different Methods

Gas chromatography-ion mobility spectroscopy (GC-IMS) was used to analyze the volatile components in dried Hypsizygus marmoreus of different drying methods, including hot air drying (HAD), heat pump drying (HPD), heated freeze-drying (HFD), and unheated freeze-drying (UFD). A total of 116 signal peaks corresponding to 96 volatile compounds were identified, including 25 esters, 24 aldehydes, 23 alcohols, 13 ketones, 10 heterocyclic compounds, 8 carboxylic acids, 7 terpenes, 3 sulfur-containing compounds, 2 nitrogen-containing compounds, and 1 aromatic hydrocarbon. The total content of volatile compounds in H. marmoreus dried by the four methods, from highest to lowest, was as follows: HAD, HPD, HFD, and UFD. The main volatile compounds included carboxylic acids, alcohols, esters, and aldehydes. Comparing the peak intensities of volatile compounds in dried H. marmoreus using different drying methods, it was found that the synthesis of esters, aldehydes, and terpenes increased under hot drying methods such as HAD and HPD, while the synthesis of compounds containing sulfur and nitrogen increased under freeze-drying methods such as HFD and UFD. Nine common key characteristic flavor compounds of dried H. marmoreus were screened using relative odor activity values (ROAV > 1), including ethyl 3-methylbutanoate, acetic acid, 2-methylbutanal, propanal, methyl 2-propenyl sulfate, trimethylamine, 3-octanone, acetaldehide, and thiophene. In the odor description of volatile compounds with ROAV > 0.1, it was found that important flavor components such as trimethylamine, 3-octanone, (E)-2-octenal, and dimethyl disulfide are related to the aroma of seafood. Their ROAV order is HFD > UFD > HPD > HAD, indicating that H. marmoreus using the HFD method have the strongest seafood flavor. The research findings provide theoretical guidance for selecting drying methods and refining the processing of H. marmoreus.

Flavor characteristics of large yellow croaker soup served with different dried edible fungi

The effects of different edible fungi on the flavor profiles of fish soups were analyzed by sensory evaluation, non-volatile and volatile flavor compounds. The sensory attributes of fish soups were modified by adding edible fungi, with the highest total scores obtained for AAFS and DFS. Compared with pure fish soup, the amounts of free amino acids, nucleotides, organic acids and inorganic ions were increased with fungi addition, especially AAFS. The different mushroom fish soups could be clearly distinguished by E-nose analysis, and a total of 52 flavor compounds, mainly composed of aldehydes (27), ketones (11), alcohols (8), esters (4), and others (2), were then identified by GC-IMS. Eventually, fish soup samples were classified into three groups based on OPLS-DA analysis: Ⅰ (LEFS), Ⅱ (BFS and BEFS) and Ⅲ (ABFS, AAFS and DFS). The results showed that Agrocybe aegerita had high suitability for improving the flavor of Large yellow croaker soups.

Authenticity assessment of ground black pepper by combining headspace gas-chromatography ion mobility spectrometry and machine learning

Currently, the authentication of ground black pepper is a major concern, creating a need for a rapid, highly sensitive and specific detection tool to prevent the introduction of adulterated batches into the food chain. To this aim, head space gas-chromatography ion mobility spectrometry (HS-GC-IMS), combined with machine learning, is tested in this initial, proof-of-concept study. A broad variety of authentic samples originating from eight countries and three continents were collected and spiked with a range of adulterants, both endogenous sub-products and an assortment of exogenous materials. The method is characterized by no sample preparation and requires 20 min for chromatographic separation and ion mobility data acquisition. After an explorative analysis of the data, those were submitted to two different machine learning algorithms (partial least squared discriminant analysis-PLS-DA and support vector machine-SVM). While the PLS-DA model did not provide fully satisfactory performances, the combination of HS-GC-IMS and SVM successfully classified the samples as authentic, exogenously-adulterated or endogenously-adulterated with an overall accuracy of 90 % and 96 % on withheld test set 1 and withheld test set 2, respectively (at a 95 % confidence level). Some limitations, expected to be mitigated by further research, were encountered in the correct classification of endogenously adulterated ground black pepper. Correct categorization of the ground black pepper samples was not adversely affected by the operator or the time span of data collection (the method development and model challenge were carried out by two operators over 6 months of the study, using ground black pepper harvested between 2015 and 2019). Therefore, HS-GC-IMS, coupled to an intelligent tool, is proposed to: (i) aid in industrial decision-making before utilization of a new batch of ground black pepper in the production chain; (ii) reduce the use of time-consuming conventional analyses and; (iii) increase the number of ground black pepper samples analyzed within an industrial quality control frame.

Case study on the influence of serving temperature on the aroma release and perception of Huangjiu, a fermented alcoholic beverage

Serving temperature plays a crucial role in influencing the sensory experience of consumers. In this context, this study investigated the influence of serving temperature on the aroma release and perception of a typical fermented alcoholic beverage named Huangjiu. A quantitative sensory description analysis was conducted, determining serving temperature significantly influenced the 17 sensory attributes in both semi-dry and semi-sweet Huangjiu. The variation in the contents of 41 volatiles in the Huangjiu with temperature was investigated using gas chromatography-ion mobility spectrometry, resulting in volatile content significantly increasing above 30 ℃. The partial least squares discriminant analysis was conducted to predict the variable importance for the projection (VIP) of volatiles, and 22 volatiles (VIP > 1) were screened. These 22 volatiles were confirmed as key odorants influenced by serving temperature though aroma addition experiments. The findings would provide a reference for the effects of serving temperature on the flavor perception of fermented alcoholic beverages.

Influence of ionization volume and sample gas flow rate on separation power in gas chromatography-ion mobility spectrometry

In this work, the influence of the sample gas flow rate and the ionization region volume of an ion mobility spectrometer (IMS) used as a detector in gas chromatography (GC) on GC-IMS peak shape has been investigated. Therefore, a drift tube IMS with a field-switching ion shutter, a defined ionization region volume and an ultra-violet radiation source was used. To identify the influence of the sample gas flow rate entering the ionization region (equals the GC carrier gas flow rate if no further make-up gas is used) and the ionization region volume on peak broadening and signal intensity, different sample volumes as they would elute from a GC were tested at a variety of sample gas flow rates at a given ionization region volume. The results clearly show that for low sample gas flow rates a depletion of sample molecules in the ionization region leads to a significant decrease in effective detector volume but also to reduced signal intensities. Therefore, for optimal performance of a GC-IMS, the optimal operating point of the GC should match the flow range, where the IMS provides the best compromise between signal-to-noise ratio and peak broadening.

