Recent progress in food flavor analysis using gas chromatography–ion mobility spectrometry (GC–IMS)

Characterization and metabolism pathway of volatile compounds in blueberries of different varieties and origins analyzed via HS-GC-IMS and HS-SPME-GC-MS

This study comprehensively identified 10 blueberry varieties from 3 regions using headspace gas chromatography ion mobility spectrometry (HS-GC-IMS) and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). The former identified 70 volatile organic compounds, while the latter identified 618. The blueberry varieties, Bluecrop, Reka, and Northland in Northeast China have significant advantages in fresh and sweet flavors were found through HS-GC-IMS. HS-SPME-GC-MS found that terpenes, esters, and heterocyclic are the main volatile components in blueberry (47.09 %), with nine volatile organic metabolites (benzene, 1,3-dimethyl, etc.) serving as potential biomarkers for distinguishing blueberry varieties from the three regions. In addition, the top 10 aromatic compounds in different blueberry varieties were screened, among which 5-ethyl-3-hydroxy-4-methyl-2 (5H) - furanone had the highest rOAV value. These findings provide theoretical support for exploring the key flavor characteristics of different varieties of blueberries and effectively distinguishing blueberries from various production areas.

Instrumental developments in drift tube ion mobility spectrometry: A review on miniaturization, new manufacturing techniques, and pre-separation

Drift tube ion mobility spectrometry (DT-IMS) separates ions based on their mobility under weak electric fields and has undergone significant advancements since its introduction as an analytical instrument in 1970. Recent developments in DT-IMS focus on addressing limitations such as low resolving power and challenges in separating complex samples. High-resolution ion shutters, optimized drift tubes, and integrated chip-based pre-separation methods have greatly enhanced analytical performance. Miniaturization has been a key focus, driven by advanced manufacturing techniques and instrumental developments, which have improved portability, reduced costs, and enabled custom designs. Tandem DT-IMS systems further enhance selectivity and structural elucidation, offering expanded capabilities for complex analyses. These innovations have significantly advanced the functionality of DT-IMS, bridging the gap between simple, straightforward designs and high analytical performance. This review highlights the transformative impact of these instrumental developments, miniaturization, and novel manufacturing techniques, positioning DT-IMS as a versatile, high-performance analytical tool for modern workflows.

Revealing the flavor changes of spiced beef under different thermal treatment temperatures: A complementary approach with GC-IMS and GC-O-MS

The flavor profiles of spiced beef (SB) and the impact of thermal treatment temperature were analyzed using complementary GC-IMS and GC-O-MS techniques. The results indicated that spice, roasted-meaty, and caramel flavors significantly contributed to the SB profile. Thermal treatment degraded α-phellandrene, citral, γ-terpinene, and other terpenoids, reducing spice flavor intensity. However, milder thermal treatments at 80°C and 95°C lessened this degradation. Increasing temperatures promoted fat oxidation and degradation, Maillard reactions, and Strecker degradation of amino acids. Thus, appropriate thermal treatment enhanced compounds related to roasted-meaty flavor (e.g., 3-methylbutyraldehyde, 1-octen-3-ol) and caramel flavor (e.g., hydroxyacetone). However, intense thermal treatment at 110 °C caused excessive Maillard reactions that produced off-flavors like 2-methylthiophene and methyl disulfide. This study provides insights into flavor changes in spice meat products under different thermal treatment temperatures. It provides a practical foundation and a theoretical basis for the traditional processing and sterilization methods of SB.

Characterizing and decoding the dynamic alterations of volatile organic compounds and non-volatile metabolites of dark tea by solid-state fermentation with Penicillium polonicum based on GC-MS, GC-IMS, HPLC, E-nose and E-tongue

Penicillium species is a kind of core fungus involved in Fu brick tea (FBT) production. However, its specific effects on shaping the distinct flavor characteristics and non-volatiles of FBT remain unclear. In this study, Penicillium polonicum, isolated from FBT, was inoculated into primary dark tea for pure-culture fermentation, and investigated its effects on the volatile profile and non-volatile metabolites of dark tea. During fermentation, P. polonicum produced various hydrolytic enzymes, including β-glucosidase, polyphenol oxidase, peroxidase, and tannase, which greatly altered the non-volatile and volatile metabolites of dark tea. GC-MS and GC-IMS identified a total of 185 volatile organic compounds (VOCs), with alcohols (38), ketones (39), aldehydes (33) and hydrocarbons (19) being the most abundant. The changes in VOCs can be divided into three distinct stages. Key aroma compounds, such as (E)-β-Ionoine, (E)-β-damascenone and linalool were prominent in the early stages, while 2-methoxy-3-sec-butyl pyrazine, 2-isopropyl-3-methoxypyrazine, 3-isobutyl-2-methoxypyrazine, and linalool were prominent in the middle and late stages. The formation pathways of key VOCs were primarily involved in amino acids degradation, oxidative degradation of fatty acids, and glycosides degradation. After fermentation with P. polonicum, significant changes were observed in the constituents of catechins, free amino acids, and alkaloids in tea, resulting in an advance while decreased the astringency and bitterness of tea infusion. This research provides novel insight for of the formation of VOCs and non-volatile metabolites of dark tea by P. polonicum, offering important guidance for utilizing P. polonicum as a starter culture to stabilize and enhancing the quality of FBT during production.

Impact of processing methods in shaping taste, flavor, antioxidants, and metabolites in teas (Camellia sinensis): A multi-method analysis

This study systematically examined the effects of processing techniques on the flavor profiles and functional attributes of tea derived from fresh leaves (Camellia sinensis) of identical origin. Pu-erh raw tea (PRT), white tea (WT), and black tea (BT) were produced through distinct processing protocols (non-fermented, lightly fermented, and fully fermented, respectively). Antioxidant activity and sensory characteristics were evaluated alongside comprehensive metabolomic analyses using GC-IMS, GC-MS, and UHPLC-QTOF-MS. PRT exhibited superior antioxidant capacity with pronounced bitterness and astringency, whereas WT displayed fruity-sweet notes and BT demonstrated a mellow profile linked to fermentation. Metabolomic profiling identified six discriminative biomarkers and two pivotal compounds differentiating tea types, alongside six key metabolic pathways (e.g., secondary metabolite biosynthesis) driving compositional variations. These findings elucidate processing-induced biochemical transformations, offering insights for quality optimization and consumer-oriented tea selection.

