Application and development trends of gas chromatography–ion mobility spectrometry for traditional Chinese medicine, clinical, food and environmental analysis

Early identification and monitoring of soft rot contamination in postharvest kiwifruit based on volatile fingerprints using headspace-gas chromatography-ion mobility spectrometry

Soft rot is one of the most devastating fungal diseases occurring in kiwifruit during postharvest storage. Whereas, the approaches for rapid, precise and non-destructive testing of early soft rot contamination are still scarce. This study successfully employed headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to evaluate volatile organic compounds (VOCs) of soft rot kiwifruit contaminated with three pathogenic fungi including B. dothidea, Diaporthe spp., A. alternata. A total of 88, 106, 110 and 99 VOCs were detected in non-infected, B. dothidea, Diaporthe spp., A. alternata-infected kiwifruit, respectively. Specific fingerprints were established with 15, 26 and 11 characteristic VOCs emitted by three pathogenic fungi invading kiwifruit and not present in non-infected kiwifruit, accomplishing effective discrimination between healthy and disease kiwifruit. Additionally, alternative potential volatile biomarkers for soft rot kiwifruit were screened, such as α-terpinene, α-terpinolene, 3-p-menthanol, 3-hepten-2-one, ethyl 2-methylbutanoate, etc. These findings promised non-destructive and timely monitoring for disease occurrence during kiwifruit postharvest.

Identification of Different Steaming Degrees of Panax quinquefolius L. Based on GC-IMS Combined With Machine Learning

RATIONALE

Panax quinquefolius L. (PQ), a commonly used traditional Chinese medicine and a food, is usually processed into various products, including white PQ, red PQ (two- or three-time steamed PQ), and black PQ (nine-time steamed PQ). Previous studies demonstrated that volatile components (VOCs) were the important active substances of PQ, which had antibacterial, antiviral, and anti-leukemia activities. However, most research had focused on ginsenosides, and few studies on the volatile components (VOCs) of PQ.

METHODS

This study used gas chromatography-ion mobility spectrometry to analyze the variation of VOCs in PQ during steaming process. Further, machine learning algorithms were used to quickly identify the steaming degrees of PQ samples.

RESULTS

A total of 58 VOCs were identified, and 20 featured components with significant changes in the content were screened, including 2-methylundecanal, n-propanol, and n-octanol. Based on these 20 featured components, six machine learning algorithms were used to predict PQ samples with different steaming degrees. Among them, naive Bayes (NB) and linear discriminant analysis (LDA) exhibited good predictive performance, demonstrating significant potential application. This study provided a reference for understanding the variation of VOCs in PQ during steaming and offered a simple, rapid, and low-cost method for distinguishing the steaming degrees of PQ samples.

Characterization of the differences in lipid profiles and volatile compounds of adipose stem cells adipogenic differentiation and adipocytic transdifferentiation of muscle stem cells from large yellow croakers based on UPLC-MS/MS and GC-IMS

Lipids contribute significantly to the flavor of cell-cultured fish meat as precursor components of flavor compounds. Here, we initially reported the differences in lipid metabolite profiles and volatile compounds between adipogenic differentiation of adipose stem cells (ASCs) and adipocytic transdifferentiation of muscle stem cells (MSCs) from large yellow croakers. A total of 2106 lipid metabolites were identified by UPLC-MS/MS. Compared with the MSCs group, 1263 differentially expressed lipid metabolites were found in the ASCs group, with 1026 up-regulated lipid metabolites and 237 down-regulated ones. The main lipid differences were fatty acyls (FAs) and glycerolipids (GL). GC-IMS identified a total of 47 volatile compounds. Volatile compounds such as ethyl laurate, nonanal, and 2,3-pentanedione were significantly higher in the ASCs group than in the MSCs group. GC-IMS results indicated that the ASCs group was more flavorful. This study provides a theoretical basis for developing cell-cultured fish meat with a familiar flavor.

Impact of Oil Temperature and Splashing Frequency on Chili Oil Flavor: Volatilomics and Lipidomics

In this study, headspace gas chromatography-ion mobility spectrometry, headspace gas chromatography-mass spectrometry, and lipidomics were used to explore the effects of three oil temperatures (210 °C, 180 °C, 150 °C) with single- and traditional triple-oil-splashing processes (210 °C → 180 °C → 150 °C) on the formation of key chili oil aromas. A total of 31 key aroma compounds were identified, with 2,4-nonadienal, α-pinene, α-phellandrene, and β-ocimene being found in all treatment groups. Lipidomics suggested that oleic acid, linoleic acid, and α-linolenic acid were highly positively correlated with key chili oil key aroma compounds, such as (E)-2-heptenal, 2-methylbutyraldehyde, limonene, (E, E)-2,4-heptadienal, 2,4-nonadienal, and 2,4-decadienal. The temperature and frequency of oil splashing significantly affected the chili oil aroma profile (p < 0.05). The citrus, woody, and grassy notes were richer in chili oil prepared at 150 °C, malty and fatty aromas were more prominent at 180 °C, and the nutty aroma was stronger in 210 °C prepared and triple-splashed chili oil. The present study reveals how sequential oil splashing processes synergistically activate distinct lipid degradation pathways compared to single-temperature treatments, providing new insights into lipid-rich condiment preparation, enabling chefs and food manufacturers to target specific aroma profiles.

HS-GC-IMS Coupled With Chemometrics Analyzes Volatile Aroma Compounds in Steamed Polygonatum cyrtonema Hua at Different Production Stages

Headspace-gas chromatography-ion migration spectrometry (HS-GC-IMS) combined with chemometrics was used to analyze the changes in volatile aroma compounds (VOCs) at different production stages of steaming Polygonatum cyrtonema Hua. Fifty-seven representative compounds in the process of steaming were identified, including 17 aldehydes, 15 alcohols, 15 ketones, 5 esters, 3 furans, and 2 acids. After steaming, the content of 21 compounds decreased. Among them, 3 compounds gradually decreased along with an increase in steaming times; they were 1-hexanol dimer, 1-hexanol monomer, and 3-methylbutan-1-ol dimer. The content of 14 compounds increased than before, and that of three, 1-(2-furanyl)ethanone monomer, 2-furaldehyde, and 3-methyl butanal, increased significantly in the steaming times. The VOCs of the different samples can be classified by GC-IMS data combined with principal component analysis (PCA) and heatmap cluster analysis. A reliable prediction set was established by orthogonal partial least squares discriminant analysis (OPLS-DA), and 18 different VOCs with projected variable importance (VIP) greater than 1.0 were screened out, which could be used as differentiating markers. Therefore, HS-GC-IMS and PCA were used to rapidly identify and classify the VOCs in different production stages of steaming P. cyrtonema Hua.

A comprehensive review of analytical techniques for spice quality and safety assessment in the modern food industry

The rapid evolution of analytical techniques has revolutionized spice quality assessment, offering unprecedented opportunities for ensuring the safety, authenticity, and desirable characteristics of these valuable commodities. This review explores the innovative integration of advanced chromatographic, spectroscopic, sensory and molecular methods, combined with chemometrics and machine learning, to provide a comprehensive and standardized approach to spice analysis. The development of portable, rapid screening devices and the application of cutting-edge technologies, such as hyperspectral imaging, molecular and electronic sensory technologies, and their combined applications with other technologies are discussed in the review. Furthermore, the review emphasizes the importance of global collaboration and the shift toward non-targeted approaches to detect novel adulterants and contaminants. By adopting these innovative strategies, the modern food industry can effectively address the challenges of spice quality control, safeguarding consumer health and maintaining the integrity of these essential ingredients in the global culinary landscape.

