Ion mobility spectrometry coupled to gas chromatography: A rapid tool to assess eggs freshness

Continuous monitoring of temperature and freshness in cold chain transport based on the dual-responsive fluorescent hydrogel

Comprehensive attention should be paid to the potential food spoilage in food transport. However, there is a problem of freshness destruction by repeated freezing and thawing during the cold chain transport. Herein, a fluorescent hydrogel with N-doped green-emitting carbon dots (N-GCDs), bovine serum albumin-gold nanoclusters (BSA-AuNCs) as fluorescent probes and polyvinyl alcohol-sodium alginate hydrogel as carrier matrix was developed to continuously detect temperature and freshness. Due to the solvatochromic effect of N-GCDs, when the temperature surpassed the threshold, the mixture of water and dimethyl sulfoxide underwent a phase transition and melted into the gel, changing the fluorescence color to realize the temperature monitoring. Then, due to the pH effect of BSA-AuNCs, the gel could respond to pH changes in food deterioration to monitor the food freshness. Thus, the changes of both fluorescence color and intensity of the hydrogel provides a new method for visual and portable authenticity of food freshness.

Effects of Lentilactobacillus buchneri and Kazachstania bulderi on the Quality and Flavor of Guizhou Fermented Red Sour Soup

In this study, the effects of Lentilactobacillus buchneri (L. buchneri: CCTCC M 2023228) and Kazachstania bulderi (K. bulderi: CCTCC M 2023227) on the quality characteristics and volatile flavor substances in fermented red sour soup were explored based on natural fermentation. Compared to natural fermentation (nitrite: 5.5 mg/kg; amino acid nitrogen: 0.17 g/100 g; lycopene: 63.73 µg/mL), three fortified fermentation methods using L. buchneri, K. bulderi, and both strains together significantly reduced the concentrations of nitrite (2.62, 2.49, and 2.37 mg/kg), amino acid nitrogen (0.03 g/100 g, 0.02 g/100 g, and 0.05 g/100 g), and lycopene (26.64, 32.45, and 51.89 µg/mL). Total acid content (11.53 g/kg) and lactic acid bacteria count (285.9 ± 1.65 × 106 CFU/mL) were the elements most significantly increased by fortified fermentation with L. buchneri relative to other fermentation methods. A total of 99 volatile compounds were determined in red sour soup and could be roughly classified into alcohols, aldehydes, ketones, and esters. Fortified fermentation with two strains and fortified fermentation with K. bulderi increased the content of methyl butanoate and 3-hydroxybutan-2-one-acetoin (D). This study confirmed the effects of L. buchneri and K. bulderi on the quality and flavor of fermented red sour soup and provided a theoretical basis for the fortified fermentation of red sour soup.

Untargeted metabolomics liquid chromatography-high resolution mass spectrometry approach for the geographical origin assessment of Italian dehydrated apples

Geographical provenience is nowadays a relevant aspect of the authenticity and the quality of many food commodities. Dehydrated apple cubes/slices represent an ingredient commonly used by food companies for bakery products. However, this apple-based matrix is not so known and studied from an analytical point of view. In the present work, seven compounds were identified as key molecules to distinguish between Italian and non-Italian samples, through an untargeted ultrahigh-pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) approach. This methodology was merged with multivariate statistical analysis, and the principal features were studied and identified considering several identification steps. Samples from 2020 and 2021 harvesting campaigns, with partial and total dehydration rates, with or without peel, and from different apple varieties were considered for the study, for a total of 91 samples. Afterward, the same analysis protocol was applied to an external set (n = 12 samples), included in the statistical models, searching for the key compounds identified in the training set. Interesting and significant results underlined the potentiality of the UHPLC-HRMS technology as a confirmatory strategy for the geographical origin assessment of dehydrated apple commodities.