Identification of Gas Mixture Components with Multichannel Hierarchical Analysis of Time-Resolved Hyperspectral Data

Chemical vapor sensors are essential for various fields, including medical diagnostics and environmental monitoring. Notably, the identification of components in unknown gas mixtures has great potential for noninvasive diagnosis of diseases such as lung cancer. However, current gas identification techniques, despite the development of electronic nose-based sensor platforms, still lack sufficient classification accuracy for mixed gases. In our previous study, we introduced multichannel hierarchical analysis using a time-resolved hyperspectral system to address the spectral ambiguity of conventional RGB sensor-based colorimetric e-noses. Here, we demonstrate the identification of mixed gas components through time-resolved line hyperspectral measurements with an eight-colorimetric sensor array that uses genetically engineered M13 bacteriophages as gas-selective colorimetric sensors. The time-dependent spectral variations induced by mixed gas in the different colorimetric sensors are converted into a hyperspectral three-dimensional (3D) data cube. For efficient machine learning classification, the data cube was converted into a multichannel spectrogram by applying a novel data processing method, including dimensionality reduction and a block average filter to reduce high-dimensional complexity and improve the signal-to-noise ratio. A convolution filter was then used for hierarchical analysis of the multichannel spectrogram, effectively capturing the complex gas-induced spectral patterns and temporal dynamics. Our study demonstrates a classification accuracy of 93.9% for pure and mixed gases of acetone, ethanol, and xylene at a low concentration of 2 ppm.

Comprehensive analysis of volatile flavor components in pear fruit spanning the entire development stages

The intricate pattern of flavor changes throughout the various stages of fruit development remains poorly understood. Here, we investigated the material dynamics underlying flavor formation, focusing on volatile and metabolite production across 8 fruit developmental and ripening stages of 'Yuluxiang' pear. A total of 154 volatile compounds were characterized by HS-GC-IMS combined with HS-SPME-GC-MS technology, mainly including aldehydes, ketones, and ester compounds in the young fruit and enlarging periods, and the ester compounds increase in the mature period. Notably, the expression of alcohol acetyltransferase gene in the fatty acid metabolism pathway significantly increased with ripening, thereby facilitating ester synthesis. Hexyl acetate was identified as a crucial marker for pear ripeness. Our findings provide a robust theoretical basis for regulating the synthesis and accumulation of these vital flavor compounds during the later stages of fruit development.

Accurate evaluation of the lipid characteristics and flavor of abdominal muscle resulting from different cooking processes using lipidomics and GC-IMS analysis

This study employed UPLC-MS/MS and GC-IMS techniques to compare and analyze the lipid metabolites and volatile flavor compounds in raw abdominal muscle (CK), sour video abdominal muscle (SV), steamed abdominal muscle (ST), and oven-cooked abdominal muscle (OC). A total of 42 subclasses and 1230 lipids were identified. Among these, lysophosphatidylethanolamine (LPE) 18:2/0:0, lysophosphatidylcholine (LPC) 18:2/0:0, and triacylglycerol (TG) 16:0_18:1_18:1 enhanced the aroma retention of steamed abdominal muscle, whereas phosphatidylcholine (PC) 16:0_18:2 and phosphatidylethanolamine (PE) P-18:18:18:2 influenced the aroma retention of roasted abdominal muscle. Additionally, 250 differentially abundant metabolites were identified as potential markers for differentiating various cooking methods. Seven compounds were recognized as potential indicators for distinguishing cooking methods: propanal-D, n-pentanal-M, n-pentanal D, butanal-D, 3-methylbutanal, 1-hexanal-M, and 1-hexanal D. Correlation analysis results indicated a significant positive correlation between aldehydes and phospholipid molecules, including PC, PE, LPC, and LPE.

Characterization and Discrimination of Volatile Compounds of Donkey and Horse Meat Based on Gas Chromatography-Ion Mobility Spectrometry

The production of high-quality specialty meats has emerged as a prominent research focus within the livestock industry, under the broader concept of big food. However, the composition and variances of volatile compounds (VOCs) in donkey meat (DM) and horse meat (HM) remain unclear, which complicates their effective identification. In the present study, the VOCs of DM and HM were analyzed using gas chromatography-ion mobility spectrometry (GC-IMS) in combination with a multivariate analysis. Our results indicate that a total of 39 VOCs were identified in both DM and HM. These VOCs were categorized into five groups: aldehydes (39.53%), ketones (28.89%), alcohols (28.89%), acids (6.98%), and furans (2.33%). Compared with HM, the concentration of aldehydes, ketones, and alcohols in DM is significantly higher. (p < 0.001). Additionally, 16 characteristic-flavor VOCs were identified in both types of meat, with notable compounds including oct-1-en-3-ol, 3-hexanone, and heptanol. Topography, fingerprinting, and multivariate analysis effectively differentiated the VOC profiles of DM and HM. Furthermore, the 28 differential VOCs identified in DM and HM were all significantly higher in DM than in HM. In summary, this study conducted a comprehensive analysis of the VOC composition and characteristic flavor compounds in DM and HM, highlighting key differential VOCs. These findings contribute valuable data for flavor regulation and offer technical support for detecting the adulteration of DM with HM. The difference in sensory quality between DM and HM needs further research.

The scent of time: Analyzing the differences in volatile organic compounds of camellia oleifera oil with different oil-tea tree ages using GC-IMS and GC-MS

Camellia oleifera oil (CO) is renowned in China for its exceptional nutritional benefits and distinctive aroma. The aroma of old CO from oil-tea tree ages over 30 years differs markedly from that of young CO aged below 8 years. However, the volatile organic compounds (VOCs) and aroma characteristics of CO from oil-tea tree at different ages remain unclear. This study identified 82 VOCs using GC-IMS and 112 VOCs using GC-MS. PCA, PLS-DA, correlation analysis, and VIP values revealed distinct VOC profiles between CO obtained from young and old oil-tea tree. The principal characteristic VOCs of CO from young oil-tea tree (4 and 8 years) were 3-methyl-3-buten-1-ol (sweet fruit) and 3-methylbutyl propanoate (apple, apricot, and pineapple). Moreover, the predominant characteristic VOCs of CO from old oil-tea tree (30, 40, and 50 years) were 4-methyl-2-pentanol (pungent), butyl acetate (apple and banana), limonene (lemon and orange), and 2-ethyl-6-methylpyrazine (green, nuts, and roasted).

Gas chromatography-ion mobility spectrometry-based fingerprint analysis of volatile flavor compounds in ginger cultivated under different conditions

Ginger is widely acclaimed for its pungent aroma, nutritional benefits, and unique pharmacological properties, making it essential in culinary and medicinal applications. This study investigates volatile flavor profile differences in ginger resulting from various cultivation practices. Gas chromatography-ion mobility spectrometry (GC-IMS) was utilized to isolate and identify volatile compounds. Subsequent analyses, including relative odor activity values (ROAV) and multivariate statistical analysis, precisely identified key flavor compounds differentiating organically cultivated ginger from conventional field-grown varieties. A total of fifty-six volatile compounds were identified, comprising 17 esters, 4 alcohols, 7 ketones, 18 terpenoids, 6 aldehydes, and 4 miscellaneous compounds, with esters and terpenoids constituting over 50 % of total volatiles. Compounds such as α-phellandrene, β-citronellal, butyl 2-propenoate, 2-heptanone-D, and 3-octanone predominantly contributed lemon, banana, and citronella notes in organically cultivated ginger. In contrast, citral dominated in conventional ginger. This research significantly advances our understanding of ginger's aroma under varied cultivation conditions and demonstrates GC-IMS's utility in effectively profiling ginger flavor, thereby guiding improved cultivation and management.