Volatile Fingerprint and Differences in Volatile Compounds of Different Foxtail Millet (Setaria italica Beauv.) Varieties

Aroma components in foxtail millet are one of the key factors in origin traceability and quality control, and they are associated with consumer acceptance and the corresponding processing suitability. However, the volatile differences based on the foxtail millet varieties have not been studied further. The present study was undertaken to develop the characteristic volatile fingerprint and analyze the differences in volatile compounds of 20 foxtail millet varieties by electronic nose (E-Nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS). A total of 43 volatile compounds were tentatively identified in foxtail millet samples, 34 and 18 by GC-IMS and GC-MS, respectively. Aldehydes, alcohols, and ketones were the major volatile compounds, and the hexanal content was the highest. The characteristic volatile fingerprint of foxtail millet was successfully constructed. A total of 39 common volatile compounds were found in all varieties. The content of hexanal, heptanal, 1-pentanol, acetophenone, 2-heptanone, and nonanal were explored to explain the aroma characteristics among the different varieties, and different varieties can be separated based on these components. The results demonstrate that the combination of E-Nose, GC-IMS, and GC-MS can be a fast and accurate method to identify the general aroma peculiarities of different foxtail millet varieties.

Detection of Triacetone Triperoxide by High Kinetic Energy Ion Mobility Spectrometry

High Kinetic Energy Ion Mobility Spectrometry (HiKE-IMS) is a versatile technique for the detection of gaseous target molecules that is particularly useful in complex chemical environments, while the instrumental effort is low. Operating HiKE-IMS at reduced pressures from 10 to 60 mbar results in fewer ion-neutral collisions than at ambient pressure, reducing chemical cross-sensitivities and eliminating the need for a preceding separation dimension, e.g., by gas chromatography. In addition, HiKE-IMS allows operation over a wide range of reduced electric field strengths E/N up to 120 Td, allowing separation of ions by low-field ion mobility and exploiting the field dependence of ion mobility, potentially allowing separation of ion species at high E/N despite similar low-field ion mobilities. Given these advantages, HiKE-IMS can be a useful tool for trace gas analysis such as triacetone triperoxide (TATP) detection. In this study, we employed HiKE-IMS to detect TATP. We explore the ionization of TATP and the field-dependent ion mobilities, providing a database of the ion mobilities depending on E/N. Confirming the literature results, ionization of TATP by proton transfer with H3O+ in HiKE-IMS generates fragments, but using NH4+ as the primary reactant ion leads to the TATP·NH4+ adduct. This adduct fragments at high E/N, which could provide additional information for reliable detection of TATP. Thus, operating HiKE-IMS at variable E/N in the drift region generates a unique fingerprint of TATP made of all ion species related to TATP and their ion mobilities depending on E/N, potentially reducing the rate of false positives.

Ultra-Fast Ion Mobility Spectrometer for High-Throughput Chromatography

Fast chromatography systems especially developed for high sample throughput applications require sensitive detectors with a high repetition rate. These high throughput techniques, including various chip-based microfluidic designs, often benefit from detectors providing subsequent separation in another dimension, such as mass spectrometry or ion mobility spectrometry (IMS), giving additional information about the analytes or monitoring reaction kinetics. However, subsequent separation is required at a high repetition rate. Here, we therefore present an ultra-fast drift tube IMS operating at ambient pressure. Short drift times while maintaining high resolving power are reached by several key instrumental design features: short length of the drift tube, resistor network of the drift tube, tristate ion shutter, and improved data acquisition electronics. With these design improvements, even slow ions with a reduced mobility of just 0.94 cm2/(V s) have a drift time below 1.6 ms. Such short drift times allow for a significantly increased repetition rate of 600 Hz compared with previously reported values. To further reduce drift times and thus increase the repetition rate, helium can be used as the drift gas, which allows repetition rates of up to 2 kHz. Finally, these significant improvements enable IMS to be used as a detector following ultra-fast separation including chip-based chromatographic systems or droplet microfluidic applications requiring high repetition rates.

Determination of adulteration, geographical origins, and species of food by mass spectrometry

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics-based methods) are still in use; however, emerging approaches like mass spectrometry (MS)-based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS-based metabolomics, proteomics and other approaches.

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Characterization of Key Compounds of Organic Acids and Aroma Volatiles in Fruits of Different Actinidia argute Resources Based on High-Performance Liquid Chromatography (HPLC) and Headspace Gas Chromatography-Ion Mobility Spectrometry (HS-GC-IMS)

Actinidia arguta, known for its distinctive flavor and high nutritional value, has seen an increase in cultivation and variety identification. However, the characterization of its volatile aroma compounds remains limited. This study aimed to understand the flavor quality and key volatile aroma compounds of different A. arguta fruits. We examined 35 A. arguta resource fruits for soluble sugars, titratable acids, and sugar-acid ratios. Their organic acids and volatile aroma compounds were analyzed using high-performance liquid chromatography (HPLC) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS). The study found that among the 35 samples tested, S12 had a higher sugar-acid ratio due to its higher sugar content despite having a high titratable acid content, making its fruit flavor superior to other sources. The A. arguta resource fruits can be classified into two types: those dominated by citric acid and those dominated by quinic acid. The analysis identified a total of 76 volatile aroma substances in 35 A. arguta resource fruits. These included 18 esters, 14 alcohols, 16 ketones, 12 aldehydes, seven terpenes, three pyrazines, two furans, two acids, and two other compounds. Aldehydes had the highest relative content of total volatile compounds. Using the orthogonal partial least squares discriminant method (OPLS-DA) analysis, with the 76 volatile aroma substances as dependent variables and different soft date kiwifruit resources as independent variables, 33 volatile aroma substances with variable importance in projection (VIP) greater than 1 were identified as the main aroma substances of A. arguta resource fruits. The volatile aroma compounds with VIP values greater than 1 were analyzed for odor activity value (OAV). The OAV values of isoamyl acetate, 3-methyl-1-butanol, 1-hexanol, and butanal were significantly higher than those of the other compounds. This suggests that these four volatile compounds contribute more to the overall aroma of A. arguta. This study is significant for understanding the differences between the fruit aromas of different A. arguta resources and for scientifically recognizing the characteristic compounds of the fruit aromas of different A. arguta resources.