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

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

Recent Advance of Intelligent Packaging Aided by Artificial Intelligence for Monitoring Food Freshness

Food safety is a pressing concern for human society, as it directly impacts people's lives, while food freshness serves as one of the most crucial indicators in ensuring food safety. There exist diverse techniques for monitoring food freshness, among which intelligent packaging based on artificial intelligence technology boasts the advantages of low cost, high efficiency, fast speed and wide applicability; however, it is currently underutilized. By analyzing the current research status of intelligent packaging both domestically and internationally, this paper provides a clear classification of intelligent packaging technology. Additionally, it outlines the advantages and disadvantages of using intelligent packaging technology for food freshness detection methods, while summarizing the latest research progress in applying artificial intelligence-based technologies to food freshness detection through intelligent packaging. Finally, the author points out the limitations of the current research, and anticipates future developments in artificial intelligence technology for assisting freshness detection in intelligent packaging. This will provide valuable insights for the future development of intelligent packaging in the field of food freshness detection.

Nondestructive Detection of Egg Freshness Based on Infrared Thermal Imaging

In this paper, we proposed a nondestructive detection method for egg freshness based on infrared thermal imaging technology. We studied the relationship between egg thermal infrared images (different shell colors and cleanliness levels) and egg freshness under heating conditions. Firstly, we established a finite element model of egg heat conduction to study the optimal heat excitation temperature and time. The relationship between the thermal infrared images of eggs after thermal excitation and egg freshness was further studied. Eight values of the center coordinates and radius of the egg circular edge as well as the long axis, short axis, and eccentric angle of the egg air cell were used as the characteristic parameters for egg freshness detection. After that, four egg freshness detection models, including decision tree, naive Bayes, k-nearest neighbors, and random forest, were constructed, with detection accuracies of 81.82%, 86.03%, 87.16%, and 92.32%, respectively. Finally, we introduced SegNet neural network image segmentation technology to segment the egg thermal infrared images. The SVM egg freshness detection model was established based on the eigenvalues extracted after segmentation. The test results showed that the accuracy of SegNet image segmentation was 98.87%, and the accuracy of egg freshness detection was 94.52%. The results also showed that infrared thermography combined with deep learning algorithms could detect egg freshness with an accuracy of over 94%, providing a new method and technical basis for online detection of egg freshness on industrial assembly lines.

Identifying Early-Stage Changes in Volatile Organic Compounds of Ceratocystis fimbriata Ellis & Halsted-Infected Sweet Potatoes (Ipomoea batatas L. Lam) Using Headspace Gas Chromatography-Ion Mobility Spectrometry

Ceratocystis fimbriata Ellis & Halsted is the pathogen causing black rot in sweet potatoes that can lead to flavor change and toxin release. This study detected the volatile organic compounds (VOCs) of C. fimbriata-infected sweet potatoes in the early stages using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS). A total of 55 VOCs were identified, including aldehydes, alcohols, esters, ketones, and others. The content of aldehydes and ketones showed a decreasing trend, while alcohols and esters showed an increasing trend. An increase in infection time elevated the content of malondialdehyde (MDA) and pyruvate, while the starch content decreased, the content of soluble protein initially increased, then decreased, and the activities of lipoxygenase (LOX), pyruvate decarboxylase (PDC), alcohol dehydrogenase (ADH), and phenylalanine ammonia-lyase (PAL) increased. The changes in VOCs were closely related to the content of MDA, starch, pyruvate, and the activities of LOX, PDC, ADH, and PAL. Sweet potatoes showed a good discrimination effect by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) from 0 to 72 h. Twenty-five differential VOCs could be used as early-stage characteristic compounds of C. fimbriata-infected sweet potatoes for early disease monitoring.

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

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

Monitoring alkyl pyrazines in roasted hazelnuts by SHS-GC-IMS: IMS response assessment and standardization

Gas chromatography coupled with ion mobility spectrometry (IMS) is an analytical tool which is rapidly becoming widespread in the analysis of food volatiles. Despite this increasing popularity, an assessment of the IMS response for several flavor compound classes is not yet available. This study focuses on alkyl pyrazines and their determination in roasted hazelnut pastes. These Maillard reaction products are crucial to determine the aromatic profile of roasted foods and are suitable markers for industrial roasting monitoring. The instrumental response of 8 alkyl pyrazines was studied using a model matrix and a matrix matching approach. The results showed a relevant effect of the pyrazine ring substitution pattern on the concentration-response curve trends, highlighting that an external standardization of the IMS response is required to make possible relative abundance comparisons between analytes. A response standardization was therefore developed and applied to determine alkyl pyrazines in samples with different roasting intensity and geographical and botanical origin.