Non-targeted volatilomics for the authentication of saffron by gas chromatography-ion mobility spectrometry and multivariate curve resolution

In the present contribution, a novel non-targeted volatilomic study based on headspace GC-IMS (HS-GC-IMS) was developed for the authentication and geographical origin discrimination of saffron. In this regard, multivariate curve resolution-alternating least squares (MCR-ALS) was employed to recover the pure GC elution and IMS profiles of saffron metabolites. Iranian saffron samples from seven important areas were analyzed by HS-GC-IMS. The resulting second-order GC-IMS datasets were organized in a augmented matrix and processed using MCR-ALS with various constraints. The MCR-ALS resolved GC profiles were analyzed by different pattern recognition techniques; principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and data driven-soft independent modeling of class analogy (DD-SIMCA). The saffron samples were assigned to their seven geographical origins with an accuracy of 89.0 %. Additionally, four adulterants (style, safflower, madder and calendula) were reliably detected with over 94.0 % accuracy. In this context, GC-IMS substantially outperformed the commonly used FT-NIR spectroscopy approach.

Analysis of the effect of three different blanching processes on the flavor profile of peeled and unpeeled broad beans

Broad beans, a seasonal leguminous vegetable renowned for their distinctive flavor and high-quality plant protein, present unique opportunities for culinary and nutritional applications. To better understand the impact of various blanching processes on their characteristics, we employed headspace gas chromatography-ion mobility mass spectrometry (HS-GC-IMS) and biochemical tests to evaluate changes in color, volatile compound content, and levels of antioxidant-related substances following different blanching treatments. Our findings revealed that microwave blanching significantly influenced the a* metric and antioxidant capacity of broad beans. Specifically, we identified 44 volatile compounds in peeled broad beans and 57 in unpeeled ones. The steam-blanched broad beans retained a flavor profile similar to the control samples, characterized by relatively high concentrations of alcohols, aldehydes, and esters, contributing to a fruity and fresh aroma. In contrast, microwave blanching led to higher concentrations of aldehydes and alcohols and introduced additional odor characteristics such as mushroom, cocoa, and almond notes, enhancing the complexity of the flavor profile. This study provided the essential knowledge for further utilization of broad beans as well as the extension of their shelf life.

How Machine Learning and Gas Chromatography-Ion Mobility Spectrometry Form an Optimal Team for Benchtop Volatilomics

This invited feature article discusses the potential of gas chromatography-ion mobility spectrometry (GC-IMS) as a point-of-need alternative for volatilomics. Furthermore, the capabilities and versatility of machine learning (ML) (chemometric) techniques used in the framework of GC-IMS analysis are also discussed. Modern ML techniques allow for addressing advanced GC-IMS challenges to meet the demands of modern chromatographic research. We will demonstrate workflows based on available tools that can be used with a clear focus on open-source packages to ensure that every researcher can follow our feature article. In addition, we will provide insights and perspectives on the typical issues of the GC-IMS along with a discussion of the process necessary to obtain more reliable qualitative and quantitative analytical results.

Innovative Supported Membranes for Ion Mobility Spectrometer (IMS) Sample Introduction Systems with High Permeability Relative to Toxic Agents in Air (TAAs)

One of the main objectives of the ion mobility spectrometry (IMS) technique is to reduce moisture in detection systems, which causes the formation of ion clusters and ion water and a reduction in formed clusters' activity. Thus, one of the methods limiting moisture in a sampling injection system is to use hydrophobic polymeric membranes. The use of membranes with high permeability relative to the analysed organic compounds is required, including toxic agents in air (TAAs). Such requirements align with those of polydimethylsiloxane (PDMS) membranes. Unfortunately, thin PDMS membranes are not mechanically resistant. In this study, relatively thin PDMS membranes were reinforced with fine mesh fabric supports. These supports were chemically modified with selected oligoglycol derivatives and finally coated with PDMS. The obtained membranes were tested for water permeability and TAA simulants.

Comparative study on organoleptic properties and volatile organic compounds in turmeric, turmeric essential oil, and by-products using E-nose, HS-GC-IMS, and HS-GC-MS

The properties, applications, and in vitro bioactivities of turmeric, turmeric essential oil (TEO), and turmeric essential oil by-products (TEO-BP) were evaluated using sensory analysis, gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS), and electronic nose techniques. A total of 62 and 66 volatile organic compounds (VOCs), primarily terpenoids and sesquiterpenoids, were identified by GC-MS and GC-IMS, respectively. Distillation temperature, particularly at 90 °C, significantly influenced the color and organoleptic properties of TEO, with variations in VOC profiles driving these differences. Molecular distillation at 90 °C was found to optimize the purification and concentration of key VOCs in TEO. All turmeric samples demonstrated robust antioxidant and α-glucosidase inhibitory activities, with TEO-90 exhibiting the highest bioactivity. These results underscore the potential applications of TEO and TEO-BP in food and nutraceutical industries, offering a sustainable strategy to reduce waste and enhance the efficient utilization of turmeric resources.

Effect of inoculation with different Eurotium cristatum strains on the microbial communities and volatile organic compounds of Fu brick tea

Eurotium cristatum is the primary fungus in Fu brick tea (FBT) and plays a crucial role in its special flavor. This study investigated the effect of inoculation with different E. cristatum strains (i.e., ZJ, GX, GZ, HN, and SX) on the microbial communities and volatile organic compounds (VOCs) of FBT. A total of 113 VOCs were identified in all samples, with the concentration of VOCs (alcohols, aldehydes, and ketones) significantly higher in GXE FBT than in other samples. The core VOCs of GXE (19), GZE (16), HNE (19), SXE (15), and ZJE (13) FBT were identified using orthogonal partial least squares discriminant analysis and relative odor activity value (ROAV) analysis. Methional (a27), butanal (a41), 1-octen-3-one (a69), and ethyl acetate (a77) were key markers for inoculated FBTs, and 1-octen-3-ol, dimethyl disulfide, and acetoin-M were the specific markers of HNE. Linalool and (E)-2-octenal were particularly prominent in GXE, and isoamyl acetate-D was an important aroma component of GZE. Differences in microbial diversity were observed among the different inoculated fermented FBTs, and E. cristatum inoculation remarkably influenced the richness and diversity of bacterial communities. The VOCs were closely associated with fungi and bacteria, and 19 potentially dominant microorganisms (10 fungal and 9 bacterial genera) correlated with VOCs were identified. Among them, Aspergillus (fungi) and Pseudomonas (bacteria) exerted the greatest role. The FBT inoculated with E. cristatum from ZJ had the highest content of theaflavins and theabrownins, which intensified the red and yellow colors of the tea. E. cristatum greatly decreased the free amino acids and fatty acids, contributing to the aroma formation of FBT. Therefore, inoculating FBT with E. cristatum remarkably influenced the microbial communities and improved its flavor profile. This work provides a theoretical foundation on the role of E. cristatum in the formation and regulation of FBT flavor.