Making Every Single Puff Count-Simple and Sensitive E-Cigarette Aerosol Sampling for GCxIMS and GC-MS Analysis

The analysis of the aerosol from tobaccoless electronic cigarettes (e-cigarettes) is an important part of understanding their impact on human health, yet sampling aerosol from e-cigarettes is still considered a challenge. It lacks a standard method for research and quality control and there are a variety of methods. However, few are simple and inexpensive, and none have been suggested for the use with gas chromatography coupled ion mobility spectrometry (GCxIMS). This work presents and evaluates such a setup made from standard lab equipment to quickly collect a quantitative sample from the aerosol of a single puff (5 s totaling 125 mL). The aerosol condensates directly in the cooled headspace (HS) vial, which is analyzed in the HS-GCxIMS or mass spectrometer (HS-GC-MS). The combined use of GC-MS and GCxIMS allows the simple and sensitive identification of unknown substances in complex mixtures and the identification of degradation products in the aerosols. A calibration of 26 flavor compounds (0.2-20 µg/g) was created using single puffs of a spiked, flavorless commercial refill solution and 2-alkanones as internal standards. This sensitive but easily reproducible setup enables a wide range of further investigations, even for labs that were previously unable to afford it.

A geographical origin assessment of Italian hazelnuts: Gas chromatography-ion mobility spectrometry coupled with multivariate statistical analysis and data fusion approach

Hazelnut is a commodity that has gained interest in the food science community concerning its authenticity. The quality of the Italian hazelnuts is guaranteed by Protected Designation of Origin and Protected Geographical Indication certificates. However, due to their modest availability and the high price, fraudulent producers/suppliers blend, or even substitute, Italian hazelnuts with others from different countries, having a lower price, and often a lower quality. To contrast or prevent these illegal activities, the present work investigated the application of the Gas Chromatography-Ion mobility spectrometry (GC-IMS) technique on the hazelnut chain (fresh, roasted, and paste of hazelnuts). The raw data obtained were handled and elaborated using two different ways, software for statistical analysis, and a programming language. In both cases, Principal Component Analysis and Partial Least Squares-Discriminant Analysis models were exploited, to study how the Volatile Organic Profiles of Italian, Turkish, Georgian, and Azerbaijani products differ. A prediction set was extrapolated from the training set, for a preliminary models' evaluation, then an external validation set, containing blended samples, was analysed. Both approaches highlighted an interesting class separation and good model parameters (accuracy, precision, sensitivity, specificity, F1-score). Moreover, a data fusion approach with a complementary methodology, sensory analysis, was achieved, to estimate the performance enhancement of the statistical models, considering more discriminant variables and integrating at the same time further information correlated to quality aspects. GC-IMS could be a key player as a rapid, direct, cost-effective strategy to face authenticity issues regarding the hazelnut chain.

Cinnamon essential oil vapor alleviates the reduction of aroma-related volatiles in cold-stored "Feicheng" peach using HS-GC-IMS

"Feicheng" peach is popular for its unique aroma, but its defect of being highly sensitive to chilling injury (CI) often leads to aroma loss and internal browning. Essential oils (EOs) are often used to enhance the antioxidant capacity of plants and fruits, as well as to trigger their defense against biotic/abiotic stresses. This study aimed to examine the effect of cinnamon essential oil (CEO) vapor treatment on the aroma quality of peach fruit during cold storage using HS-GC-IMS. The results showed that 50 μL/L CEO vapor reduced the severity of internal browning (IB) in peaches at the stage of 7 ~ 21 d during refrigeration (Significantly, the L* value was higher and the IB index was lower than that of control, p < 0.05). Meanwhile, the evident reduction or loss of aroma content caused by CI was restored to a higher level than the control (p < 0.05). Furthermore, CEO treatment promoted the release of aroma-related volatiles as evidenced by more propyl acetate, and the dimer of amyl acetate, isoamyl acetate, butyl acetate detected than that on harvest day and no-treated group after 21 d of cold storage plus 2 d of shelf life. Genes of PpLOX1, PpLOX2, PpHPL1 and PpADH1 associated with aroma-related volatile biosynthesis revealed higher transcript abundance in peach fruits treated with CEO than the control (p < 0.05). Overall, our study demonstrated that CEO in vapor phase may be beneficial to alleviate the quality deterioration in aroma and flesh color of "Feicheng" peaches caused by CI, which lays a theoretical reference for maintaining postharvest quality of peach fruits.

Novel Method Based on Ion Mobility Spectrometry Combined with Machine Learning for the Discrimination of Fruit Juices

Fruit juices are one of the most widely consumed beverages worldwide, and their production is subject to strict regulations. Therefore, this study presents a methodology based on the use of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) in combination with machine-learning algorithms for the characterization juices of different raw material (orange, pineapple, or apple and grape). For this purpose, the ion mobility sum spectrum (IMSS) was used. First, an optimization of the most important conditions in generating the HS was carried out using a Box-Behnken design coupled with a response surface methodology. The following factors were studied: temperature, time, and sample volume. The optimum values were 46.3 °C, 5 min, and 750 µL, respectively. Once the conditions were optimized, 76 samples of the different types of juices were analyzed and the IMSS was combined with different machine-learning algorithms for its characterization. The exploratory analysis by hierarchical cluster analysis (HCA) and principal component analysis (PCA) revealed a clear tendency to group the samples according to the type of fruit juice and, to a lesser extent, the commercial brand. The combination of IMSS with supervised classification techniques reported an excellent result with 100% accuracy on the test set for support vector machines (SVM) and random forest (RF) models regarding the specific fruit used. Nevertheless, all the models have proven to be an effective alternative for characterizing and classifying the different types of juices.