Further Interpretation of the Volatile, Microbial Community and Edible Quality of Fresh Fermented Rice Noodles with Different Selected Strains

Understanding bacteria and yeasts can reduce unpredictable changes in fresh fermented rice noodles (FFRN). The effects of selected strains (Limosilactobacillus fermentum, Lactoplantibacillus plantarum, Lactococcus lactis and Saccharomyces cerevisiae) on the edible quality, microbial community, and volatile component of FFRN were studied. The results indicated that the fermentation time could be shortened to 12 h when Limosilactobacillus fermentum, Lactoplantibacillus plantarum, and Lactococcus lactis were added, whereas it still required approximately 42 h after adding Saccharomyces cerevisiae. Only a steady bacterial composition was provided by adding Limosilactobacillus fermentum, Lactoplantibacillus plantarum, and Lactococcus lactis, and only a steady fungal composition was provided by adding Saccharomyces cerevisiae. Therefore, these microbial results indicated that the selected single strains cannot improve the safety of FFRN. However, the cooking loss was decreased from 3.11 ± 0.11 to 2.66 ± 0.13 and the hardness of FFRN was increased from 1186 ± 178 to 1980 ± 207 when it was fermented with single strains. Finally, a total of 42 volatile components were determined by Gas chromatography-ion Mobility Spectrometry and 8 aldehydes, 2 ketones, and 1 alcohol were added during the entire fermentation process. The main volatile components were different during fermentation depending on the added strain, and there was the greatest variety of volatiles in the group with added Saccharomyces cerevisiae.

Eggshell biometrics for individual egg identification based on convolutional neural networks

Individual egg identification technology has potential applications in breeding, product tracking/tracing, and anti-counterfeit. This study developed a novel method for individual egg identification based on eggshell images. A convolutional neural network-based model, named Eggshell Biometric Identification (EBI) model, was proposed and evaluated. The main workflow included eggshell biometric feature extraction, egg information registration, and egg identification. The image dataset of individual eggshell was collected from the blunt-end region of 770 chicken eggs using an image acquisition platform. The ResNeXt network was then trained as a texture feature extraction module to obtain sufficient eggshell texture features. The EBI model was applied to a test set of 1,540 images. The testing results showed that when an appropriate Euclidean distance threshold for classification was set (17.18), the correct recognition rate and the equal error rate reached 99.96% and 0.02%. This new method provides an efficient and accurate solution for individual chicken egg identification, and can be extended to eggs of other poultry species for product tracking/tracing and anti-counterfeit.

Review of extraction and detection techniques for the analysis of pesticide residues in fruits to evaluate food safety and make legislative decisions: Challenges and anticipations

Fruits are vital parts of the human diet because they include necessary nutrients that the body needs. Pesticide use has increased dramatically in recent years to combat fruit pests across the world. Pesticide usage during production, on the other hand, frequently results in undesirable residues in fruits after harvest. Consumers are concerned about pesticide residues since most of the fruits are directly consumed and even recommended for the patients as dietary supplements. As a result of this worry, pesticide residues in fruits are being randomly monitored to re-assess the food safety situation and make informed legislative decisions. To assess the degree of pesticide residues in fruits, a simple and quick analytical procedure is usually required. As a result, pesticide residue detection (using various analytical techniques: GC, LC and Biosensors) becomes critical, and regulatory directives are formed to regulate their amounts via the Maximum Residue Limit (MRL). Over the previous two decades, a variety of extraction techniques and analytical methodologies for xenobiotic's efficient extraction, identification, confirmation and quantification have been developed, ranging from traditional to advanced. The goal of this review is to give readers an overview of the evolution of numerous extraction and detection methods for pesticide residue analysis in fruits. The objective is to assist analysts in better understanding how the ever-changing regulatory landscape might drive the need for new analytical methodologies to be developed in order to comply with current standards and safeguard consumers.