Gas chromatography-ion mobility spectrometry for the detection of human disease: a review

Gas chromatography-ion mobility spectrometry (GC-IMS) is an advanced technique used for detecting trace compounds, due to its non-destructive, straightforward, and rapid analytical capabilities. However, the application of GC-IMS in human disease screening is barely reported. This review summarizes the application and related parameters of GC-IMS in human disease diagnosis. GC-IMS detects volatile organic compounds in human breath, feces, urine, bile, etc. It can be applied to diagnose diseases, such as respiratory diseases, cancer, enteropathy, Alzheimer's disease, bacterial infection, and metabolic diseases. Several potential disease markers have been identified by GC-IMS, including ethanal (COVID-19), 2-heptanone (lung cancer) and 3-pentanone (pulmonary cryptococcosis). In conclusion, GC-IMS offers a non-invasive approach to monitor and diagnose human diseases with broad applications.

Rapid separation of bile acid isomers via ion mobility mass spectrometry by complexing with spiramycin

Bile acid (BA) is one of the main active components of bile and has multiple isomers, the structure or content of its isomers often changes due to diseases and other health problems; thus, the accurate detection of BA isomers is very important. In this study, two groups of BA isomers of glycine-conjugated BAs and taurine-conjugated BAs were simultaneously separated and quantitatively analyzed by ion mobility mass spectrometry (IM-MS). Especially, baseline mobility separation between the isomers was achieved by the formation of binary complexes via simple interaction with spiramycin (SPM), for which a separation resolution (Rp-p) of 1.96 was reached. Moreover, BA isomers were quantitatively analyzed, and the limit of detection (LOD) of absolute quantification for TCDCA/TUDCA and GUDCA/GCDCA/GHDCA was 0.514 and 0.611 ng∙mL-1, respectively; the LODs for molar ratio ranges of relative quantification for TCDCA/TUDCA, GUDCA/GHDCA, and GCDCA/GHDCA were 1:18-30:1, 1:18-21:1, and 1:19-21:1, respectively. Additionally, BA isomers analyzed in pig bile powder and bear bile powder were measured, which were in good consistency with those labeled, revealing the differences in BA composition and content between the two powders. Finally, BA detection and recovery analyses were performed on serum samples, with a recovery rate of ≥73.69%, RSD of ≤6.8%, and SR (standard deviation of recoveries, the degree of difference between measured values and average recovery) of ≤1.27. Due to the simple, rapid, and lack of need for complex sample preparation and chromatographic separation, the proposed method can be an effective method for BA detection in practical samples.

PungentDB: Bridging traditional Chinese medicine of medicine food homology and modern food flavor chemistry

Merging traditional Chinese medicine's (TCM) principles of medicine-food homology with modern flavor chemistry, this research unveils PungentDB (http://www.pungentdb.org.cn/home), a database documenting 205 unique pungent flavor compounds from 231 TCMs. It provides detailed insights into their chemical attributes, biological targets (including IC50/EC50 values), and molecular structures (2D/3D), enriched with visualizations of target organ distribution and protein structures, exploring the pungent flavor space with the help of a feature-rich visual interface. This collection, derived from over 3249 sources and highlighting 9129 targets, delves into the compounds' unique pungent flavors-taste, aroma, and thermal sensations-and their interaction with taste and olfactory receptors. PungentDB bridges ancient wisdom and culinary innovation, offering a nuanced exploration of pungent flavors' role in enhancing food quality, safety, and sensory experiences. This initiative propels flavor chemistry forward, serving as a pivotal resource for food science advancement and the innovative application of pungent flavors.

Computer Vision-Assisted Robotized Sampling of Volatile Organic Compounds

In conventional chemical analysis, samples are homogenized, extracted, purified, and injected into an analytical instrument manually or with a certain degree of automation. Such complex methods can provide superior performance in terms of sensitivity or selectivity. However, in some cases, it would be advantageous to possess a method that circumvents those preparatory steps, which require much attention. Here, we present a facile analytical approach to sampling volatile organic compounds (VOCs). Solid specimens emitting VOCs can be dropped onto the drop-off zone at a random position without any special alignment. A computer vision system recognizes specimen position, and a robotic arm places a sampling probe in the proximity of the specimen. The probe aspirates the VOCs─emitted by the specimen─with the aid of a suction force. A portion of the gaseous extract is transferred to the tritium-based ion source of a drift-tube ion mobility spectrometer. The ion mobility spectrum is immediately displayed in the customized graphical user interface (GUI). The sampling system also features a function for flushing extract ducts with hot nitrogen gas. Multiple specimens can be dropped for analysis at the same time. In one embodiment, the system can distinguish fresh meat from spoiled meat. When two meat specimens are placed on the drop-off zone, they are immediately sampled by the robotic arm, analyzed, and labeled on the digital image displayed on the GUI. Thus, the developed autosampling platform provides a hassle-free way of qualitative or semiquantitative analysis of raw specimens.

Volatile Flavor Analysis in Yak Meat: Effects of Different Breeds, Feeding Methods, and Parts Using GC-IMS and Multivariate Analyses

This study investigates the effects of breeds, feeding methods, and parts on the volatile flavor of yak meat. Gas chromatography-ion mobility spectrometry (GC-IMS) and multivariate analysis were used to analyze the volatile organic components (VOCs) in yak meat from various sources. A total of 71 volatile compounds were identified, 53 of which were annotated based on the GC-IMS database. These include 20 alcohols, 16 ketones, 10 aldehydes, four alkenes, one ester, one acid, and one furan. Using VOC fingerprinting and multivariate analysis, yak meats from different sources were distinctly categorized. Breed had the most significant impact on yak meat VOCs, followed by feeding method and then part. Six volatiles with a variable importance in projection value greater than one were identified as potential markers for distinguishing yak meat. This study offers insights into the flavor profile of yak meat from different sources and demonstrates the efficacy of GC-IMS and multivariate analysis in characterizing and discriminating meats.

Discriminative analysis of aroma profiles in diverse cigar products varieties through integrated sensory evaluation, GC-IMS and E-nose

Cigars, treasured for their rich aromatic profiles, occupy a notable segment in the global consumer market. The objective of this study was to characterize the volatile aroma compounds that shape the flavor profiles of six distinct varieties of Great Wall cigars, contributing to the understanding of cigar aroma analysis. Utilizing HS-GC-IMS and sensory evaluation, the study discerned the aroma profiles of GJ No. 6 (GJ), Animal from the Chinese zodiac (SX), Range Rover No. 3 Classic (JD), Miracle 132 (QJ), Sheng Shi No. 5 (SS), and Red 132 (HS) cigars. The analysis uncovered a spectrum of characteristic aromas, including tobacco, creaminess, cocoa, leather, baking, herbaceous, leathery, woodsy, and fruity notes. A total of 88 compounds were identified, categorized into 11 chemical classes, with their quantities varying among the cigars in a descending order of QJ, JD, GJ, SS, HS, and SX. 24 compounds, such as 2-heptanone, n-butanol, 2,6-dimethylpyrazine and 2-furfuryl methyl sulfide were considered as key differential components. The volatile components were effectively differentiated using principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and cluster analysis, revealing correlations between sensory attributes, key components, and electronic nose (E-nose). This research introduces a novel method for analyzing volatile aroma components in cigars, offering insights to enhance cigar quality and to foster the development of new products with unique aroma profiles.