Effects of Different Probiotics on the Volatile Components of Fermented Coffee Were Analyzed Based on Headspace-Gas Chromatography-Ion Mobility Spectrometry

Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was used to study the effects of four kinds of probiotics on the volatile components of fermented coffee. The fingerprints showed that 51 compounds were confirmed and quantified, including 13 esters, 11 aldehydes, 9 alcohols, 6 ketones, 3 furans, 5 terpenes (hydrocarbons), 2 organic acids, 1 pyrazine, and 1 sulfur-containing compound. After fermenting, the aroma of the green beans increases while that of the roasted beans decreases. After roasting, the total amount of aroma components in coffee beans increased by 4.48-5.49 times. The aroma differences between fermented and untreated roasted beans were more significant than those between fermented and untreated green beans. HS-GC-IMS can distinguish the difference in coffee aroma, and each probiotic has a unique influence on the coffee aroma. Using probiotics to ferment coffee can significantly improve the aroma of coffee and provide certain application prospects for improving the quality of commercial coffee beans.

Comparative Study on the Volatile Organic Compounds and Characteristic Flavor Fingerprints of Five Varieties of Walnut Oil in Northwest China Using Using Headspace Gas Chromatography-Ion Mobility Spectrometry

Odor is an important characteristic of walnut oil; walnut oil aromas from different varieties smell differently. In order to compare the differences of volatile flavor characteristics in different varieties of walnut oil, the volatile organic compounds (VOCs) of walnut oil from five different walnut varieties in Northwest China were detected and analyzed using headspace gas chromatography–ion mobility spectrometry (HS–GC–IMS). The results showed that 41 VOCs in total were identified in walnut oil from five different varieties, including 14 aldehydes, 8 alcohols, 4 ketones, and 2 esters. Walnut oil (WO) extracted from the “Zha343” variety was most abundant in VOCs. The relative odor activity value (ROAV) analysis showed that aldehydes were the main aroma substances of walnut oil; specifically, hexanal, pentanal, and heptanal were the most abundant. Fingerprints and heat map analysis indicated that WO extracted from the “Xin2”, “185”, “Xin’guang”, and “Zha343” varieties, but not from the “Xinfeng” variety, had characteristic markers. The relative content differences of eight key VOCs in WO from five varieties can be directly compared by Kruskal–Wallis tests, among which the distribution four substances, hexanal (M), hexanal (D), pentanal (M), (E)-2-hexanal (M), presented extremely significant differences (P<0.01). According to the results of the principal component analysis (PCA), WO extracted from the “Zha343” variety was distinct from the other four varieties; in addition, WO extracted from the “Xin2” variety exhibited similarity to WO extracted from the “185” variety, and WO extracted from the “Xinfeng” variety showed similarity to WO extracted from the “Xin’guang” variety. These results reveal that there are certain differences in the VOCs extracted from five different WO varieties, making it feasible to distinguish different varieties of walnut oil or to rapidly detect walnut oil quality based on its volatile substances profile.

Qualitative determination of volatile substances in different flavored cigarette paper by using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with chemometrics

In order to investigate the difference of volatile substances among flavored cigarette paper, which are supplied by several manufacturers with different batches, the stability of the complex system of scented cigarette paper was analyzed and evaluated. In this study, Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was used to detect the aroma compounds of 23 flavored cigarette paper samples. Based on fingerprint analysis, the differences and changes of aroma compounds of different samples were studied in the form of data visualization. Principal component analysis, partial least squares regression analysis, cluster heatmap analysis and artificial neural network analysis were used to evaluate the stability of different cigarette paper. The results show that: A total of 29 volatile substances were identified from different scented cigarette paper. Fingerprint analysis revealed that the volatile substances of different cigarette paper samples were roughly the same, but not the content. The results of chemometrics analysis showed that there were significant differences in the characteristic aroma compounds of cigarette paper from different manufacturers. HS-GC-IMS technology combined with chemometrics method could be applied to determine the difference of volatile substances among different flavored cigarette paper, which theoretically and technically supported the quality stability maintenance and identification of flavored cigarette paper processed in different places.

HS-GC-IMS and PCA to Characterize the Volatile Flavor Compounds in Three Sweet Cherry Cultivars and Their Wines in China

The aim of this research was to characterize differences and sources of volatile flavor compounds by using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and principal component analysis (PCA). Three sweet cherry fruits from different cultivars (cv. Tie, Van, and Lap) and their wines that were produced by the same yeast were detected. The results showed that 27 flavor compounds were identified in cherry fruits, including 10 alcohols, 7 esters, 7 aldehydes, 2 ketones, and 1 organic acid. Twenty-three flavor compounds were identified in cherry wines, including nine esters, eight alcohols, three aldehydes, two organic acids, and one ketone. In cherry fruits, aldehydes, several alcohols, and one ketone were the most prevalent in cv. Tie, and the majority of esters and alcohols in cv. Van. After fermentation, ethanol, butanol, butanal, ethyl propionate, propionaldehyde, 3-hydroxy-2-butanone, and acetic acid increased, whereas 1-hexanol, 3-methyl-3-buten-1-ol, 1-penten-3-ol, ethyl acetate, methyl acetate, (E)-2-hexenal and hexanal decreased. Few differences were detected in the type and content of volatile compounds in cherry wines from cv. Tieton (WT) and cv. Van (WV). Almost all aldehydes are derived from cherry fruits, which cannot be produced during wine-making, and other volatile compounds are almost all produced by saccharomyces cerevisiae. The volatile compounds of cherry wines were determined by row materials and fermentation cultures. Flavor fingerprints were established by HS-GC-IMS and PCA, which provided a theoretical foundation for the evaluation and improvement of flavor quality in cherry wine-making.

Effects of Drying Methods on Taste Components and Flavor Characterization of Cordyceps militaris

The influences of four drying methods (hot air drying (HAD), vacuum freeze drying (VFD), vacuum drying (VD) and intermittent microwave combined with hot air drying (MW-HAD)) on the taste profile and flavor characteristic of Cordyceps militaris were investigated. MW-HAD samples had the highest levels of umami taste 5'-nucleotides, bitter taste amino acids, and equivalent umami concentration (EUC) value. The aroma fingerprints and differences of dried Cordyceps militaris were established by GC-MS with odor activity values (OAVs) and GC-IMS with principal component analysis (PCA). GC-MS data showed that the predominant volatiles of dried samples were aldehydes, alcohols, and ketones. VFD samples had the highest amount of total aroma compounds and C8 compounds. Moreover, 21 aroma-active components (OAVs ≥ 1) were the main contributors to the flavor of dried Cordyceps militaris. The OAVs of 1-octen-3-one and 3-octanone associated with mushroom-like odor in VFD were significantly higher than other samples. Furthermore, a significant difference in flavor compounds of four dried samples was also clearly demonstrated by GC-IMS analysis with PCA. GC-IMS analysis revealed that VFD samples had the most abundant flavor compounds. Overall, MW-HAD was an effective drying method to promote umami taste, and VFD could superiorly preserve volatiles and characteristic aroma compounds in dried Cordyceps militaris.