Characterization of Key Aroma Compounds in Dongpo Pork Dish and Their Dynamic Changes During Storage

The objective of this study was to identify the key aroma compounds of Dongpo pork dish (DPD) and to explore the changes in key aroma compounds of DPD during the storage period. Quantitative descriptive analysis (QDA) combined with two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) was employed to investigate the aroma characteristics and the volatile profiles of DPD. Further, a sensomic approach was used to decipher its key aroma compounds. The typical flavors identified in DPD were described as meat, grease, garlic, wine, soy sauce, and spice flavors by the QDA. The key aroma compounds contributing to the flavor of DPD include 2-heptanol, 1-octen-3-ol, hexanal, (E)-2-octenal, 3-methylthiopropanal, decanal, ethyl caproate, 2,5-dimethylpyrazine, and dimethyl trisulfide. In addition, the changes of key aroma compounds of DPD at different storage temperatures (25 °C, 4 °C) were explored, and the results demonstrated that the key aroma compounds showed an overall trend of attenuation with the increase in time. The content of ethyl caproate decayed by more than 60%. Compared with the storage temperature of 25 °C, DPD storage at 4 °C was more effective in slowing down the change of key aroma compounds. These results can provide theoretical evidence for the flavor modulation and the industrial production of DPD.

Aroma Release and Consumer Perception During Cider Consumption

Flavor is an important property affecting consumer acceptance, yet little is known about the correlation between the sensory attributes, volatile compounds, and consumer preference during cider consumption. This study was the first to evaluate which sensory attributes of commercial apple ciders in China were preferred by Chinese consumers. Meanwhile, GC-MS and GC-IMS were conducted to characterize the aroma release both in orthonasal and retronasal olfactory perceptions. The sensory analyses exhibited that Chinese consumers preferred "sweet cider", and sensory attributes such as "a-tropical fruit", "f-fruity" and "t-sweet" were the most popular. A total of 63 volatile compounds were identified using GC-MS, while both the variety and concentrations of these compounds detected by GC-IMS were lower. Finally, partial least squares (PLS) analysis was used to establish two models based on sensory data, and orthonasal and retronasal volatile compounds. The two models had 32 and 29 compounds with variable importance in projection (VIP) values > 1, respectively. The results revealed that the compounds with high correlation with "t-sweet" and "f-fruity" were roughly the same in two PLS models, whereas the number of compounds contributing positively to "t-sour" and "f-fermented" changed significantly.

Insight into the mechanism of Maillard reaction and lipids mutually contribute to the flavor release of squid fillets during the drying process

Dried squid fillet is a popular seafood product with a unique flavor. However, its flavor release mechanism is unclear. In this study, volatile compounds (VOCs) were dynamically monitored in thawed squid (TS), salted squid (SS) and dried squid for 6 h (D6) and 24 h (D24). Subsequently, the Maillard reaction (MR) substrate, lipid oxidation index, free fatty acids and lipid profiles were detected. The results showed that the number of VOCs increased from 11 in TS (114.26 μg/kg) to 19 in D24 (1257.89 μg/kg). Besides, MR between glucose/ribose and amino acids (methionine, arginine, etc.) contributed to 3-methyl-butanal, methional and 2,3-butanedione. Meanwhile, lipid oxidation index, lipidomics and correlation analysis indicated that lipids (phosphatidylcholines and triglycerides) containing polyunsaturated fatty acids (C18:2, C20:4, C20:5 and C22:6) were precursors of 3-methyl-butanal, nonanal, heptanal, dodecane and tetradecane. Briefly, lipid hydrolysis, oxidation and MR mutually contributed to the flavor during the drying process of squid fillets.

Effect of cooking conditions on sea urchin dumplings

The objective of this study was to investigate the changes in flavour and taste of sea urchin dumplings subjected to different cooking methods, utilising gas chromatography-ion mobility spectrometry (GC-IMS), electronic tongue (E-tongue) analysis, free amino acid content assessment and sensory evaluation. The GC-IMS technique successfully detected 69 volatile compounds in the skin and 60 volatile compounds in the filling of the boiled dumplings. From the established fingerprints, it was found that there were significant differences in the flavour compounds of dumplings skins among the groups. 1-Octen-3-ol, 2-methylpropanal, ethyl acetate monomer, methyl 2-methylbutyrate and 2-pentylfuran were found in the skins of dumplings cooked in different ways and were positively correlated with freshness in the E-tongue, and were also positively correlated with aspartic acid and glutamic acid. Sensory evaluations revealed significant differences in dumplings under different cooking methods. The results can provide data support and theoretical reference for the processing of dumplings.

Comprehensive Characterization of Aroma Profile of "Glutinous Rice" Flavor in Pandanus amaryllifolius Roxb. Using HS-SPME-GC-O-MS and HS-GC-IMS Technology Coupled with OAV

Pandan leaves have a prominent glutinous-rice aroma; however, few studies have explored their volatile aroma compound composition. Herein, the differences in the volatile aroma components of fresh and dried pandan leaves were investigated for the first time using HS-SPME-GC-O-MS combined with principal component analysis, orthogonal partial least squares discriminant analysis, and HS-GC-IMS with aroma fingerprinting. A total of 93 volatile compounds were identified, exceeding previous reports, including 43 main flavor components with odor activity values (OAV) > 1. OAV and aroma extract dilution analysis tests reveal 13 main aroma volatiles including 2-acetyl-1-pyrroline, hexanal, nonanal, phenylacetaldehyde, β-cyclocitral, butanal, ethyl caprylate, ethyl nonanoate, ethyl caprate, ethyl laurate, 3-hydroxy-2-butanone, acetophenone, and α-ionone. Sixteen types of aromas were classified, and the results are presented as flavor wheels. The findings of this study elucidate the changes and retention of aroma volatiles in differently processed leaves, which could benefit food industry applications.

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.

Unraveling the generation mechanism of volatile compounds in intermittent microwave-dried anchovies via HS-GC-IMS and MMSE-GC-MS

The mechanism of aroma formation in anchovies via various intermittent microwave drying counts were revealed by the associated variations of flavor precursors compounds and volatile compounds. Variations in the structure of flavor precursors were compared with multidimensional infrared spectroscopy (MM-IR), revealing that the structure of fatty acid compounds exhibited notable transformations via different drying counts. Anchovies via different drying counts presented similar fatty acid and volatile compound compositions, whereas greater discrepancies were observed in the concentration. There are 127 and 45 volatile compounds identified by monolithic material sorptive extraction gas chromatography-mass spectrometry (MMSE-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), respectively. Two-dimensional network modeling revealed strong positive correlations between C16:0, C21:0, C17:1, C18:2n6c, C18:3n6, and C22:1n9 with straight-chain aldehydes, aromatic aldehydes, and aromatic compounds. This study systematically revealed the correlation between fatty acids and volatile compounds in anchovies at different intermittent drying counts, and provided theoretical underpinnings for the application of dried anchovy products in industry.