Effects of discharge plasma on seed germination and volatile compounds content of Agropyron Mongolicum

To investigate the effects of discharge plasma on Agropyron mongolicum seeds, various treatments including direct exposure to discharge plasma, combined treatment with discharge plasma and plasma-activated water (PAW) were applied to the seeds. The changes in germination rate, MDA content, and volatile compound levels of Agropyron mongolicum seeds after different treatments were examined. The results showed that the direct effect of plasma had no significant effect on the MDA content or germination rate of Agropyron mongolicum seeds due to the limited penetration depth. However, the combined effect of plasma and activated water could cause active nitrogen and oxygen particles to enter the seeds and cause oxidative stress damage. After 18 h of combined treatment, the MDA content increased significantly, and the germination rate decreased to below the semilethal dose, which was 33.44 %. After plasma treatment, 55 volatile compounds, mainly alcohols, aldehydes and ketones, were identified from the seeds of Agropyron mongolicum. Due to the oxidation and modification of the plasma, the content of most aldehydes increased with increasing reaction time. After screening, 13 volatile organic compounds could be used as potential markers to distinguish between different treatment methods. These results reveal the mechanism underlying the biological effects of plasma treatment on Agropyron mongolicum seeds.

Analysis of flavor substances changes during fermentation of Chinese spicy cabbage based on GC-IMS and PCA

This study employed a combination of principal component analysis (PCA) and gas chromatography-ion mobility spectrometry (GC-IMS) to examine the distinctive taste mixtures produced by Chinese spicy cabbage (CSC) fermented at varying temperatures. As the fermentation progressed, the pH gradually decreased and stabilized after the 11 days of fermentation, and the total content of organic acids and short-chain fatty acids increased. A total of 49 volatile mixtures were detected during CSC fermentation and storage for 21 days. These included 7 aldehydes, 6 alcohols, 7 esters, 6 ketones, 5 pyrazines, 4 sulfides, 4 phenols, 2 ethers, 2 olefins, and 1 acid. With time, the content of most volatile flavor substances decreased. PCA of the signal intensities of the volatile chemicals in the samples showed significant differences in the flavor of CSC fermented at different temperatures; consequently, the samples fermented at different temperatures were effectively separated in relatively independent regions of CSC. Therefore, low-temperature fermentation and storage at 4 °C were more suitable for CSC. Based on the identified volatile chemicals, HS-GC-IMS and PCA could effectively construct the flavour fingerprints of CSC samples. This study provided a theoretical basis for improving the fermentation quality of CSC.

Characterizing the composition of volatile compounds in different types of Chinese bacon using GC-MS, E-nose, and GC-IMS

Chinese bacon is highly esteemed by consumers worldwide due to its unique aroma. The composition of volatile organic compounds (VOCs) varies significantly among different types of Chinese bacon. This study analyzed the VOCs of Chinese bacon from Sichuan, Hunan, Guangxi, and Shaanxi provinces using gas chromatography-mass spectrometry (GC-MS), an electronic nose (E-nose), and gas chromatography-ion mobility spectrometry (GC-IMS). The results demonstrate that the combination of GC-MS and GC-IMS effectively distinguishes Chinese bacon from different regions. Notably, Guangxi bacon lacks a smoky aroma, which sets it apart from the other types. However, it contains many esters that play a crucial role in its flavor profile. In contrast, phenols, including guaiacol, which is typical in smoked bacon, were present in the bacon from Sichuan, Hunan, and Shaanxi but were absent in Guangxi bacon. Furthermore, Hunan bacon exhibited a higher aldehyde content than Sichuan bacon. 2-methyl-propanol and 3-methyl-butanol were identified as characteristic flavor compounds of Zhenba bacon. This study provides a theoretical foundation for understanding and identifying the flavor profiles of Chinese bacon. Using various analytical techniques to investigate the flavor compounds is essential for effectively distinguishing bacon from different regions.

HS-GC-IMS Analysis of Volatile Organic Compounds in Six Spicy Spices and Their Effects on Ulcerative Colitis

The volatile organic compounds of six spices, including black pepper, dried ginger, cinnamon, fennel, clove, and zanthoxylum, were analyzed by gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with principal component analysis (PCA) and Euclidean distance. In further analyses, the effects of volatile oils in six spices on ulcerative colitis were assayed in a zebrafish model induced by 3-nitrobenzenesulfonic acid. A total of 120 kinds of volatile organic compounds were detected and 80 among them were identified, which included 10 common components and 3 to 24 characteristic components belonging to different spices. The major VOCs in six spices were estimated to be terpenes with the contents of 45.02%, 56.87%, 36.68%, 58.19%, 68.68%, and 30.62%, respectively. Meanwhile, the volatile components of fennel, dried ginger, black pepper, and cinnamon are quite similar, but differ from clove and zanthoxylum. The volatile oils in six spices presented efficient activity to improve ulcerative colitis which can decrease the number of neutrophils, restore the structure of intestinal epithelial and the morphology of the epithelial cells. Our study achieved rapid analysis of the volatile organic compounds and flavors in six spices and further revealed the potential health benefits of their volatile oils on ulcerative colitis, especially for clove and zanthoxylum. This study is expected to provide certain data support for the quality evaluation and the potential use in functional foods of six spices.

Metal-Organic Frameworks in Surface Enhanced Raman Spectroscopy-Based Analysis of Volatile Organic Compounds

Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on-site detection without complex sample preparation. Surface-Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal-Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre-concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF-based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.

Airborne signals of Pseudomonas fluorescens modulate swimming motility and biofilm formation of Listeria monocytogenes in a contactless coculture system

Bacterial volatile compounds (BVCs) facilitate interspecies communication in socio-microbiology across physical barriers, thereby influencing interactions between diverse species. The impact of BVCs emitted from Pseudomonas on the biofilm formation characteristics of Listeria monocytogenes within the same ecological niche has been scarcely investigated under practical conditions of food processing. The objective of this study was to explore the motility and biofilm formation characteristics of L. monocytogenes under the impact of Pseudomonas BVCs. It was revealed that BVCs of P. fluorescens, P. lundensis, and P. fragi significantly promoted swimming motility of L. monocytogenes (P < 0.05). As evidenced by crystal violet staining, the L. monocytogenes biofilms reached a maximum OD570 value of approximately 3.78 at 4 d, which was 0.65 units markedly higher than that of the control group (P < 0.05). Despite a decrease in adherent cells of L. monocytogenes biofilms among the BVCs groups, there was a remarkable increase in the abundance of extracellular polysaccharides and proteins with 3.58 and 4.90 μg/cm2, respectively (P < 0.05), contributing to more compact matrix architectures, which suggested that the BVCs of P. fluorescens enhanced L. monocytogenes biofilm formation through promoting the secretion of extracellular polymers. Moreover, the prominent up-regulated expression of virulence genes further revealed the positive regulation of L. monocytogenes under the influence of BVCs. Additionally, the presence of BVCs significantly elevated the pH and TVB-N levels in both the swimming medium and biofilm broth, thereby exhibiting a strong positive correlation with increased motility and biofilm formation of L. monocytogenes. It highlighted the crucial signaling regulatory role of BVCs in bacterial interactions, while also emphasizing the potential food safety risk associated with the hitchhiking behavior of L. monocytogenes, thereby shedding light on advancements in control strategies for food processing.