Roasting treatments affect oil extraction rate, fatty acids, oxidative stability, antioxidant activity, and flavor of walnut oil

Introduction

The quality of pressed walnut oil can be improved by moderate roasting treatment.

Methods

This study compared physicochemical characteristics and antioxidant ability of walnut oils pressed from differently roasted pretreated walnuts, analyzed the correlation among these indicators by using Pearson correlation coefficient and correlation coefficient heatmap, and evaluated the volatile organic compounds (VOCs) of walnut oil under optimal pretreatment roasting conditions using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS).

Results

Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were able to remarkably distinguish walnut oil produced by different roasting processes. In addition, correlation analysis showed that there was a significant impact among indicators. There were 73 VOCs were identified in the optimum roasted treated walnut oil, consisting of 30 aldehydes, 13 alcohols, 11 ketones, 10 esters, 5 acids, 2 oxygen-containing heterocycles, 1 nitrogen-containing heterocycle and 1 other compound. GC-IMS results showed that aldehydes contributed significantly to the volatile flavor profile of walnut oil, especially (E)-2-heptenal, (E)-2-pentenal and hexenal.

Discussion

The properties of walnut oil based on varying roasting pretreatment of walnut kernels were significantly differentiated. Roasting at 120°C for 20 min is a suitable pretreatment roasting condition for pressing walnut oil. Roasting at 120°C for 20 min is a suitable pretreatment roasting condition for pressing walnut oil.

Comparison of aroma active compounds in cold- and hot-pressed walnut oil by comprehensive two-dimensional gas chromatography-olfactory-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry

Aroma composition of cold-pressed walnut oil (CWO) and hot-pressed walnut oil (HWO) was analyzed by comprehensive two-dimensional gas chromatography-olfactory-mass spectrometry (GC × GC-O-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). A total of 83 and 197 compounds were identified in the CWO and HWO, respectively; among these, 76 and 123 compounds were sniffed exclusively by GC × GC-O-MS, respectively. A total of 36 volatile compounds were detected by HS-GC-IMS, of which 10 in CWO and 32 in HWO. Based on of flavor dilution (FD) factors, odor-activity values (OAVs), and recombination and omission experiments, 1-octen-3-ol, cyclohexanol, and benzaldehyde were found to be the key aroma-active compounds in CWO, while 3-methylbutanal, (E,E)-2,4-nonadienal, nonanal, 1-octen-3-ol, 3-pentanol, 1-octanol, and furfural were the key aroma-active compounds in HWO. Moreover, Maillard reaction and lipid oxidation were found to play an important role in flavor formation in HWO. This study provides a guide to improve the quality of walnut oil based on aroma characteristics.

Potential volatile markers of brown rice infested by the rice weevil, Sitophilus oryzae (L.) (Coleoptera: Curculionidae)

The rice weevil, Sitophilus oryzae (L.) (Coleoptera: Curculionidae) could cause significant grain loss by feeding internally on seeds. In this study, we tried to analyze the volatile compounds in non-infested and S. oryzae-infested brown rice during different storage periods to identify potential markers in S. oryzae-infested brown rice and facilitate pest monitoring during brown rice storage. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) were used to identify the volatile compounds. On the basis of GC-MS and GC-IMS data, a reliable method to distinguish between non-infested and S. oryzae-infested brown rice was discovered using partial least squares-discriminant analysis (PLS-DA). 1-Octen-3-ol, 1-hexanol and 3-octanone were co-selected as potential markers because their variable importance in projection (VIP) was greater than 1 in both models. The current study's findings lay a foundation for further research on the brown rice infestation mechanism and safe storage monitoring.

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.