Quantitation of Flavor Compounds in Refill Solutions for Electronic Cigarettes Using HS-GCxIMS and Internal Standards

New regulations on the use of flavor compounds in tobaccoless electronic cigarettes require comprehensive analyses. Gas chromatography coupled ion mobility spectrometry is on the rise as an analytical technique for analyzing volatile organic compounds as it combines sensitivity, selectivity, and easy usage with a full-range screening. A current challenge is the quantitative GCxIMS-analysis. Non-linear calibration methods are predominantly used. This work presents a new calibration method using linearization and its corresponding fit based on the relation between the reactant and analyte ions from the chemical ionization. The analysis of e-liquids is used to compare the presented calibration with an established method based on a non-linear Boltzmann fit. Since e-liquids contain matrix compounds that have been shown to influence the analyte signals, the use of internal standards is introduced to reduce these effects in GCxIMS-analysis directly. Different matrix mixtures were evaluated in the matrix-matched calibration to improve the quantitation further. The system's detection and quantitation limits were determined using a separate linear calibration. A matrix-matched calibration series of 29 volatile compounds with 12 levels were used to determine the concentration of these substances in a spiked, flavorless e-liquid and a banana-flavored e-liquid, validating the quality of the different calibrations.

Evaluation of the Influence of Flavor Characteristics of Cooked Bacon with Different Sterilization Methods by GC-IMS Combined with HS-SPME-GC-MS and Electronic Nose

This study investigated the impact of high pressure and temperature (HTHP) and electron-beam irradiations (3, 5, 7, and 9 kGy) using differences in two sterilization methods on the volatile compounds and sensory characteristics of cooked bacon. It showed that 7 and 9 kGy of irradiation caused a significant reduction in species of volatile compounds and sensory features, but the concentration of total ketones, alcohols, aldehydes, acids and aromatic hydrocarbons significantly increased at 9 kGy. Samples treated with a dose of less than 5 kGy did not change volatile compounds and sensory properties. High-temperature-high-pressure conditions could greatly impact the concentrations of volatile compound species and sensory traits. The electronic nose effectively detected the flavor difference in different sterilization methods. Fingerprinting showed that HTHP and 9-kGy-treated groups were significantly different from other treatments. This study inferred that 5 kGy might be optimal for maintaining the original flavor and sensory properties of cooked bacon.

Sampling Volatile Organic Compound Emissions from Consumer Products: A Review

Volatile organic compounds (VOCs) are common constituents of many consumer products. Although many VOCs are generally considered harmless at low concentrations, some compound classes represent substances of concern in relation to human (inhalation) exposure and can elicit adverse health effects, especially when concentrations build up, such as in indoor settings. Determining VOC emissions from consumer products, such as toys, utensils or decorative articles, is of utmost importance to enable the assessment of inhalation exposure under real-world scenarios with respect to consumer safety. Due to the diverse sizes and shapes of such products, as well as their differing uses, a one-size-fits-all approach for measuring VOC emissions is not possible, thus, sampling procedures must be chosen carefully to best suit the sample under investigation. This review outlines the different sampling approaches for characterizing VOC emissions from consumer products, including headspace and emission test chamber methods. The advantages and disadvantages of each sampling technique are discussed in relation to their time and cost efficiency, as well as their suitability to realistically assess VOC inhalation exposures.

Nondestructive classification of soft rot disease in napa cabbage using hyperspectral imaging analysis

Identification of soft rot disease in napa cabbage, an essential ingredient of kimchi, is challenging at the industrial scale. Therefore, nondestructive imaging techniques are necessary. Here, we investigated the potential of hyperspectral imaging (HSI) processing in the near-infrared region (900–1700 nm) for classifying napa cabbage quality using nondestructive measurements. We determined the microbiological and physicochemical qualitative properties of napa cabbage for intercomparison of HSI information, extracted HSI characteristics from hyperspectral images to predict and classify freshness, and established a novel approach for classifying healthy and rotten napa cabbage. The second derivative Savitzky–Golay method for data preprocessing was implemented, followed by wavelength selection using variable importance in projection scores. For multivariate data of the classification models, partial least square discriminant analysis (PLS-DA), support vector machine (SVM), and random forests were used for predicting cabbage conditions. The SVM model accurately distinguished the cabbage exhibiting soft rot disease symptoms from the healthy cabbage. This study presents the potential of HSI systems for separating soft rot disease-infected napa cabbages from healthy napa cabbages using the SVM model, especially under the most effective wavelengths (970, 980, 1180, 1070, 1120, and 978 nm), prior to processing. These results are applicable to industrial multispectral images.

Changes of volatile substance composition during processing of nine-processed tangerine peel (Jiuzhi Chenpi) determined by gas chromatography-ion mobility spectrometry

Nine-processed tangerine peel (Jiuzhi Chenpi in Chinese) is a famous Chinese traditional snack. The composition and contents of volatile substances during its processing is unclear. Gas chromatography combined with ion mobility spectrometry (GC-IMS) was applied to determine the characteristic changes of volatile components throughout the production process. Four stages such as untreated dry tangerine peel (raw material), debittered tangerine peel, pickled tangerine peel, and final product were examined. A total of 110 flavor compounds including terpenes, alcohols, aldehydes, ketones, esters, acids, and two others were successfully detected in tangerine peel samples across the various production stages. There were abundant amounts of terpenes contributing to the flavor, including limonene, gamma-terpinene, alpha-pinene, myrcene, beta-pinene, and alpha-thujene which were reduced at the later stage of production. Large amounts of esters and alcohols such as methyl acetate, furfuryl acetate, ethyl acetate, benzyl propionate, 2-hexanol, linalool, and isopulegol, were diminished at the early stage of processing, i.e., soaking for debittering. One the other hand, the final product contained increased amount of aldehydes and ketones including pentanal, hexanal, 2-hexenal, 2-heptenal (E), 2-pentenal (E), 1-penten-3-one, 6-methyl-5-hepten-2-one, 2-methyl-2-propenal, and 2-cyclohexen-1-one, and very high level of acetic acid. Present findings help to understand the formation of the unique flavor of nine-processed tangerine peel and provide a scientific basis for the optimization of processing methods and quality control.