Application of gas chromatography-ion mobility spectrometry in tea (Camellia sinensis): A comprehensive review

Gas chromatography-ion mobility spectrometry (GC-IMS) technology boasts several salient features, including fast detection, portability, simple sample preparation, and nondestructive detection, making it a highly appealing tool in tea research. By harnessing its prowess in detecting and analyzing volatile compounds present in tea, GC-IMS has found numerous applications within the broad realm of tea studies. These applications encompass discerning geographical origins, analyzing aroma profiles, classifying tea grades, distinguishing harvest seasons, monitoring aroma variations during processing, and storage, differentiating tea varieties and categories. In the current study, the development history and performance characteristics of GC-IMS technology are presented. Furthermore, the relevant research studies of the application of GC-IMS in tea field are summarized, highlighting its practical applications and impacts. Additionally, the promotion strategies and improvement methods for enhancing of GC-IMS in the qualitative analysis of volatile compounds are put forward. Looking ahead, the potential avenues for the application of GC-IMS in tea quality control, online monitoring of tea manufacturing, detection of tea adulteration, and tea storage environment management are proposed. The versatility and precision of GC-IMS make it a promising technology that can to some extent change the tea industry's understanding and assurance of product quality.

Fruit wines classification enabled by combing machine learning with comprehensive volatiles profiles of GC-TOF/MS and GC-IMS

Fruit wines, produced through the fermentation of various fruits, are well-documented for their distinct flavor profiles. Intelligent sensory analysis, GC-TOF/MS and GC-IMS were used for the analysis of the volatile profile of eight types of fruit wines including 5 grape wine (SJ, LS, HY, TJ, FT), 1 fermented plum wine (FZ), 1 blueberry wine (HZ), as well as 1 configured plum wine (LM). A total of 281 compounds were identified through GC-TOF/MS, with esters and acids constituting over 80% of all samples. GC-IMS identified 60 compounds, predominantly including 16 esters, 11 alcohols, and 6 ketones, and 7 sulfur-containing compounds. This observation leads to the assumption that the IMS and MS data contain different information about the composition of the volatile profile. 37 and 18 differential compounds for TOF/MS data and IMS data were obtained, respectively. Three ranking algorithms combined with five machine learning models Neural Networks (NN), Random Forests (RF), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR) applied and identified both 58 key features from volatiles. LR and KNN achieved an overall classification of 0.95 and an F1 score greater than 0.9. For the IMS data, NN, LR, and KNN models exhibited accuracies and F1 scores greater than 0.9. This study advances fruit wine classification, benefiting the beverage industry and food chemistry research.

Influence of Different Shaping Techniques on the Aroma Quality and Volatile Metabolites of Green Tea Revealed by Gas Chromatography Electronic Nose and Gas Chromatography-Tandem Mass Spectrometry

The shaping process is recognized as a crucial step in the manufacturing of green tea. However, its influence on aroma quality remains unclear. In this study, the effects of four shaping techniques, including flat green tea (FGT), straight green tea (SGT), phoenix green tea (PGT), and curled green tea (CGT), on the aroma quality and volatile metabolites of green tea were investigated by gas chromatography electronic nose (GC-E-Nose) and gas chromatography-tandem mass spectrometry (GC-MS/MS). The findings indicated that distinct shaping processes significantly influenced the development of the aroma quality and aroma components of green tea. The PGT processing facilitated the attainment of superior aroma quality of green tea. In total, 60 volatile components were identified by GC-MS/MS, with 54 of these compounds being consistently detected across four different shaping techniques. In particular, the PGT processing method was effective in yielding elevated levels of alcohols, esters and ketones. Moreover, 20 key odorants were screened out, with (E,E)-2,4-decadienal, (E,E)-2,4-nonadienal, phenylethyl alcohol, and benzeneacetaldehyde proven to be substantial contributors to the overall aromas of green tea under diverse shaping procedures. These key odorants were primarily derived from lipid degradation and the Maillard reaction. GC-E-Nose served as a significant adjunct to sensory evaluation, enabling the swift differentiation of green tea samples that have undergone various shaping processes. These findings offer both theoretical and technical perspectives that may guide the creation of innovative green tea products distinguished by their unique shapes.

Analysis of volatile compounds and vintage discrimination of raw Pu-erh tea based on GC-IMS and GC-MS combined with data fusion

Storage duration significantly influences the aroma profile of raw Pu-erh tea. To comprehensively investigate the differences in the volatile compounds across various vintages of raw Pu-erh teas and achieve the rapid classification of tea vintages, volatile compounds of raw Pu-erh tea with different years (2020-2023) were analyzed using a combination of gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography-mass spectrometry (GC-MS). The datasets obtained from both techniques were integrated through low-level and mid-level data fusion strategies. Additionally, partial least squares discriminant analysis (PLS-DA) and random forest (RF) machine learning algorithms were applied to develop predictive models for the classification of tea storage durations. Consequently, GC-IMS and GC-MS identified 54 and 76 volatile compounds, respectively. Notably, the RF model, particularly when coupled with mid-level data fusion, exhibited exceptional predictive accuracy for tea storage time, reaching an accuracy of 100%. These findings provide a reference for elucidating the aroma characteristics of raw Pu-erh tea of different vintages and demonstrate that data fusion combined with machine learning has great potential for ensuring food quality.

New Method of Direct Sampling Gas Chromatography-Ion Mobility Spectrometry to Identify the Dynamic Retronasal Volatile Compounds in the Alcoholic Beverage and Their Release Behaviors: A Case Study on Huangjiu

Owing to extremely low concentrations and dynamic changes, it is difficult to detect and trace the retronasal volatile organic compounds (VOCs) generated during the consumption of alcoholic beverages. We developed a direct sampling gas chromatography-ion mobility spectrometry (GC-IMS) method to identify the dynamic VOCs after drinking Huangjiu-a fermented alcoholic beverages. The optimal procedure was obtained: take a sip of 10 mL Huangjiu, holding it in mouth for 10 s and then swallow, and the VOCs in one nasal expiration were collected with gas sampling bag and transferred directly to the injection port of GC-IMS. The repeatability was satisfactory (RSD < 5%). Twenty-two VOCs were detected in Huangjiu, with esters and alcohols being dominant, which were divided into five distinct release behavior groups. Their release was found significantly inhibited by saliva. Overall, this new method offers a technical approach to understanding and assessing the characteristics of retronasal aroma in alcoholic beverages.

Shrimp lipids improve flavor by regulating characteristic aroma compounds in hot air-dried shrimp

Hot air-dried shrimp (HDS) has a strong fishy smell greatly reducing its flavor quality. This study aimed to investigate the regulation of total lipids, phospholipids and triglycerides isolated from shrimp for improving the characteristic volatile flavor of HDS. It was found that three lipids could promote the formation of aroma compounds with pleasant characteristic aromas (e.g., pyrazines). Phospholipids and triglycerides inhibited the formation of trimethylamine, a key component of fishy smell, with phospholipids exhibiting the best inhibitory effect (47.70 ± 2.63 %), greatly improving the flavor quality of HDS. Aldehydes, unsaturated ketones, and furans, primarily derived from the thermal degradation of C18:1, C18:2, and C22:6, were key intermediate compounds promoting the Maillard reaction. Lipids inhibited trimethylamine by prompting the formation of pyrazines. Maillard reaction was the key pathway for lipids to improve the flavor quality of HDS. This study can provide theoretical support for the development of high-quality thermally processed shrimp products.