Application progress of intelligent flavor sensing system in the production process of fermented foods based on the flavor properties

Fermented foods are sensitive to the production conditions because of microbial and enzymatic activities, which requires intelligent flavor sensing system (IFSS) to monitor and optimize the production process based on the flavor properties. As the simulation system of human olfaction and gustation, IFSS has been widely used in the field of food with the characteristics of nondestructive, pollution-free, and real-time detection. This paper reviews the application of IFSS in the control of fermentation, ripening, and shelf life, and the potential in the identification of quality differences and flavor-producing microbes in fermented foods. The survey found that electronic nose (tongue) is suitable to monitor fermentation process and identify food authenticity in real time based on the changes of flavor profile. Gas chromatography-ion mobility spectrometry and nuclear magnetic resonance technology can be used to analyze the flavor metabolism of fermented foods at various production stages and explore the correlation between flavor substances and microorganisms.

Untargeted rapid differentiation and targeted growth tracking of fungal contamination in rice grains based on headspace-gas chromatography-ion mobility spectrometry

BACKGROUND

Milled rice are prone to be contaminated with spoilage or toxigenic fungi during storage, which may pose a real threat to human health. Most traditional methods require long periods of time for enumeration and quantification. However, headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology could characterize the complex volatile organic compounds (VOCs) released from samples in a non-destructive and environmentally friendly manner. Thus, this study described an innovative HS-GC-IMS strategy for analyzing VOC profiles to detect fungal contamination in milled rice.

RESULTS

A total of 24 typical target compounds were identified. Analysis of variance-partial least squares regression (APLSR) showed significant correlations between the target compounds and colony counts of fungi. While the changes of selected volatile components (acetic acid, 3-hydroxy-2-butanone and oct-en-3-ol) in fungi-inoculated rice had sufficiently high positive correlations with the colony counts, the logistic model could effectively be used to monitor the growth of individual fungus (R²  = 0.902-0.980). PLSR could effectively be used to predict fungal colony counts in rice samples (R²  = 0.831-0.953), and the different fungi-inoculated rice samples at 24 h could be successfully distinguished by support vector machine (SVM) (94.6%). The ability of HS-GC-IMS to monitor fungal infection would help to prevent contaminated rice grains from entering the food chain.

CONCLUSIONS

This result indicated that HS-GC-IMS three-dimensional fingerprints may be appropriate for the early detection of fungal infection in rice grains. © 2021 Society of Chemical Industry.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

Evaluation of Mutton Quality Characteristics of Dongxiang Tribute Sheep Based on Membership Function and Gas Chromatography and Ion Mobility Spectrometry

Dongxiang tribute sheep have a history of use in food dishes such as "Dongxiang Handgrip," which dates back hundreds of years and is a favorite halal food in northwestern China. However, little is known about the mutton quality characteristics of Dongxiang tribute sheep. Here, we measured the sensory characteristics, nutritional quality, and flavor substances to comprehensively evaluate the mutton quality characteristics of these sheep. The mutton qualities of Dongxiang tribute, Tibetan, Ujumqin, and Hu sheep were comprehensively evaluated by membership function. Subsequently, the volatile components in mutton samples from 30 Dongxiang tribute sheep were detected via gas chromatography and ion mobility spectrometry (GC-IMS), and their fingerprints were established. The result of meat quality revealed that the shear force, the contents of protein, essential amino acid (EAA), non-essential amino acid (NEAA), and n-6/n-3 ratio of Dongxiang tribute mutton were better than the other three breeds. Membership functions were calculated for 10 physical and chemical indexes of mutton quality, and the comprehensive membership function values of the four breeds in order of highest to lowest mutton quality were Tibetan sheep (0.76) > Dongxiang tribute sheep (0.49) > Hu sheep (0.46) > Ujumqin sheep (0.33). Thirty volatile compounds were identified via GC-IMS: seven alcohols, eight aldehydes, five ketones, two esters, two phenols, one ether, one furan, one acid, two hydrocarbons, and one pyrazine. Ketones, aldehydes, and alcohols were the main volatile compounds forming the flavor of Dongxiang tribute sheep mutton. The reliability of the results was validated by PCA (principal component analysis) and similarity analyses. Our results provide reference value for consumers of mutton in China.