gc-ims-tools - A new Python package for chemometric analysis of GC-IMS data

Due to its high sensitivity and resolving power, gas chromatography ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for non-target screening of complex sample materials. Given the wide range of applications, such as food authenticity, custom data analysis workflows are needed. As a common basis, they necessarily share many functionalities such as file input/output, preprocessing methods, exploratory or supervised analysis and visualizations. This study introduces a new open source, fully customizable Python package for handling and analysis of GC-IMS data. A workflow to classify olive oils by geographical origin exemplarily demonstrates functionality and ease of use. Key preprocessing steps, exploratory - and supervised data analysis and feature selections are visualized. All code and detailed documentation are freely available as open source under the BSD 3-clause license at https://github.com/Charisma-Mannheim/gc-ims-tools.

Overview of advanced technologies for volatile organic compounds measurement in food quality and safety

Food quality and nutrition have received much attention in recent decades, thanks to changes in consumer behavior and gradual increases in food consumption. The demand for high-quality food necessitates stringent quality assurance and process control measures. As a result, appropriate analytical tools are required to assess the quality of food and food products. VOCs analysis techniques may meet these needs because they are nondestructive, convenient to use, require little or no sample preparation, and are environmentally friendly. In this article, the main VOCs released from various foods during transportation, storage, and processing were reviewed. The principles of the most common VOCs analysis techniques, such as electronic nose, colorimetric sensor array, migration spectrum, infrared and laser spectroscopy, were discussed, as well as the most recent research in the field of food quality and safety evaluation. In particular, we described data processing algorithms and data analysis captured by these techniques in detail. Finally, the challenges and opportunities of these VOCs analysis techniques in food quality analysis were discussed, as well as future development trends and prospects of this field.

Insights into the Aroma Profile of Sauce-Flavor Baijiu by GC-IMS Combined with Multivariate Statistical Analysis

Aroma is among the principal quality indicators for evaluating Baijiu. The aroma profiles of sauce-flavor Baijiu produced by 10 different manufacturers were determined by GC-IMS. The results showed that GC-IMS could effectively separate the volatile compounds in Baijiu, and a total of 80 consensus volatile compounds were rapidly detected from all samples, among which 29 volatile compounds were identified, including 5 alcohols, 14 esters, 2 acids, 2 ketones, 5 aldehydes, and 1 furan. According to the differences in aroma profile found by multivariate statistical analysis, these sauce-flavor Baijiu produced by 10 different manufacturers can be further divided into three types. The relative odor activity value of the identified volatile compounds indicated that seven volatile compounds contributed most to the aroma of sauce-flavor Baijiu in order of aroma contribution rate, and they were ethyl hexanoate, ethyl pentanoate, ethyl 2-methylbutanoate, ethyl octanoate (also known as octanoic acid ethyl ester), ethyl 3-methylbutanoate, ethyl butanoate, and ethyl isobutyrate. Correspondingly, the main aromas of these sauce-flavor Baijiu produced by 10 different manufacturers were sweet, fruity, alcoholic, etheral, cognac, rummy, and winey. On the one hand, this study proved that GC-IMS is well adapted to the detection of characteristic volatile aroma compounds and trace compounds in Baijiu, which is of positive significance for improving the aroma fingerprint and database of sauce-flavor Baijiu. On the other hand, it also enriched our knowledge of Baijiu and provided references for the evaluation and regulation of the flavor quality of sauce-flavor Baijiu.

Volatilomics-Based Microbiome Evaluation of Fermented Dairy by Prototypic Headspace-Gas Chromatography–High-Temperature Ion Mobility Spectrometry (HS-GC-HTIMS) and Non-Negative Matrix Factorization (NNMF)

Fermented foods, such as yogurt and kefir, contain a versatile spectrum of volatile organic compounds (VOCs), including ethanol, acetic acid, ethyl acetate, and diacetyl. To overcome the challenge of overlapping peaks regarding these key compounds, the drift tube temperature was raised in a prototypic high-temperature ion mobility spectrometer (HTIMS). This HS-GC-HTIMS was used for the volatilomic profiling of 33 traditional kefir, 13 commercial kefir, and 15 commercial yogurt samples. Pattern recognition techniques, including principal component analysis (PCA) and NNMF, in combination with non-targeted screening, revealed distinct differences between traditional and commercial kefir while showing strong similarities between commercial kefir and yogurt. Classification of fermented dairy samples into commercial yogurt, commercial kefir, traditional mild kefir, and traditional tangy kefir was also possible for both PCA- and NNMF-based models, obtaining cross-validation (CV) error rates of 0% for PCA-LDA, PCA-kNN (k = 5), and NNMF-kNN (k = 5) and 3.3% for PCA-SVM and NNMF-LDA. Through back projection of NNMF loadings, characteristic substances were identified, indicating a mild flavor composition of commercial samples, with high concentrations of buttery-flavored diacetyl. In contrast, traditional kefir showed a diverse VOC profile with high amounts of flavorful alcohols (including ethanol and methyl-1-butanol), esters (including ethyl acetate and 3-methylbutyl acetate), and aldehydes. For validation of the results and deeper understanding, qPCR sequencing was used to evaluate the microbial consortia, confirming the microbial associations between commercial kefir and commercial yogurt and reinforcing the differences between traditional and commercial kefir. The diverse flavor profile of traditional kefir primarily results from the yeast consortium, while commercial kefir and yogurt is primarily, but not exclusively, produced through bacterial fermentation. The flavor profile of fermented dairy products may be used to directly evaluate the microbial consortium using HS-GC-HTIMS analysis.