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.

Effects of sterilization intensity on the flavor profile of canned Antarctic krill (Euphausia superba): Moderate vs. excessive

Selecting the appropriate sterilization intensity is crucial for the canning of Antarctic krill (Euphausia superba). This study investigated the effects of different sterilization intensities on volatile organic compounds (VOCs) of canned krill. Using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography-mass spectrometry (GC-MS), which identified 45 and 36 VOCs, respectively. As the sterilization intensity was increased, the flavor profile became more stabilized; however, excessive sterilization led to the generation of off-flavor compounds. Eight key flavor markers were identified at different sterilization intensities. Cluster analysis could distinguish between samples obtained from low (F = 6, 9) and high (F = 12, 15) sterilization intensities. Odor Activity Value (OAV) analysis revealed that higher sterilization intensities led to the generation of fishy, fatty, and earthy notes. The findings suggest that sterilization at F = 9 can best maintain the desired flavor characteristics. Overall, this work provides valuable insights into the optimization of the canning process of Antarctic krill.

Insights Into the Composition and Antibacterial Activity of Different Parts of Alpinia katsumadai Hayata Based on HS-SPME-GC-MS and HS-GC-IMS

RATIONALE

The volatile organic compounds (VOCs) of Alpinia katsumadai Hayata (AKH) play a key role in determining its effects such as organoleptic properties, medicinal properties, and consumer preferences. The nonmedicinal parts (roots, fibrous roots, stems, leaves, and shells) in AKH are also rich in VOCs and different degrees of antibacterial activity. Therefore, it is important to comprehensively characterize the VOCs in different parts of AKH and learn about their potential antimicrobial abilities.

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 used to comprehensively investigate the compositional characteristics and differences of roots, fibrous roots, stems, leaves, shells, and seeds in AKH. Multivariate statistical analysis was used to determine the differential VOCs in different parts of AKH. The inhibition zone diameter method was used to compare the antibacterial ability of different parts.

RESULTS

HS-GC-IMS and HS-SPME-GC-MS analyses identified 67 and 125 VOCs, respectively. Multivariate statistical analysis showed the differences in the six parts is obvious. Compounds such as (E)-2-heptenal and thymol were selected as potential VOCs to distinguish six sites of AKH. In general, the inhibition effect of the volatile oils from shell and root on the two colonies was better, and the volatile oils of the four parts of AKH have better inhibitory effect on Staphylococcus aureus.

CONCLUSION

This research conducted a comprehensive analysis of the fundamental volatile components in AKH. It subsequently elucidated the distinctions and specificities in different parts. The antibacterial effect of volatile oil in different parts was further compared, which was conducive to finding alternative parts for seeds in some active aspects, and the utilization of AKH was more sufficient.

Comparison of flavor components between normal and gas-producing wasabi based on HS-GC-IMS, HS-GC-MS and electronic sensory technology

Wasabi is a type of sauce made from the plant horseradish. During its production and storage, gas production sometimes occurs, which leads to changes in the flavor quality of wasabi. In this study, an electronic nose, electronic tongue, headspace-gas chromatography-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry combined with multivariate statistical analysis were used to compare the differences in odor, taste and volatile components between normal and gas-producing wasabi. The results showed that normal and gas-producing wasabi samples could be distinguished by the electronic nose and electronic tongue. Furthermore, 72 and 65 volatile components were identified from wasabi by headspace-gas chromatography-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry analysis, respectively. In addition, 33 key volatile components that caused the difference between normal and gas-producing wasabi were identified through variable projection importance index analysis. Therefore, normal and gas-producing wasabi could be effectively distinguished and their differences in odor, taste and volatile components could be clarified by the four flavor analysis techniques combined with multivariate statistical analysis, which provide a scientific basis for the quality control and process optimization of wasabi.

Analyzing the effect of different storage times and different processes on the volatile components in Shenling Baizhu powder by HS-GC-IMS combined with multivariate statistics

AIM

this study aimed to examine the effect of different storage times (0, 7, 24, 57, and 119 days) on the volatile components of Shenling Baizhu powder across different preparation processes (Pharmacopoeia, ultra-micro pulverization-pulverization, and microparticle design methods). The findings offer insights to guide quality control measures for Shenling Baizhu powder.

METHODS

gas chromatography-ion mobility spectrometry (GC-IMS) was employed to ascertain the volatile components in Shenling Baizhu powder at various storage times across different preparation processes. In addition, the study compared the dynamic changes of these components under different conditions. Principal component analysis (PCA) and orthogonal partial least-squares discrimination analysis (OPLS-DA) were conducted using SIMCA-P19.0 software to analyze differences among these volatile components.

RESULTS

the volatile components identified by GC-IMS comprised 52 monomers and dimers and polymers of some substances, primarily including aldehydes, esters, terpenes, nitrogenous compounds, and ketones. Fingerprint spectra revealed significant differences in the types and quantities of volatile components in Shenling Baizhu powder at different storage times under different processes. PCA indicated negligible differences in the types of volatile components among samples prepared using different processes. An OPLS-DA model was developed to distinguish storage times and identify characteristic markers. In addition, 22 volatile components with variable importance for the projection (VIP) > 1 were identified, significantly contributing to the discrimination of storage times for Shenling Baizhu powder. Overall, the content of volatile components in the samples gradually decreased with prolonged storage time. Samples prepared using the Pharmacopoeia method exhibited the most significant decline, whereas those prepared using the microparticle design method showed the least reduction in volatile components.

CONCLUSION

HS-GC-IMS effectively captures the changing trends of volatile components in Shenling Baizhu powder across different preparation processes and storage times. This analysis provides a reference for quality control and process optimization in the production of Shenling Baizhu powder.

Characterization changes of volatile organic compounds in Aconitum sinomontanum Nakai (Gao Wu Tou) with different proportions of yellow wine steamed by GC-IMS, E-nose

Gas chromatography-ion mobility spectrometry (GC-IMS) combined with multiple analytical methods and E-nose were used to study the differences in volatile organic compounds (VOCs) in 0 %, 10 %, 15 %, 20 %, 25 % yellow wine steamed A. sinomontanum and its raw products. The results indicated that the VOCs in different proportions of yellow wine steamed A. sinomontanum and its raw products were mainly composed of aldehydes, ketones, alcohols, ethers, esters, acids, and heterocycles. Among them, the contents of the aldehydes, ketones, heterocycles, alcohols and esters are remarkably higher than those of other compounds. The results based on multiple analysis methods such as PCA and fingerprint analysis showed that there were certain differences between steaming A. sinomontanum with different proportions of yellow wine and the raw products. Among them, yellow wine has a 15 % proportion and the highest content of VOCs, and perhaps the best proportion of yellow wine for steaming A. sinomontanum. Simultaneously, it is speculated that the unique odor of steamed A. sinomontanum may be related to the aldehydes and esters it contains, such as benzalde-hyde, 2-Methylbutanol acetate. In addition, the E-nose results of this study could be helpful for flavor identification and distinction of raw and processed products from A. sinomontanum.