A Sequence Variation in GmBADH2 Enhances Soybean Aroma and Is a Functional Marker for Improving Soybean Flavor

The vegetable soybean (Glycine max L. Merr.) plant is commonly consumed in Southeast Asian countries because of its nutritional value and desirable taste. A "pandan-like" aroma is an important value-added quality trait that is rarely found in commercial vegetable soybean varieties. In this study, three novel aromatic soybean cultivars with a fragrant volatile compound were isolated. We confirmed that the aroma of these cultivars is due to the potent volatile compound 2-acetyl-1-pyrroline (2AP) that was previously identified in soybean. A sequence comparison of GmBADH1/2 (encoding an aminoaldehyde dehydrogenase) between aromatic and non-aromatic soybean varieties revealed a mutation with 10 SNPs and an 11-nucleotide deletion in exon 1 of GmBADH2 in Quxian No. 1 and Xiangdou. Additionally, a 2-bp deletion was detected in exon 10 of GmBADH2 in ZK1754. The mutations resulted in a frame shift and the introduction of premature stop codons. Moreover, genetic analyses indicated that the aromatic trait in these three varieties was inherited according to a single recessive gene model. These results suggested that a mutated GmBADH2 may be responsible for the aroma of these three aromatic soybean cultivars. The expression and function of GmBADH2 in aromatic soybean seeds were confirmed by qRT-PCR and CRISPR/Cas9. A functional marker developed on the basis of the mutated GmBADH2 sequence in Quxian No. 1 and Xiangdou was validated in an F2 population. A perfect association between the marker genotypes and aroma phenotypes implied that GmBADH2 is a major aroma-conferring gene. The results of this study are potentially useful for an in-depth analysis of the molecular basis of 2-AP formation in soybean and the marker-assisted breeding of aromatic vegetable soybean cultivars.

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

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

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.

Comparative Analysis and Development of a Flavor Fingerprint for Volatile Compounds of Vegetable Soybean Seeds Based on Headspace-Gas Chromatography-Ion Mobility Spectrometry

Evaluating the volatile compounds and characteristic fingerprints of the core cultivars of vegetable soybean would provide useful data for improving their aroma in the breeding programs. The present study used headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to evaluate the volatile compounds of vegetable soybean seeds at a specific growth stage. In total, 93 signal peaks were identified, 63 compounds qualitatively, with 14 volatile flavor compounds providing multiple signals. The 63 volatile compounds consisted of 15 esters, 15 aldehydes, 13 alcohols, 15 ketones, one acid, and four other compounds. The peak intensity of most of the volatile compounds varied greatly between the core cultivars. The alcohols and aldehydes determined the basic volatile flavor of the vegetable soybean seeds. Volatile flavors were determined by their respective esters, ketones, or other components. Characteristic fingerprints were found in some core vegetable soybean cultivars. Four cultivars (Xiangdou, ZHE1754, Zhexian 65018-33, and Qvxian No. 1) had pleasant aromas, because of their higher content of 2-acetyl-1-pyrroline (2-AP). A principal component analysis (PCA) was used to distinguish the samples based on the signal intensity of their volatile components. The results showed that the composition and concentration of volatile compounds differed greatly between the core cultivars, with the volatile flavor compounds of soybeans being determined by the ecotype of the cultivar, the direction of breeding selection, and their geographical origin. Characteristic fingerprints of the cultivars were established by HS-GC-IMS, enabling them to be used to describe and distinguish cultivars and their offspring in future breeding studies.

Volatile compounds, bacteria compositions and physicochemical properties of 10 fresh fermented rice noodles from southern China

To clarify the discrepancy in characteristic flavor and bacteria composition of 10 fresh fermented rice noodles from southern China, the volatile and bacteria composition were determined by headspace-gas chromatography ion mobility spectrometry and 16SrRNA sequencing methods. The potential relationship between volatile compounds and bacterial composition has also been further revealed using spearman's correlation analysis. The contents of proximate composition, cooking properties and texture properties of 10 fresh fermented rice noodles exhibited significant different among them (p ＜ 0.05). The flavor analysis showed that a total of 54 compounds were detected. 1-Octen-one, ethyl 3-methylbutanoate, 3-methylbutanal, n-nonanal, hexanal, amyl acetate, ethanol and 2-pentyl furan were the key volatiles among them. The bacterial analysis showed that Leuconostoc and Lactococcus were the core bacteria at the genu level of all samples. Amyl acetate, 2-butanone and methyl-2-methylpropanoate were positively related to Lactococcus while ethanol was negatively correlated with Lactococcus. And Leuconostoc was positively related to 3-methylbutanal and acetone, while was negatively correlated with hexanal. Results indicated that key volatiles and textural properties of different fresh fermented rice noodle samples were associated with bacterial composition.