Analysis of drugs including illicit and new psychoactive substances in oral fluids by gas chromatography-drift tube ion mobility spectrometry

In this study, a gas chromatograph (GC) has been coupled to a drift tube ion mobility spectrometer (IMS) in order to develop an analytical procedure for the determination of psychoactive substances in oral fluids. Working parameters, including the GC-IMS interface ones, were adjusted in order to obtain sensitive and robust signals. A volume of 500 μL of oral fluid was extracted with 250 μL chloroform and, after centrifugation, were injected into the GC-IMS system. Amphetamine, methylone, α-PVP, ketamine, lidocaine, MPHP, cocaine, THJ-2201, and 5F-ADB were employed as model compounds, providing limits of detection from 6 to 15 μg L^-1 and recoveries from 70 to 115% for field oral fluids spiked with target analytes at 250, 500, and 600 μg L^-1. Moreover, two oral fluid certified reference materials were analysed by the proposed GC-IMS based methodology with obtained relative percentage errors lower than 8.4%, being the proposed GC-IMS procedure a reliable, selective, and sensitive technique for the determination of psychoactive substances in oral fluids.

Application of gas chromatography-ion mobility spectrometry in the analysis of food volatile components

Gas chromatography-ion mobility spectrometry (GC-IMS) is an emerging analytical technique that has the advantages of fast response, high sensitivity, simple operation, and low cost. The combination of the fast speed and resolution of GC with the high sensitivity of IMS makes GC-IMS play an important role in the detection of food volatile substances. This paper focuses on the basic principles and future development trend, and the comparative analysis of the functions, similarities and differences of GC-IMS, GC-MS and electronic nose in the detection of common volatile compounds. A comprehensive introduction to the main application of GC-IMS in food volatile components: fingerprint identification of sample differences and detection of characteristic compounds. On the basis of perfecting the spectral library, GC-IMS will have broad development prospects in food authentication, origin identification, process optimization and product classification, especially in the analysis and identification of trace volatile food flavor substances.

Validation Study on the Simultaneous Quantitation of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry

A new quantitative method based on static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) is proposed, which enables the simultaneous quantitation 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 quantitation studies, namely, nonlinearity 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 quantitation, repeatability, reproducibility, and recovery, were investigated. Both nonlinear 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 quantitation, that is, effects of ethanol content and competitive ionization, were also discussed. The performance of the SHS-GC-IMS method was subsequently compared against that of a currently established method, namely, GC-MS, using commercial wine samples. These findings provide an initial validation of a GC-IMS-based quantitation method, as well as a starting point for further enhancing the analytical scope of GC-IMS.

Characteristic Volatile Fingerprints of Four Chrysanthemum Teas Determined by HS-GC-IMS

Volatile composition is an important feature that determines flavor, which actively affects the overall evaluation of chrysanthemum tea. In this study, HS-GC-IMS (headspace-gas chromatography-ion mobility spectrometry) was performed to characterize the volatile profiles of different chrysanthemum tea subtypes. Forty-seven volatiles of diverse chemical nature were identified and quantified. Partial least squares discriminant analysis (PLS-DA) revealed that four chrysanthemum teas were distinct from each other based on their volatile compounds. Furthermore, this work provides reference methods for detecting novel volatile organic compounds in chrysanthemum tea plants and products.

Coupling Droplet Microfluidics with Ion Mobility Spectrometry for Monitoring Chemical Conversions at Nanoliter Scale

We introduce the coupling of droplet microfluidics and ion mobility spectrometry (IMS) to address the challenges of label-free and chemical-specific detection of compounds in individual droplets. In analogy to the established use of mass spectrometry, droplet-IMS coupling can be also achieved via electrospray ionization but with significantly less instrumental effort. Because IMS instruments do not require high-vacuum systems, they are very compact, cost-effective, and robust, making them an ideal candidate as a chemical-specific end-of-line detector for segmented flow experiments. Herein, we demonstrate the successful coupling of droplet microfluidics with a custom-built high-resolution drift tube IMS system for monitoring chemical reactions in nL-sized droplets in an oil phase. The analytes contained in each droplet were assigned according to their characteristic ion mobility with limit of detections down to 200 nM to 1 μM and droplet frequencies ranging from 0.1 to 0.5 Hz. Using a custom sheath flow electrospray interface, we have further achieved the chemical-specific monitoring of a biochemical transformation catalyzed by a few hundred yeast cells, at single droplet level.

Electrospray ionization ion mobility spectrometer with new tristate ion gating for improved sensitivity for compounds with lower ion mobility

An electrospray is a dispersed nebula of charged droplets produced under the influence of a strong electric field. The charged droplets subsequently result in ions in the gas phase. Therefore, electrospray is a commonly used method for transferring liquids to the gas phase while ionizing its constituents at the same time. In this work, we investigate the performance of an electrospray ionization ion mobility spectrometer by varying the electric field strength in the desolvation region. In particular, we investigate a new tristate ion shutter with increased sensitivity for ions with higher molecular mass and lower ion mobility that are usually suppressed by classical Bradbury-Nielsen or Tyndall-Powell ion shutters when using short gating times as required for high resolving power. The electric field in the tristate ion shutter affects the optimal ratio of the electric field strengths in the drift and desolvation region. Furthermore, the solvent flow rate needs to be considered when setting the field strengths in the desolvation region. However, a higher electric field strength in the desolvation region affects the field at the emitter tip. For this reason, a smaller ratio of the drift field strength and the desolvation field strength is beneficial, especially since higher solvent flow rates require higher fields to initiate an electrospray. In this work, we use tetraoctylammonium bromide as an instrument standard and the fungicide metalaxyl, the herbicide isoproturon and the antibiotic cefuroxime as model compounds.