Characterization of Fusarium venenatum Mycoprotein-Based Harbin Red Sausages

Fusarium venenatum mycoprotein is an alternative, nutritious protein source with a meat-like texture. Here, F. venenatum mycoprotein-based Harbin red sausage was developed and characterized. The study focused on the effect of mycoprotein on the quality of red sausages, which were evaluated in five groups of red sausages based on nutrient content, differential scanning calorimetry (DSC), and gas chromatography-ion mobility spectrometry (GC-IMS). The results showed that increasing the component of mycoprotein in red sausage increased the protein and volatile organic compound content but decreased the water and ash content. There was no significant difference (p > 0.05) between red sausage with 25% added mycoprotein and traditional red sausage in terms of redness and thawed water component, but the protein component was higher, the flavor substances were slightly richer, and the consumer preference was higher. These results suggest that moderate amounts of mycoprotein can improve nutritional value and maintain sensory quality, but that higher levels of substitution can adversely affect preference. This study highlights the potential of mycoprotein as an artificial meat that can strike a balance between improved nutritional value and sensory acceptability.

Quality identification of Amomi fructus using E-nose, HS-GC-IMS, and intelligent data fusion methods

Amomi fructus (AF) has been used for both medicinal and food purposes for centuries. However, issues such as source mixing, substandard quality, and product adulteration often affect its efficacy. This study used E-nose (EN) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to determine and analyze the volatile organic compounds (VOCs) in AF and its counterfeit products. A total of 111 VOCs were detected by HS-GC-IMS, with 101 tentatively identified. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) identified 47 VOCs as differential markers for distinguishing authentic AF from counterfeits (VIP value >1 and P < 0.05). Based on the E-nose sensor response value and the peak volumes of the 111 VOCs, the unguided Principal Component Analysis (PCA), guided Principal Component Analysis-Discriminant Analysis (PCA-DA), and Partial Least Squares-Discriminant Analysis (PLS-DA) models were established to differentiate AF by authenticity, origin, and provenance. The authenticity identification model achieved 100.00% accuracy after PCA analysis, while the origin identification model and the provenance identification model were 95.65% (HS-GC-IMS: PLS-DA) and 98.18% (HS-GC-IMS: PCA-DA/PLS-DA), respectively. Further data-level fusion of E-nose and HS-GC-IMS significantly improved the accuracy of the origin identification model to 97.96% (PLS-DA), outperforming single-source data modeling. In conclusion, the intelligent data fusion algorithm based on E-nose and HS-GC-IMS data effectively identifies the authenticity, origin, and provenance of AF, providing a rapid and accurate method for quality evaluation.

Investigation on the Effect of Three Different Nonthermal Sterilization Methods on Volatile Organic Compounds in Safflower Using HS-GC-IMS

During the transportation, storage, and processing of safflower, it is susceptible to contamination by microorganisms, which may seriously affect the quality and safety of the flowers. Therefore, sterilization is an important step in ensuring the safety, quality, and stability of safflower products. In this study, headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) was utilized to compare the volatile organic compounds (VOCs) in safflower samples before and after sterilization with three nonthermal sterilization technologies (60Co irradiation sterilization, ultraviolet sterilization, and ozone sterilization). A total of 70 VOCs were detected in all of the safflower samples. According to the two-dimensional and three-dimensional difference contrast spectra and the fingerprint results of HS-GC-IMS, the VOCs in the safflower samples processed with the three nonthermal sterilization methods varied. By conducting principal component analysis (PCA), cluster analysis (CA), and partial least-squares regression analysis (PLS-DA) on the VOCs, it was found that 3-methyl-2-butenal, 2-heptanone, and 4-methyl-2-pentanone were the main contributors to the differences between the groups. HH-01 (not sterilized) differed significantly from HH-03 (UV sterilized) and HH-04(ozone sterilized) and differed the least from HH-02(60Co irradiation sterilized), suggesting that 60Co irradiation sterilized had the least effect on the VOCs of safflower. Therefore, 60Co irradiation technology is recommended to sterilize safflowers in large-scale production. This study provides a scientific basis for future large-scale sterilization processing of high-quality safflower. The results of this study demonstrate that HS-GC-IMS can provide strong technical support for the identification and authenticity assessment of VOCs in safflower samples.

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.

Dynamic evolution of volatile compounds during cold storage of sturgeon fillets analyzed by gas chromatography-ion mobility spectrometry and chemometric methods

This study investigated the changes in quality and volatile flavoring compounds in sturgeon fillets during refrigeration. Potential flavor compounds were identified using orthogonal partial least squares discriminant analysis (OPLS-DA) and gas chromatography- ion mobility spectrometry (GC-IMS). The results showed that TVB-N content, TBARS values, total colony counts, and K-value increased with prolonged refrigeration, reaching spoilage thresholds after approximately eight days. A total of 33 volatile compounds (including monomers and dimers) were detected in sturgeon fillets during different refrigeration periods, including aldehydes, alcohols, ketones, acids, esters, ethers, and other compounds. OPLS-DA further revealed flavor differences in sturgeon fillets across different refrigeration stages, identifying 18 distinct volatile compounds. Correlation analysis showed that trans-2-Pentenal, 2-methylpropanal, and glutaraldehyde were associated with pleasant odor to the frozen sturgeon fillets in the early stage, while hexane nitrile and thiazole were the main substances that caused unpleasant odors.

Tailoring Super-Performed Chemo-Sensor via Simulation-Modeling and MEMS-Screening

Chemo-sensor designing involves a time-consuming trial-and-error screening process, which commonly cannot lead to optimal S4R features (Sensitivity, Selectivity, Speed, Stability, and Reversibility). Due to strong path dependence on reported groups/mechanisms, conventional chemo-sensors often fail to meet critical application demands, especially in achieving high reversibility without compromising other features. Here, a three-step screen and design strategy is developed for gaining customized chemo-sensors, through Structure modeling; MEMS (Micro Electro Mechanical Systems) analysis, and Performance verification. With such a strategy, the coordination hanging anion mechanism is screened out for reversible nerve agent detection and shows reversible emission enhancement by 25.8 times with DCP, ultrasensitive vapor phase detection (5.7 ppb), and rapid response(10 s) and recovery speed (20 s). Such tailored designing strategy for new organic chemo-sensors will probably play an important role in developing high-performance sensing system in the future.

Volatile and non-volatile compound analysis of ginkgo chicken soup during cooking using a combi oven

This study employed a range of analytical techniques to evaluate the changes in both volatile and non-volatile compounds during different cooking times (30, 60, 90, 120, and 150 min) of ginkgo chicken soup prepared using a multifunctional combi oven, and comparedthese results with those obtained from the traditional ceramic pot method.The techniques included electronic nose (e-nose), electronic tongue (e-tongue), gas chromatography-ion mobility spectrometry (GC-IMS), high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and automated amino acid analysis. A total of 64 volatile compounds, primarily aldehydes, ketones, esters, and alcohols, were detected, with 23 key aroma components identified. Principal component analysis (PCA) demonstrated similar aroma and taste profiles between the two cooking methods. Additionally, 22 amino acids, 6 nucleotides enhancing umami, and 18 fatty acids were categorized into saturated, monounsaturated, and polyunsaturated groups. Pearson correlation revealed significant relationships among key amino acids, 5'-nucleotides, and volatile compounds, providing insights into industrial-scale applications of multifunctional ovens in ginkgo chicken soup production.