The Aroma Fingerprints and Discrimination Analysis of Shiitake Mushrooms from Three Different Drying Conditions by GC-IMS, GC-MS and DSA

The aroma fingerprints and discrimination analysis of shiitake mushrooms under different drying conditions were performed by GC-IMS, GC-MS, and descriptive sensory analysis (DSA) with advanced chemometric methods. Three samples (A, B, and C) were treated with varied drying degree and rate. The sample A and C were at the same drying degree and the sample B and C were at the same drying rate. The GC-IMS volatile fingerprints, including the three-dimensional topographic map, topographic map, and gallery plot, showed that 29 compounds showed higher signal intensities in sample B. Moreover, 28 volatile compounds were identified by HS-SPME-GC-MS and only 8 compounds were ever detected by GC-IMS. The sample B not only had more varieties of volatile compounds, but also showed significant higher contents than sample A and C, especially C8 compounds (p < 0.05). Additionally, sample B showed the highest intensity in mushroom-like, chocolate-like, caramel, sweat, seasoning-like, and cooked potato-like odors by DSA. PCA, fingerprint similarity analysis (FSA) and PLSR further demonstrated that the sample B was different from sample A and C. These results revealed that samples with different drying degree were different and drying degree exerted more influence on the volatile flavor quality than the drying rate. This study will provide a foundation and establish a set of comprehensive and objective methods for further flavor analysis.

Strategy for the multi-component characterization and quality evaluation of volatile organic components in Kaixin San by correlating the analysis by headspace gas chromatography/ion mobility spectrometry and headspace gas chromatography/mass spectrometry

RATIONALE

Kaixin San (KXS) is a prescription traditional Chinese medicine (TCM) with the effects of "tonifying the kidney and brain" and "improving memory". The volatile organic compounds (VOCs) in KXS could effectively improve senile dementia and depression, but only few studies have focused on the overall characterization of VOCs in KXS and the quantitative study of the main active components.

METHODS

We have developed a strategy to correlate the results from headspace gas chromatography/ion mobility spectrometry (HS-GC/IMS) and headspace gas chromatography/mass spectrometry (HS-GC/MS) for the comprehensive characterization of VOCs in KXS and the quantitative analysis of the main pharmacodynamic substances.

RESULTS

A totsal of 68 low molecular weight VOCs were identified in KXS by HS-GC/IMS at room temperature and atmospheric pressure; 117 VOCs were identified and 10 components (isocalamenediol, α-asarone, β-asarone, methyl eugenol, isoeugenol methyl ether, camphor, anethol, 2,4-di-tert-butylphol, linalool, asarylaldehyde) as the quality markers of KXS based on HS-GC/MS.

CONCLUSIONS

This results from this study provide a foundation for quality control, pharmacodynamic mechanism research and further development of KXS, and provides more convincing data supporting the VOCs of other natural products.

Characteristic fingerprints and volatile flavor compound variations in Liuyang Douchi during fermentation via HS-GC-IMS and HS-SPME-GC-MS

The present study investigates volatile organic compound (VOC) compositional changes in Liuyang Douchi during fermentation via a HS-GC-IMS and HS-SPME-GC-MS combination approach. A total of 115 VOCs were identified from Douchi, most of which were accumulated during pile fermentation. Notably, most alcohols and acids decreased with fermentation, while esters, ketones, pyrazines, and phenols accumulated during pile fermentation. Depending on the VOCs identified by GC-IMS/MS, the different fermentation stages of Douchi could be facilely distinguished. Of these, 49 VOCs were regarded as the marker VOCs of Douchi in different fermentation stage: hexanol, hexanal, and propanoic acid was the marker VOCs of the black beans before fermentation and contributing beany and grassy odors; 1-octen-3-ol and 3-octanone supplying a mushroom aroma to the Douchi fermented for 3-9 days; and esters and pyrazine, especially ethyl acetate and 2,6-dimethylpyrazine, contributing the cocoa, fruity, and nutty aromas of matured Douchi.