Benchtop volatilomics supercharged: How machine learning based design of experiment helps optimizing untargeted GC-IMS gas phase metabolomics

Gas chromatography-ion mobility spectrometry (GC-IMS) plays a significant role in both targeted and non-targeted analyses. However, the non-linear behavior of IMS and its complex ion chemistry pose challenges for finding optimal experimental conditions using existing methodologies. To address these issues, integrating machine learning (ML) strategies offers a promising approach. In this study, we propose a hybrid strategy, combining design of experiment (DOE) and machine learning (ML) for optimizing GC-IMS conditions in non-targeted volatilomic/flavoromic analysis, with saffron volatiles as a case study. To begin, a rotatable circumscribed central composite design (CCD) is used to define five influential GC-IMS factors of sample amount, headspace temperature, incubation time, injection volume, and split ratio. Subsequently, two ML models are utilized: multiple linear regression (MLR) as a linear model and Bayesian regularized-artificial neural network (BR-ANN) as a nonlinear model. These models are employed to predict the response variables of total peak areas (PAs) and the number of detected peaks (PNs) in GC-IMS. The findings show that there is a direct correlation between the factors in GC-IMS and the PNs, suggesting that MLR is a suitable approach for building a model in this scenario. However, the PAs exhibit nonlinear behavior, suggesting that BR-ANN is better suitable to capture this complexity. Notably, Derringer's desirability function is utilized to integrate the PAs and PNs, and in this scenario, MLR demonstrates satisfactory performance in modeling the GC-IMS factors.

Key components, formation pathways, affecting factors, and emerging analytical strategies for edible mushrooms aroma: A review

Aroma is one of the decisive factors affecting the quality and consumer acceptance of edible mushrooms. This review summarized the key components and formation pathways of edible mushroom aroma. It also elaborated on the affecting factors and emerging analytical strategies of edible mushroom aroma. A total of 1308 volatile organic compounds identified in edible mushrooms, 61 were key components. The formation of these compounds is closely related to fatty acid metabolism, amino acid metabolism, lentinic acid metabolism, and terpenoid metabolism. The aroma profiles of edible mushrooms were affected by genetic background, preharvest factors, and preservation methods. Molecular sensory science and omics techniques are emerging analytical strategies to reveal aroma information of edible mushrooms. This review would provide valuable data and insights for future research on edible mushroom aroma.

An Evaluation of the Impact of 60Co Irradiation on Volatile Organic Compounds of Olibanum Using Gas Chromatography Ion Mobility Spectrometry

Olibanum is a resinous traditional Chinese medicine that is directly used as a powder. It is widely used in China and is often combined with other traditional Chinese medicine powders to promote blood circulation and relieve pain, as well as to treat rheumatism, rheumatoid arthritis, and osteoarthritis. Powdered traditional Chinese medicine is often easily contaminated by microorganisms and 60Co irradiation is one of the good sterilization methods. Volatile organic compounds (VOCs) are the main active ingredient of olibanum. The aim of this study was to validate the optimum doses of 60Co irradiation and its effect on VOCs. 60Co irradiation was applied in different doses of 0 kGy, 1.5 kGy, 3.0 kGy, and 6.0 kGy. Changes in VOCs were detected using gas chromatography ion mobility spectrometry. A total of 81 VOCs were identified. The odor fingerprint results showed that, with an increase in irradiation dose, most of the VOCs of olibanum changed. Through principal component analysis, cluster analysis, and partial least squares discriminant analysis, it was demonstrated that, at 1.5 kGy, the impact of radiation on the VOCs of olibanum was minimal, indicating this is a relatively good irradiation dose. This study provides a theoretical basis for the irradiation processing and quality control of resinous medicinal materials such as olibanum and it also provides a good reference for irradiation technology development and its application to functional foods, thus making it both significant from a research perspective and useful from an application perspective.

Discrimination and characterization of volatile organic compounds in Lonicerae Japonicae flos and Lonicerae flos using multivariate statistics combined with headspace gas chromatography-ion mobility spectrometry and headspace solid-phase microextraction gas chromatography-mass spectrometry techniques

RATIONALE

The volatile organic compounds (VOCs) of Lonicerae Japonicae flos (LJF) and Lonicera flos (LF) play a pivotal role in determining their sensory characteristics, medicinal properties, and subsequent impact on market pricing and consumer preferences. However, the differences and specificity of these VOCs remain obscure. Hence, it is crucial to conduct a comprehensive characterization of the VOCs in LJF and LF and pinpoint their potential differential VOCs.

METHODS

In this study, headspace gas chromatography-ion mobility spectrometry (HS-GC/IMS) and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) were employed to comprehensively investigate the compositional characteristics and distinctions in VOCs between LJF and LF. Multivariate statistical analysis was used to identify candidate differential VOCs of LJF and LF samples.

RESULTS

A total of 54 and 88 VOCs were identified using HS-GC/IMS and HS-SPME-GC/MS analysis, respectively. Primary VOCs detected in LJF include leaf alcohol, (E)-2-hexen-1-ol dimer, 2-octyn-1-ol, and (E)-3-hexen-1-ol. Key VOCs prevalent in LF encompass farnesol, heptanoic acid, octanoic acid, and valeric acid. Multivariate statistical analysis indicates that compounds such as phenethyl alcohol and leaf alcohol were selected as potential VOCs for distinguishing between LJF and LF.

CONCLUSION

This research conducted a comprehensive analysis of the fundamental volatile components in both LJF and LF. It subsequently elucidated the distinctions and specificities within their respective VOC profiles. And this study enables differentiation between LJF and LF through the analysis of VOCs, offering valuable insights for enhancing the quality control of both LJF and LF.

Comprehensive multicomponent characterization and quality assessment of Xiaoyao Wan by UPLC-Q-Orbitrap-MS, HS-SPME-GC-MS and HS-GC-IMS

Xiaoyao Wan (XYW) is a prescription medicine of traditional Chinese medicine (TCM) with the effects of "soothing the liver and relieving depression," and "strengthening spleen and nourishing blood". XYW has been widely concerned in the treatment of depression and has become one of the commonly used classic formulas in clinical practice. However, the pharmacodynamic substance basis and the quality control studies of XYW are hitherto quite limited. Here, we aim to fully utilize an advanced ultra - performance liquid chromatography-quadrupole - Orbitrap mass spectrometry (UPLC-Q-Orbitrap-MS), headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technique to deep characterization of the pharmacological substance basis and quantitatively evaluate the quality of XYW. Firstly, 299 compounds were identified or tentatively characterized, including 198 non-volatile organic compounds (n-VOCs) and 101 volatile organic compounds (VOCs). Secondly, principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to analyze quality differences in XYW at different manufacturers. Thirdly, a parallel reaction monitoring (PRM) method was established and validated to quantify the fourteen major effective substances in different manufacturers of XYW, which were chosen as the benchmarked substances to evaluate the quality of XYW. In conclusion, this study shows that the strategy provides a useful method for quality control of TCM and offers a practical workflow for exploring the quality consistency of TCM.