Enhancing cider quality through co-fermentation with acid protease and esterase-producing Metschnikowia species and Saccharomyces cerevisiae

BACKGROUND

To date, cider production has primarily relied on Saccharomyces cerevisiae. Introducing novel non-Saccharomyces yeasts can enhance the diversity of cider properties. Among these, the Metschnikowia genus stands out for its ability to produce hydrolytic enzymes that may impact the sensorial and technological properties of cider. This study focused on evaluating the impact of three Metschnikowia species - Metschnikowia koreensis (Mk), M. reukaufii (Mr), and M. pulcherrima (Mp) - which exhibit acid protease and esterase activity, on the quality enhancement of cider.

RESULTS

The research findings indicate that the overall quality of cider produced through co-fermentation with these species surpassed that of cider fermented with mono-fermentation of S. cerevisiae (Sc). The cider fermented with the Sc + Mk combination exhibited the lowest levels of harsh-tasting malic acid and higher levels of softer lactic acid. Sensory array analysis also demonstrated that the Sc + Mk fermented cider exhibited high sensor response values for compounds contributing to a complex overall olfactory composition and richness. Furthermore, the Sc + Mk fermented cider exhibited the highest total quantity and variety of volatile organic compounds (VOCs). Specifically, the concentrations of phenethyl alcohol, 3-methyl-1-butanol, ethyl octanoate, and decanoic acid were notably elevated in comparison with other groups.

CONCLUSION

This study illustrates that Metschnikowia species, particularly M. koreensis, show significant potential as starters for cider due to their various technological properties, including acidity modulation, aroma enhancement, and color improvement. The findings of this study provide a foundation for improving cider quality by co-fermenting S. cerevisiae with innovative starter cultures. © 2024 Society of Chemical Industry.

Comparison of Volatile and Non-Volatile Compounds of Ice-Stored Large Yellow Croaker (Larimichthys crocea) Affected by Different Post-Harvest Handling Methods

To compare the impact of different post-harvest handling methods on volatile and non-volatile compounds, a total of 54 live large yellow croakers were subjected to commercial slaughter (CS), spinal cord cutting (SCC), or spinal cord cutting and bleeding (SCCB). The fish samples were ice-stored for 72 h, followed by the analysis of volatile compounds using gas chromatography-ion mobility spectrometry and non-volatile compounds using LC-MS-based untargeted metabolomics. The results revealed the detection of a total of 28 volatile organic compounds, with 23 being successfully identified, predominantly including alcohols, aldehydes, esters, ketones, and heterocyclic compounds. Substances such as (E)-2-nonenal and 2-butanone are highly sensitive to post-harvest handling methods during ice storage. Furthermore, 943 non-volatile metabolites were identified, showing significant differences in 180, 100, 117, and 186 metabolites across comparisons of SCC 0 h/CS 0 h, SCCB 0 h/CS 0 h, SCC 72 h/CS 72 h, and SCCB 72 h/CS 72 h, respectively. Notably, the altered metabolic pathways mainly involved fatty acid and amino acid metabolism, including pathways like glycerophospholipid metabolism and arginine biosynthesis. This study revealed the potential mechanisms underlying the enhancement of fish quality through spinal cord cutting and bleeding.

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.

Recent Advances in the Mechanisms of Quality Degradation and Control Technologies for Peanut Butter: A Literature Review

As the quality of life continues to improve globally, there is an increasing demand for nutritious and high-quality food products. Peanut butter, a widely consumed and nutritionally valuable product, must meet stringent quality standards and exhibit excellent stability to satisfy consumer expectations and maintain its competitive position in the market. However, its high fat content, particularly unsaturated fatty acids, makes it highly susceptible to quality deterioration during storage. Key issues such as fat separation, lipid oxidation, and rancidity can significantly compromise its texture, flavor, and aroma, while also reducing its shelf life. Understanding the underlying mechanisms that drive these processes is essential for developing effective preservation strategies. This understanding not only aids food scientists and industry professionals in improving product quality but also enables health-conscious consumers to make informed decisions regarding the selection and storage of peanut butter. Recent research has focused on elucidating the mechanisms responsible for the quality deterioration of peanut butter, with particular attention to the intermolecular interactions among its key components. Current regulatory techniques aimed at improving peanut butter quality encompass raw material selection, advancements in processing technologies, and the incorporation of food additives. Among these innovations, plant protein nanoparticles have garnered significant attention as a promising class of green emulsifiers. These nanoparticles have demonstrated potential for stabilizing peanut butter emulsions, thereby mitigating fat separation and oxidation while aligning with the growing demand for environmentally friendly food production. Despite these advances, challenges remain in optimizing the stability and emulsifying efficiency of plant protein nanoparticles to ensure the long-term quality and stability of peanut butter. Future research should focus on improving the structural properties and functional performance of these nanoparticles to enhance their practical application as emulsifiers. Such efforts could provide valuable theoretical and practical insights into the development of stable, high-quality peanut butter, ultimately advancing the field of food science and technology.

Temperature-dependent metabolic interactions between Streptococcus thermophilus and Lactobacillus delbrueckii ssp. bulgaricus in milk fermentation: Insights from gas chromatography-ion mobility spectrometry metabolomics

Streptococcus (S.) thermophilus and Lactobacillus (L.) delbrueckii ssp. bulgaricus are widely used as a combined starter culture for milk fermentation, often at temperatures of 37°C and 42°C. To investigate the metabolic interplay between these 2 species during the fermentation process, this study examined the growth and fermentation characteristics of different S. thermophilus strains cocultured with L. delbrueckii ssp. bulgaricus ND02 at these 2 temperature conditions. Gas chromatography-ion mobility spectrometry metabolomics was employed to analyze changes in the milk metabolome during 3 key fermentation stages: initiation (F0, pH 6.50 ± 0.02), curdling (F1, pH 5.20 ± 0.02), and endpoint (F2, pH 4.50 ± 0.02). The results showed that 42°C fermentation promoted rapid bacterial growth, with significantly reduced fermentation time compared with 37°C. Interestingly, 37°C fermentation favored the enrichment of volatile fatty acids like 2-methylpropanoic acid, 3-methylbutanoic acid, and ethyl acetate. In contrast, 42°C fermentation led to increased levels of ketones such as acetone, 2-hexanone, 2-pentanone, and 2-heptanone. Sensory evaluation indicated that the 42°C fermented milk had higher overall scores. Discriminatory flavor metabolites were more abundant during the later fermentation stage (F1 to F2), while the underlying metabolic pathways became increasingly active. These findings provide insights into the dynamic changes in volatile metabolite profiles of fermented milk produced under different temperature and time conditions using varied starter culture combinations. The results are valuable for optimizing dairy fermentation processes and product quality.

