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

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.

Discrimination and Characterization of the Volatile Organic Compounds in Schizonepetae Spica from Six Regions of China Using HS-GC-IMS and HS-SPME-GC-MS

Volatile organic compounds (VOCs) are the main chemical components of Schizonepetae Spica (SS), which have positive effects on the quality evaluation of SS. In this study, HS-SPME-GC-MS (headspace solid-phase microextraction-gas chromatography-mass spectrometry) and HS-GC-IMS (headspace-gas chromatography-ion mobility spectrometry) were performed to characterize the VOCs of SS from six different regions. A total of 82 VOCs were identified. In addition, this work compared the suitability of two instruments to distinguish SS from different habitats. The regional classification using orthogonal partial least squares discriminant analysis (OPLS-DA) shows that the HS-GC-IMS method can classify samples better than the HS-SPME-GC-MS. This study provided a reference method for identification of the SS from different origins.

Correlation between the redox activity of Polygonum multiflorum extract and its extraction technology with Chinese liquor (Baijiu): An electrochemistry-based study

Elucidating the pharmaceutical mechanisms behind traditional Chinese medicine (TCM) is the key to promote its modernization process. In China, soaking TCM in liquor has a history of thousands of years, and many TCMs have to be processed into liquor before they can be used to treat diseases. Chinese liquor (Baijiu) contains more than 2,000 trace components, the interaction mechanism between TCM and Baijiu still remains unclear, making TCM a "mystery". The TCM industry commonly employs chromatographic and spectrographic technology to investigate the redox activity of TCM substances. However, only investigating the redox differences in specific active substances cannot provide a complete understanding of the redox activity of TCM substances. Thus, we employed the electrochemical approach to study the overall redox activity of substances in TCM in situ. The key result is that the redox substances in Baijiu function as a mediator for the redox reaction of Polygonum multiflorum extract. The redox efficiency of the extract is enhanced because of the faster electron transferability of the redox mediator in Baijiu.

A global systematic review on the concentration of organophosphate esters in water resources: Meta-analysis, and probabilistic risk assessment

Organophosphate esters (OPEs) are used as additives in various industries. They do not chemically bond with the polymeric structure of materials, so they can stay for a long time and have a very adverse effect on the environment. To analyze the development of the prevalence and concentration of OPEs such as TCEP, TCPP, TDCP, TnBP, TPHP, TBOEP, TEHP, TMP, TCIPP, TDCIPP, TMPP, and TDBPP in water resources, a search between January 01, 2000, to April 08, 2021, was followed by a systematic review and meta-analysis. Among of the 888 articles scanned in the identity step, 58 articles containing 2676 samples, 10 countries, and 4 water types were included in the meta-analysis study. Among all studied OPEs, the concentration of TcrP, TCPP, TDCPP, and TnBP were at the top in water resources, with values >715 μg L^-1 and lowest average concentrations were obtained for TDBPP and TpeP with values <0.0004 μg L^-1. The most polluted area in terms of the concentration of OPEs in water resources was China. Besides, data analysis showed that there only was carcinogenic risk for China. A Monte-Carlo simulation indicated that although these obtained averages are in the same order of magnitude as the acceptable limit, for both adults and children, 95% of the population is at risk.

Characterisation of Flavour Attributes in Egg White Protein Using HS-GC-IMS Combined with E-Nose and E-Tongue: Effect of High-Voltage Cold Plasma Treatment Time

Egg white protein (EWP) is susceptible to denaturation and coagulation when exposed to high temperatures, adversely affecting its flavour, thereby influencing consumers' decisions. Here, we employ high-voltage cold plasma (HVCP) as a novel nonthermal technique to investigate its influence on the EWP's flavour attributes using E-nose, E-tongue, and headspace gas-chromatography-ion-mobilisation spectrometry (HS-GC-IMS) due to their rapidness and high sensitivity in identifying flavour fingerprints in foods. The EWP was investigated at 0, 60, 120, 180, 240, and 300 s of HVCP treatment time. The results revealed that HVCP significantly influences the odour and taste attributes of the EWP across all treatments, with a more significant influence at 60 and 120 s of HVCP treatment. Principal component analyses of the E-nose and E-tongue clearly distinguish the odour and taste sensors' responses. The HS-GC-IMS analysis identified 65 volatile compounds across the treatments. The volatile compounds' concentrations increased as the HVCP treatment time was increased from 0 to 300 s. The significant compounds contributing to EWP characterisation include heptanal, ethylbenzene, ethanol, acetic acid, nonanal, heptacosane, 5-octadecanal, decanal, p-xylene, and octanal. Thus, this study shows that HVCP could be utilised to modify and improve the EWP flavour attributes.

The selectivity of a polydimethylsiloxane-based triblock copolymer as the stationary phase for capillary gas chromatography

A triblock copolymer (PCL-PDMS-PCL) constructed from polydimethylsiloxane (PDMS) and poly(ε-caprolactone) (PCL) chains was synthesized and used as the stationary phase for capillary gas chromatography (GC).