Automated 2D peak detection in gas chromatography-ion mobility spectrometry through persistent homology

BACKGROUND

Gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful analytical technique which has gained widespread use in a variety of fields. Detecting peaks in GC-IMS data is essential for chemical identification. Topological data analysis (TDA) has the ability to record alterations in topology throughout the entire spectrum of GC-IMS data and retain this data in diagrams known as persistence diagrams. To put it differently, TDA naturally identifies characteristics such as mountains, volcanoes, and their higher-dimensional equivalents within the original data and measures their significance.

RESULTS

In the present contribution, a novel approach based on persistent homology (a flagship technique of TDA) is suggested for automatic 2D peak detection in GC-IMS. For this purpose, two different GC-IMS data examples (urine and olive oil) are used to show the performance of the proposed method. The outputs of the algorithm are GC-IMS chromatogram with detected peaks, persistence plot showing the importance (intensity) of the detected peaks and a table with retention times (RT), drift times (DT), and persistence scores of detected peaks. The RT and DT can be used for identification of the peaks and persistence scores for quantitation. Additionally, watershed segmentation is applied to the GC-IMS images to index individual peaks and segment overlapping compounds allowing for a more accurate identification and quantification of individual peaks.

SIGNIFICANCE

Inspection of the results for GC-IMS datasets showed the accurate and reliable performance of the proposed strategy based on persistent homology for automatic 2D GC-IMS peak detection for qualitative and quantitative analysis. In addition, this approach can be easily extended to other types of hyphenated chromatographic and/or spectroscopic data.

Influence of lactic acid fermentation on the phenolic profile, antioxidant activities, and volatile compounds of black chokeberry (Aronia melanocarpa) juice

Lactic acid fermentation is an effective method for improving the quality of black chokeberry. This study aimed to investigate the influence of lactic acid bacteria on the phenolic profile, antioxidant activities, and volatiles of black chokeberry juice. Initially, 107  cfu/mL of Lactiplantibacillus plantarum, Lactobacillus acidophilus, and Lacticaseibacillus rhamnosus were inoculated into pasteurized black chokeberry juice and fermented for 48 h at 37°C. All these strains enhanced the total phenolic and total flavonoid contents, with La. acidophilus showing the highest total phenolic (1683.64 mg/L) and total flavonoid (659.27 mg/L) contents. Phenolic acids, flavonoids, and anthocyanins were identified using ultrahigh-performance liquid chromatography-tandem mass spectrometry. The prevalent phenolic acid, flavonoid, and anthocyanin in the lactic-acid-fermented black chokeberry juice were cinnamic acid, rutin, and cyanidin-3-O-rutinoside, respectively. Furthermore, following fermentation, the DPPH and ABTS scavenging capacity, as well as the reducing power capacity, increased from 59.98% to 92.70%, 83.06% to 94.95%, and 1.24 to 1.82, respectively. Pearson's correlation analysis revealed that the transformation of phenolic acids, flavonoids, and anthocyanins probably contributed to enhancing antioxidant activities and color conversation in black chokeberry juice. A total of 40 volatiles were detected in the fermented black chokeberry juice by gas chromatography-ion mobility spectrometry. The off-flavor odors, such as 1-penten-3-one and propanal in the black chokeberry juice, were weakened after fermentation. The content of 2-pentanone significantly increased in all fermented juice, imparting an ethereal flavor. Hence, lactic acid fermentation can effectively enhance black chokeberry products' flavor and prebiotic value, offering valuable insights into their production. PRACTICAL APPLICATION: The application of lactic acid bacteria in black chokeberry juice not only enhances its flavor but also improves its health benefits. This study has expanded the range of black chokeberry products and offers a new perspective for the development of the black chokeberry industry.

Comparative Analysis of Volatile Compounds in the Flower Buds of Three Panax Species Using Fast Gas Chromatography Electronic Nose, Headspace-Gas Chromatography-Ion Mobility Spectrometry, and Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources.

Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling

In order to investigate the flavour characteristics of aromatic, glutinous, and nonaromatic rice, gas chromatography-ion mobility spectrometry (GC-IMS) was used to analyse the differences in volatile organic compounds (VOCs) amongst different rice varieties. The results showed that 103 signal peaks were detected in these rice varieties, and 91 volatile flavour substances were identified. Amongst them, 28 aldehydes (28.89~31.17%), 24 alcohols (34.85~40.52%), 14 ketones (12.26~14.74%), 12 esters (2.30~4.15%), 5 acids (7.80~10.85%), 3 furans (0.30~0.68%), 3 terpenes (0.34~0.64%), and 2 species of ethers (0.80~1.78%) were detected. SIMCA14.1 was used to perform principal component analysis (PCA) and orthogonal partial least squares discriminant analysis, and some potential character markers (VIP > 1) were further screened out of the 91 flavour substances identified based on the variable important projections, including ethanol, 1-hexanol, hexanal, heptanal, nonanal, (E)-2-heptenal, octanal, trans-2-octenal, pentanal, acetone, 6-methyl-5-hepten-2-one, ethyl acetate, propyl acetate, acetic acid, and dimethyl sulphide. Based on the established fingerprint information, combined with principal component analysis and orthogonal partial least squares discriminant analysis, different rice varieties were also effectively classified, and the results of this study provide data references for the improvement in aromatic rice varieties.

Discriminant Analysis of Aroma Differences between Cow Milk Powder and Special Milk Powder (Donkey, Camel, and Horse Milk Powder) in Xinjiang Based on GC-IMS and Multivariate Statistical Methods

In order to explore the aromatic differences between Xinjiang cow milk powder and specialty milk powder (donkey, camel, and horse milk powder), Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) analysis was employed to investigate the volatile compounds in these four types of milk powders. A total of 61 volatile substances were detected, with ketones, aldehydes, and alcohols being the primary flavor components in the milk powders. While the aromatic components of the different milk powders showed similarities in terms of types, there were significant differences in their concentrations, exhibiting distinct characteristics for each type. The Partial Least Squares Discriminant Analysis (PLS-DA) showed that there were 15, 14, and 23 volatile compounds that could be used for discrimination of cow milk powder against specialty milk powders, respectively. And it was validated by Receiver Operating Characteristic (ROC) analysis, and finally, 8, 6, and 19 volatile compounds were identified as valid differential marker substances. To facilitate visual discrimination between the different milk powders, we established GC-IMS fingerprint spectra based on the final discriminant markers. These studies provide theoretical guidance for the application of volatile compounds to discriminate adulteration of milk powder marketed in Xinjiang.