Differentiation and characterization of volatile compounds in five common milk powders using HS-GC-IMS, HS-SPME-GC-MS, and multivariate statistical approaches

Aroma is a key factor in milk powder quality evaluation and consumer choice. However, research has mostly focused on processing effects, with little on flavor differences among milk powders. This study analysed and identified the flavor characteristics of five common types of milk powders in China, including yak milk powder, donkey milk powder, camel milk powder, goat milk powder, and cow milk powder, using Headspace-Gas Chromatography-Ion Mobility Spectrometry (HS-GC-IMS), Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS), and multivariate statistical analysis. Results identified 55 and 86 volatile compounds via HS-GC-IMS and HS-SPME-GC-MS, respectively, revealing significant differences between milk powders. PCA, OPLS-DA, PLS-DA, and heatmaps further distinguished the sources. Based on VIP values, 27 and 24 key compounds were identified. These results underscored the potential of utilizing these combined techniques for quick flavor analysis and detecting adulteration in milk powder.

Effects of enhanced fermentation with high-yielding strains of Tetramethylpyrazine on flavor quality of Douchiba

Douchiba (DCB) is a nutritious food rich in various functional components such as Tetramethylpyrazine (TTMP), and the strain fermentation is crucial for enhancing its quality. This work utilized Bacillus subtilis S2-2 and Hyphopichia burtonii S6-J1 with high TTMP production for fermentation of soybeans to optimize the pre-fermentation process and to evaluate the flavor quality of mature DCB. The concentration of TTMP in DCB fermented by mixed microbial (MG) was 2.95 times higher than that of of the control. Furthermore, the concentrations of taste substances, organic acids, free amino acids, and free fatty acids in MG were significantly increased. 87 flavor compounds were detected by gas chromatography-ion mobility spectrometry. The content of aldehydes, alcohols, esters, acids, and pyrazines flavor compounds was higher in MG, with esters and alcohols being notably higher than in other groups. Additionally, the highest comprehensive score of flavor quality was obtained in MG by principal component analysis.

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.

An overview on olfaction in the biological, analytical, computational, and machine learning fields

Recently, the comprehension of odor perception has advanced, unveiling the mysteries of the molecular receptors within the nasal passages and the intricate mechanisms governing signal transmission between these receptors, the olfactory bulb, and the brain. This review provides a comprehensive panorama of odors, encompassing various topics ranging from the structural and molecular underpinnings of odorous substances to the physiological intricacies of olfactory perception. It extends to elucidate the analytical methods used for their identification and explores the frontiers of computational methodologies.

A strategy to distinguish similar traditional Chinese medicines by liquid chromatography-mass spectrometry, electronic senses, and gas chromatography-ion mobility spectrometry: Marsdeniae tenacissimae Caulis and Paederiae scandens Caulis as examples

INTRODUCTION

Marsdeniae tenacissimae Caulis (MTC), a popular traditional Chinese medicine, has been widely used in the treatment of tumor diseases. Paederiae scandens Caulis (PSC), which is similar in appearance to MTC, is a common counterfeit product. It is difficult for traditional methods to effectively distinguish between MTC and PSC. Therefore, there is an urgent need for a rapid and accurate method to identify MTC and PSC.

OBJECTIVES

The aim is to distinguish between MTC and PSC by analyzing the differences in nonvolatile organic compounds (NVOCs), taste, odor, and volatile organic compounds (VOCs).

METHODS

Liquid chromatography-mass spectrometry (LC-MS) was utilized to analyze the NVOCs of MTC and PSC. Electronic tongue (E-tongue) and electronic nose (E-nose) were used to analyze their taste and odor respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) was applied to analyze VOCs. Finally, multivariate statistical analyses were conducted to further investigate the differences between MTC and PSC, including principal component analysis, orthogonal partial least squares discriminant analysis, discriminant factor analysis, and soft independent modeling of class analysis.

RESULTS

The results of this study indicate that the integrated strategy of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis can be effectively applied to distinguish between MTC and PSC. Using LC-MS, 25 NVOCs were identified in MTC, while 18 NVOCs were identified in PSC. The major compounds in MTC are steroids, while the major compounds in PSC are iridoid glycosides. Similarly, the distinct taste difference between MTC and PSC was precisely revealed by the E-tongue. Specifically, the pronounced bitterness in PSC was proven to stem from iridoid glycosides, whereas the bitterness evident in MTC was intimately tied to steroids. The E-nose detected eight odor components in MTC and six in PSC, respectively. The subsequent statistical analysis uncovered notable differences in their odor profiles. GC-IMS provided a visual representation of the differences in VOCs between MTC and PSC. The results indicated a relatively high relative content of 82 VOCs in MTC, contrasted with 32 VOCs exhibiting a similarly high relative content in PSC.

CONCLUSION

In this study, for the first time, the combined use of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis has proven to be an effective method for distinguishing between MTC and PSC from multiple perspectives. This approach provides a valuable reference for the identification of other visually similar traditional Chinese medicines.

Analysis of volatile compounds in Xiangjiao baijiu from different storage containers and years based on HS-GC-IMS and DI-GC-MS

The volatile compounds in 16 different storage containers and years of Xiangjiao Baijiu (XJBJ) were compared and analyzed via direct injection (DI) combined with gas chromatography-mass spectrometry (GC-MS) and headspace extraction (HS) coupled with gas chromatography-ion mobility spectrometry (HS-GC-IMS) for the first time. Through HS-GC-IMS analysis, it was found that the succession rules of 14 compounds such as furfural during aging process. A total of 60 compounds were identified using DI-GC-MS. Twenty-five of these compounds were further quantified, and 19 compounds had odor activity values (OAVs) > 1, which were important contributor to aroma of XJBJ. Among them, those with OAVs >1000 included ethyl hexanoate, ethyl octanoate, ethyl butanoate, and ethyl pentanoate. Combining the results of quantitative, OAVs and partial least squares-discriminant analysis (PLS-DA) revealed that 10 compounds such as ethyl octanoate were the important compounds that lead to the differences between different storage types of XJBJ.

Comparison of different drying technologies for green tea: Changes in color, non-volatile and volatile compounds

Drying technology plays a pivotal role in tea processing. Herein, the differences in color, non-volatile, and volatile components of green tea under various drying methods were investigated. The results indicated that vacuum freeze-microwave increased the L* and b* values, and decreased the a* values of tea leaves. Moreover, vacuum freeze-microwave drying resulted in higher polyphenol content than the other three drying methods although there was no significant difference. A total of 43 volatile compounds were identified. Of these, 2-propanone, ethanol(D), ethanol(M), ethyl acetate(M), 2-methyl-1-butanol, and 2-methylthiophene were found to play an important role in the above discrimination (VIP >1.5). Dry extraction showed a higher content of volatile components than wet extraction. Regardless of the extraction conditions, vacuum freeze-microwave drying exhibited a stronger signal intensity and more volatile components than other drying methods. This study provides a reference for analyzing the quality differences of green tea by different drying methods.