Changes in volatile organic compounds and lipid oxidation in traditional Chinese bacon during cold smoking

The smoking time of cold-smoked traditional Chinese bacon (TCB) in northeast Chongqing is not precisely controlled. In this study, the accumulation of, and changes in, volatile organic compounds (VOCs) during smoking were investigated by gas chromatography–ion mobility spectrometry (GC-IMS). Simultaneously, the lipid oxidation and sensory attributes of TCB were assessed. Thirty-nine VOCs were identified in samples, most of which were alcohols, aldehydes, ketones, and esters. Samples smoked for 12 and 15 days contained characteristic VOCs, mainly comprising phenols, esters, and heterocyclic compounds, which produce the flavor of mature TCB. Odorous substances other than characteristic VOCs reached their maximum or sub-maximum on day 12, which was consistent with the sensory assessment results. The peroxide value of TCB increased continuously with smoking; while 2-thiobarbituric acid reactive substances test (TBARS) values were at a lower level between days 9 and 12. Therefore, the recommended smoking time should be about 12 days.

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

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

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

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

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

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

Characteristic volatile organic compounds in “HeTao” melon and other cultivars grown in Hetao region analyzed by HS-GC-IMS

The headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was used to compare the volatile organic components of the Hetao melon and six other cultivars of melon grown in the Hetao region of China. The results showed that the common VOCs that could be qualitatively identified from the 7 different melon samples were 35 monomers and dimers of certain compounds, mainly including alcohols, esters, aldehydes, terpenes, acids and pyridines. Hexyl acetate, 3-methylbutyl acetate, ethyl acetate and ethyl formate were predominant VOCs in seven melon cultivars. Among them, Xizhoumi No. 25 (XZM25) had 3 unique volatile organic components: 3-methylbutanal, benzaldehyde and nonanal. Xizhoumi No. 17 (XZM17) had 3 unique volatile organic components: alpha-pinene, linalool and (E)-2-hexenol. Jinhongmi (JHM) had 1 unique volatile organic component: ethyl pentanoate. The Hetao melon (HLS) contained 3 unique volatile organic components: heptanal, 2-ethyl-6-methyl pyrazine and 3-methyl valeric acid. Yinmi (YM) had 2 unique volatile organic components: 3-methylbutanol and 1-butanol, and Huangjinmi (HJM) had 1 unique volatile organic component: limonene. YM, GMB2010, HLS and JHM were similar based on the principal component analysis. This research analyzed the flavor components of different melon cultivars grown in the Hetao region of China for the first time.

Volatile Profile and Biosynthesis of Post-harvest Apples are Affected by the Mechanical Damage

Mechanical damage to fruit causes flavor changes during post-harvest supply chains. It is important to identify the main volatiles and explore their biosynthesis mechanism. In this study, the volatile changes in apples caused by mechanical damage were analyzed by gas chromatography-ion mobility spectrometry. Hexanal and ethyl acetate were accumulated and identified as potential volatile biomarkers to detect damaged apples. The study on the lipoxygenase (LOX) pathway and transcription factors (TFs) shows that mechanical damage up-regulated the expression of MdLOX-like, MdLOX3b, MdLOX7b, MdLOX7c, MdLOX2a, and MdAAT in the LOX pathway and that of one MYB TF (MdMYB-like), five ERF TFs (MdERF073, MdERF003, MdERF114, MdERF15, and MdERF2), and five WRKY TFs (MdWRKY23, MdWRKY17, MdWRKY46, MdWRKY48, and MdWRKY71). Notably, MdAAT was significantly correlated to MdMYB-like, MdWRKY23, MdWRKY71, MdERF15, and MdERF2. Thus, TFs may attribute to the accumulation of hexanal and ethyl acetate by regulating the expression of LOX pathway-related genes.