HS-GC-IMS Analysis of Volatile Organic Compounds in Different Varieties and Harvesting Times of Rhizoma gastrodiae (Tian Ma) in Yunnan Province

Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) coupled with principal component analysis (PCA) was used to investigate the differences in volatile organic compounds (VOCs) in four different varieties of Yunnan Huang Tian Ma (containing both winter and spring harvesting times), Yunnan Hong Tian Ma, Yunnan Wu Tian Ma, and Yunnan Lv Tian Ma. The results showed that the flavor substances of different varieties and different harvesting times of Rhizoma gastrodiae were mainly composed of aldehydes, alcohols, ketones, heterocycles, esters, acids, alkenes, hydrocarbons, amines, phenols, ethers, and nitrile. Among them, the contents of the aldehydes, alcohols, ketones, and heterocyclic compounds are significantly higher than those of other substances. The results of cluster analysis and fingerprint similarity analysis based on principal component analysis and Euclidean distance showed that there were some differences between different varieties of Yunnan Rhizoma gastrodiae and different harvesting times. Among them, Yunnan Lv Tian Ma and Wu Tian Ma contained the richest volatile components. Winter may be the best harvesting season for Tian Ma. At the same time, we speculate that the special odor contained in Tian Ma should be related to the aldehydes it is rich in, especially benzene acetaldehyde, Benzaldehyde, Heptanal, Hexanal, Pentanal, and butanal, which are aldehydes that contain a strong and special odor and are formed by the combination of these aldehydes.

Analysis of Volatile Markers and Their Biotransformation in Raw Chicken during Staphylococcus aureus Early Contamination

To address the potential risks to food safety, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) were used to analyze the volatile organic compounds (VOCs) generated from chilled chicken contaminated with Staphylococcus aureus during early storage. Together with the KEGG database, we analyzed differential metabolites and their possible biotransformation pathways. Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to characterize VOCs and identify biomarkers associated with the early stage of chicken meat contamination with S. aureus. The results showed 2,6,10,15-tetramethylheptadecane, ethyl acetate, hexanal, 2-methylbutanal, butan-2-one, 3-hydroxy-2-butanone, 3-methylbutanal, and cyclohexanone as characteristic biomarkers, and 1-octen-3-ol, tetradecane, 2-hexanol, 3-methyl-1-butanol, and ethyl 2-methylpropanoate as potential characteristic biomarkers. This provides a theoretical basis for the study of biomarkers of Staphylococcus aureus in poultry meat.

Differences in Volatile Organic Compounds in Rhizoma gastrodiae (Tian Ma) of Different Origins Determined by HS-GC-IMS

Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and principal component analysis (PCA) were used to compare the differences in volatile organic compounds (VOCs) of Rhizoma gastrodiae (Tian Ma) from six different origins in Yunnan, Sichuan, Shaanxi, Anhui, Hubei, and Guizhou. A total of 161 signal peaks were identified, and 84 compounds were characterized, including 23 aldehydes, 19 alcohols, 12 ketones, 8 heterocyclic compounds, 7 esters, 4 phenols, 4 acids, 4 ethers, 2 amines, and 1 alkane. The results of cluster analysis and fingerprint similarity analysis based on principal component analysis and Euclidean distance indicated that there were significant differences between the volatile components of Rhizoma gastrodiae from different origins. This study demonstrated that HS-GC-IMS is simple, rapid, accurate, and has a small sample size and can achieve rapid analysis of the differences in volatile compounds between samples of different origins of Rhizoma gastrodiae.

Exploring the Characteristic Aroma Components of Traditional Fermented Koumiss of Kazakh Ethnicity in Different Regions of Xinjiang by Combining Modern Instrumental Detection Technology with Multivariate Statistical Analysis Methods for Odor Activity Value and Sensory Analysis

To investigate the characteristic aromatic compounds, present in the traditional fermented koumiss of the Kazakh ethnic group in different regions of Xinjiang, GC-IMS, and GC-MS were used to analyze the volatile compounds in koumiss from four regions. A total of 87 volatile substances were detected, and esters, acids, and alcohols were found to be the main aroma compounds in koumiss. While the types of aroma compounds in koumiss were similar across different regions, the differences in their concentrations were significant and displayed clear regional characteristics. The fingerprint spectrum of GC-IMS, combined with PLS-DA analysis, indicates that eight distinctive volatile compounds, including ethyl butyrate, can be utilized to distinguish between different origins. Additionally, we analyzed the OVA value and sensory quantification of koumiss in different regions. We found that aroma components such as ethyl caprylate and ethyl caprate, which exhibit buttery and milky characteristics, were prominent in the YL and TC regions. In contrast, aroma components such as phenylethanol, which feature a floral fragrance, were more prominent in the ALTe region. The aroma profiles of koumiss from the four regions were defined. These studies provide theoretical guidance for the industrial production of Kazakh koumiss products.

Research progress of Traditional Chinese Medicine (TCM) in targeting inflammation and lipid metabolism disorder for arteriosclerosis intervention: A review

Atherosclerosis (AS) is a chronic disease caused by inflammation and lipid deposition. Immune cells are extensively activated in the lesions, producing excessive pro-inflammatory cytokines, which accompany the entire pathological process of AS. In addition, the accumulation of lipid-mediated lipoproteins under the arterial intima is a crucial event in the development of AS, leading to vascular inflammation. Improving lipid metabolism disorders and inhibiting inflammatory reactions are the primary treatment methods currently used in medical practice to delay AS progression. With the development of traditional Chinese medicine (TCM), more mechanisms of action of the monomer of TCM, Chinese patent medicine, and compound prescription have been studied and explored. Research has shown that some Chinese medicines can participate in treating AS by targeting and improving lipid metabolism disorders and inhibiting inflammatory reactions. This review explores the research on Chinese herbal monomers, compound Chinese medicines, and formulae that improve lipid metabolism disorders and inhibit inflammatory reactions to provide new supplements for treating AS.

Differentiation of Goat Meat Freshness Using Gas Chromatography with Ion Mobility Spectrometry

To investigate the flavor changes in goat meat upon storage, the volatile components observed in goat meat after different storage periods were determined using gas chromatography-ion mobility spectrometry (GC-IMS). A total of 38 volatile organic compounds (VOCs) were determined from the goat meat samples, including alcohols, ketones, aldehydes, esters, hydrocarbons, ethers, and amine compounds. 1-Hexanol, 3-Hydroxy-2-butanone, and Ethyl Acetate were the main volatile substances in fresh goat meat, and they rapidly decreased with increasing storage time and can be used as biomarkers for identifying fresh meat. When combined with the contents of total volatile basic-nitrogen (TVB-N) and the total numbers of bacterial colonies observed in physical and chemical experiments, the characteristic volatile components of fresh, sub-fresh, and spoiled meat were determined by principal component analysis (PCA). This method will help with the detection of fraudulent production dates in goat meat sales.

Analysis of the Volatile Flavor Compounds of Pomegranate Seeds at Different Processing Temperatures by GC-IMS

This study sought to reveal the mechanism of flavor generation when pomegranate seeds are processed, as well as the contribution of volatile organic components (VOCs) to flavor formation. Gas chromatography–ion mobility spectrometry (GC-IMS), combined with relative odor activity (ROAV) and statistical methods, was used for the analysis. The results showed that 54 compounds were identified from 70 peaks that appeared in the GC-IMS spectrum. Then, the ROAV results showed 17 key volatile components in processing pomegranate seeds, and 7 flavor components with large differential contributions were screened out using statistical methods. These included γ-butyrolactone, (E)-3-penten-2-one (dimer), pentanal, 1-propanethiol, octanal, and ethyl valerate (monomer). It is suggested that lipid oxidation and the Maillard reaction may be the main mechanisms of flavor formation during the processing of pomegranate seeds. Furthermore, this study lays the experimental and theoretical foundations for further research on the development of flavor products from pomegranate seeds.