Full Workflows for the Analysis of Gas Chromatography-Ion Mobility Spectrometry in Foodomics: Application to the Analysis of Iberian Ham Aroma

Gas chromatography—ion mobility spectrometry (GC-IMS) allows the fast, reliable, and inexpensive chemical composition analysis of volatile mixtures. This sensing technology has been successfully employed in food science to determine food origin, freshness and preventing alimentary fraud. However, GC-IMS data is highly dimensional, complex, and suffers from strong non-linearities, baseline problems, misalignments, peak overlaps, long peak tails, etc., all of which must be corrected to properly extract the relevant features from samples. In this work, a pipeline for signal pre-processing, followed by four different approaches for feature extraction in GC-IMS data, is presented. More precisely, these approaches consist of extracting data features from: (1) the total area of the reactant ion peak chromatogram (RIC); (2) the full RIC response; (3) the unfolded sample matrix; and (4) the ion peak volumes. The resulting pipelines for data processing were applied to a dataset consisting of two different quality class Iberian ham samples, based on their feeding regime. The ability to infer chemical information from samples was tested by comparing the classification results obtained from partial least-squares discriminant analysis (PLS-DA) and the samples’ variable importance for projection (VIP) scores. The choice of a feature extraction strategy is a trade-off between the amount of chemical information that is preserved, and the computational effort required to generate the data models.

Non-Targeted Screening Approaches for Profiling of Volatile Organic Compounds Based on Gas Chromatography-Ion Mobility Spectroscopy (GC-IMS) and Machine Learning

Due to its high sensitivity and resolving power, gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful technique for the separation and sensitive detection of volatile organic compounds. It is a robust and easy-to-handle technique, which has recently gained attention for non-targeted screening (NTS) approaches. In this article, the general working principles of GC-IMS are presented. Next, the workflow for NTS using GC-IMS is described, including data acquisition, data processing and model building, model interpretation and complementary data analysis. A detailed overview of recent studies for NTS using GC-IMS is included, including several examples which have demonstrated GC-IMS to be an effective technique for various classification and quantification tasks. Lastly, a comparison of targeted and non-targeted strategies using GC-IMS are provided, highlighting the potential of GC-IMS in combination with NTS.

Analysis of flavor formation during production of Dezhou braised chicken using headspace-gas chromatography-ion mobility spec-trometry (HS-GC-IMS)

In order to help the poultry industry to generate higher quality products, the headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technique was used to identify volatile substances formed during the processing of Dezhou braised chicken (DBC). A total of 37 volatile substances including aldehydes, alcohols, ketones, esters, terpenoids, furans and pyrazines were identified during DBC processing across seven sampling stages. The analyses identified 2-ethylhexanol as a key flavor chemical within the chicken carcasses, and found that ethyl acetate, 1-hexanol, 4-methyl-2-pentanone and 1-pentanol were mainly produced during the deep-frying stage of processing. Stewing with herbs and spices was found to be an important stage in the flavor impartation process. 2-Butanone, n-nonanal, heptanal and ethanol were positively related to processing stage 3, whereas processing stage 4 was characterized by ethyl propanoate, benzaldehyde, butyl acetate, 2-pentyl furan and 2-heptanone. The processing stages 5, 6 and 7 were not significantly different (P > 0.05) from each other.

Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics

Deep learning is a trending field in bioinformatics; so far, mostly known for image processing and speech recognition, but it also shows promising possibilities for data processing in food analysis, especially, foodomics. Thus, more and more deep learning approaches are used. This review presents an introduction into deep learning in the context of metabolomics and proteomics, focusing on the prediction of shelf-life, food authenticity, and food quality. Apart from the direct food-related applications, this review summarizes deep learning for peptide sequencing and its context to food analysis. The review’s focus further lays on MS (mass spectrometry)-based approaches. As a result of the constant development and improvement of analytical devices, as well as more complex holistic research questions, especially with the diverse and complex matrix food, there is a need for more effective methods for data processing. Deep learning might offer meeting this need and gives prospect to deal with the vast amount and complexity of data.

Strategy for the identification of flavor compounds in e-liquids by correlating the analysis of GCxIMS and GC-MS

This work presents a strategy to correlate the results from gas chromatography coupled ion mobility spectrometry (GCxIMS) and mass spectrometry (GC-MS) to enable a simpler and cheaper analysis of flavor compounds in e-liquids. The use of the retention index for GCxIMS measurements was validated for its application to correlate results with GC-MS data. The easy detection of the GCxIMS for substances at concentrations as low as 1 μg/L can therefore be combined with the identification power of the MS. The use of the MS' mass signals and wide-spread availability of mass spectra libraries reduces the effort necessary to choose the correct reference standards for the identification of unknown substances. Between both detectors, correlating of the retention time indices was achieved for ± 1%. 2-Alkanones were used as an alternative reference point for the IMS and the well-established alkanes for the MS. The application on flavor compounds in e-liquids shows equal or better results than those presented for more complex, hardware-based correlations like line splitting. Additionally, the inverted reduced mobility combined with the retention index of a non-polar column enables simple extrapolation for the confirmation of expected substances as well as the use in a transferable database. For the first time, this comprehensive application allows an extensive, simplified, and cheap identification of flavor compounds in e-liquids by GCxIMS and GC-MS.

Analysis of volatile flavor compounds of green wheat under different treatments by GC-MS and GC-IMS

Volatile components in green wheat under different treatments including raw, washing, blanching, precooling, freezing, steaming, boiling, frying, and freeze-drying were evaluated by gas chromatography-ion mobility spectroscopy (GC-IMS) and gas chromatography-mass spectrometry (GC-MS). Five key aroma substances including n-hexanal, benzaldehyde, nonanal, 2-pentylfuran, and (E)-oct-2-enal were found by Venn diagram and odor activity values (OAV). Furthermore, according to volatile fingerprints characteristics and the aroma profile of sensory evaluation, it was found that green wheat under different treatments mainly presented seven characteristic flavor notes including sweet flowers, fat fragrance, mushroom hay, waxy aldehyde, citrus fruity, vegetable-like bean, and bitter almond from the sensory evaluation, and they could be divided into four categories, which was consistent with the results of PCA and GC-IMS. Hence, the volatile compounds of green wheat samples could be visualized and identified quickly via GC-IMS and the samples could be clearly classified based on the difference of volatile compounds. PRACTICAL APPLICATIONS: In the study, fingerprints coupled with cluster analysis were a visualized method for the identification of volatile compounds. Meanwhile, a new method, Venn diagram with OAV, was used to identify the key aroma of products. Finally, a rapid method to classify products by GC-IMS was performed. In future practical applications, GC-IMS can be used to classify products from different origins and different manufacturers. Similarly, it can identify fake and inferior products and whether the products have deteriorated. In addition, this research will provide a new strategy to find the relationship between flavor compounds and various processed technologies toward different cereals.