Flavor components detection and discrimination of isomers in Huaguo tea using headspace-gas chromatography-ion mobility spectrometry and multivariate statistical analysis

Aroma components are one of the crucial factors in dynamic processes analysis, quality control, and origin traceability. Various categories of Huaguo Tea possessed different taste due to the generation of aroma. In this study, a comprehensive analysis of volatiles was conducted for five popular Huaguo Tea samples (Lemon Slices, Bitter Gourd Slices, Citri Reticulatae Pericarpium, Red Lycium Barbarum, and Black Lycium Barbarum) via gas chromatography-ion mobility spectrometry (GC-IMS) combining with multivariate statistical strategies. Comparison analysis was achieved with the properties of visually and intuitively by drawing of topography plots. A total of one hundred and eighty volatiles were distinguished. Aliphatic isomers were identified simultaneously by fingerprint spectra. Alcohols, aldehydes, esters, and ketones were the most abundant volatiles in Huaguo Tea samples. To characterize the Huaguo Tea precisely and establish an analysis model for their classification, multivariate statistical analysis was applied to distinguish different Huaguo Tea. Satisfied discrimination was obtained by principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) based on the HS-GC-IMS results with the robustness parameter (R²Y) of 99.4%, and prediction ability parameter (Q²) of 98.6%, respectively. The results provide a theoretical basis for aroma discrimination, isomer identification, and categories analysis of Huaguo Tea.

Drying of Chinese medicine residues (CMR) by hot air for potential utilization as renewable fuels: drying behaviors, effective moisture diffusivity, and pollutant emissions

High moisture in Chinese medicine residues (CMR) can decrease the energy efficiency of thermochemical conversion, which necessitates the pre-drying. Owing to the complex constituents and decoction, CMR may possess distinct drying characteristics. It is necessary to understand its drying behaviors, effective moisture diffusivity, and pollutant emissions for future design and optimization of an industrial-level dryer. In this study, the drying of four types of typical CMR in hot nitrogen was performed. Their condensate and exhaust gas were collected and characterized. The results indicated that their drying process was dominated by internal moisture transport mechanism with a long falling rate stage. Drying temperature influenced their drying process more greatly than N2 velocity did. Residual sum of squares, root mean square error, and coefficient of determination indicated that Weibull model demonstrated their drying process best. Their effective moisture diffusivity was in the range of 1.224 × 10-8 to 4.868 × 10-8 m2/s, while their drying activation energy ranged from 16.93 to 30.39 kJ/mol. The acidic condensate had high chemical oxygen demand and total nitrogen concentration and yet low total phosphorus concentration. The concentration of total volatile organic compounds, non-methane hydrocarbons, H2S, and NH3 in the exhaust gas met the national emission limitation, while the deodorization of exhaust gas was required to remove odor smell.

Supplementary information

The online version contains supplementary material available at 10.1007/s13399-022-03722-4.

Meat quality and flavor evaluation of Nanjing water boiled salted duck (NWSD) produced by different Muscovy duck (Cairina moschata) ingredients

Reports on meat quality and flavor evaluation of Nanjing water boiled salted duck (NWSD) produced by different Muscovy duck (Cairina moschata) ingredients are limited. To select a suitable Muscovy duck ingredient for the NWSD processing, six kinds of NWSD products were produced using female (65, 70, and 75 days) and male (75, 80, and 85 days) Muscovy duck ingredients. The meat quality, volatile organic compounds (VOCs), smell and taste were investigated by using colorimeter, texture analyzer, headspace-gas chromatography-ion mobility spectroscopy (HS-GC-IMS), electronic nose (E-nose), electronic tongue (E-tongue), etc. Results exhibited that 32 iconic VOCs were obtained by using partial least squares discrimination analysis (PLS-DA), principal component analysis (PCA), and variable importance projection (VIP) methods. 80-day-old male Muscovy duck showed moderate moisture and protein content, good meat texture and bright color, diverse iconic VOCs and clear differentiation, making it the preferred ingredient for NWSD processing.

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network

As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probability of invasive alien species. A major pathway for invasive alien species is agricultural quarantine materials (AQMs) in travelers' baggage. Thus, it is meaningful to develop efficient methods for early detection and prompt action against AQMs. In this study, a method based on the combination of odor detection of AQMs using ion mobility spectroscopy (IMS) and convolutional neural network (CNN) analysis for the identification of AQM species in luggage was developed. Two different ways were investigated to feed the IMS data of AQMs into the CNN, either as one-dimensional data (1D) (as a spectrum) or as two-dimensional data (2D) (as an IMS topographic map). The performances of CNN models were also compared to those of the commonly used classification algorithms: partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA). By doing gradient-weighted class activation mapping (Grad-CAM), the essential IMS feature regions from the CNN models to predict different AQM species were also identified. The results of this research demonstrated that the application of the CNN to the IMS data of AQMs yielded superior classification performance compared to PLS-DA and SIMCA. Especially, the CNN-2D model which utilized the IMS topographic map as input achieved the best classification accuracy both on the calibration and validation sets. In addition, the Grad-CAM method had an ability to detect critical discriminating spectral regions for different types of AQM samples, and could provide explanation for the CNNs' decision-making. Despite the inherent limitations of the present analytical protocol, the results showed that the method of IMS in combination with a CNN has great potential to be a complement for sniffer dogs and X-ray imaging techniques to detect AQMs.

The Discrimination and Characterization of Volatile Organic Compounds in Different Areas of Zanthoxylum bungeanum Pericarps and Leaves by HS-GC-IMS and HS-SPME-GC-MS

The pericarps of Zanthoxylum bungeanum (ZBP) and leaves of Zanthoxylum bungeanum (ZBL) are popular spices in China, and they have pharmacological activities as well. In this experiment, the volatile organic compounds (VOCs) of the pericarps of Zanthoxylum bungeanum in Sichuan (SJ) and its leaves (SJY) and the pericarps of Zanthoxylum bungeanum in Shaanxi (SHJ) and its leaves (SHJY) were analyzed by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). The fingerprint of HS-GC-IMS and the heat maps of HS-SPME-GC-MS were established. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed. The results showed that a total of 95 components were identified, 62 components identified by HS-SPME-GC-MS and 40 components identified by HS-GC-IMS, of which 7 were the same. The analysis found that SJ and SHJ were obviously distinguished, while SJY and SHJY were not. There were considerably fewer VOCs in the leaves than in the pericarps. In the characterization of the VOCs of ZBL and ZBP, the flavor of ZBP was more acrid and stronger, while the flavor of ZBL was lighter and slightly acrid. Thirteen and eleven differential markers were identified by HS-GC-IMS and HS-SPME-GC-MS, respectively. This is helpful in distinguishing between SHJ and SJ, which contributes to their quality evaluation.