A green triple-locked strategy based on volatile-compound imaging, chemometrics, and markers to discriminate winter honey and sapium honey using headspace gas chromatography-ion mobility spectrometry

Advances of Ion Mobility Platform for Plant Metabolomics

Metabolomics aims to profile the extensive array of metabolites that exists in different types of matrices using modern analytical techniques. These techniques help to separate, identify, and quantify the plethora of chemical compounds at various analytical platforms. Hence, ion mobility spectrometry (IMS) has emerged as an advanced analytical approach, exclusively owing to the 3D separation of metabolites and their isomers. Furthermore, separated metabolites are identified based on their mass fragmentation pattern and CCS (collision cross-section) values. The IMS provides an advanced alternative dimension to separate the isomeric metabolites with enhanced throughput with lesser chemical noise. Thus, the present review highlights the types, factors affecting the resolution, and applications of IMMS (Ion mobility mass spectrometry) for isomeric separations, and ionic contaminants in the plant samples. Furthermore, an overview of IMS-based applications for the identification of plant metabolites (volatile and non-volatile) over the last few decades has been discussed, followed by future assumptions for creating IM-based databases. Such approaches could be significant to accelerate and improve our knowledge of the vast chemical diversity found in plants.

Characterization of flavor substances in cooking and seasoned cooking brown seaweeds by GC-IMS and E-nose

The flavor of algae was one of the key factors for consumer acceptance. The objective of this study was to investigate the characteristic volatile compounds in cooking and seasoned cooking edible brown seaweeds (Undaria pinnatifida and Laminaria japonica). The gas chromatography-ion mobility spectrometry (GC-IMS) and electronic nose (E-nose) analysis showed that baking resulted in significant difference in flavor of brown seaweeds. However, the overall effect of cooking was not as significant as that of the seasoning solution treatment. Additionally, brown seaweeds treated with the seasoning solution were more acceptable. Undaria pinnatifida was found to contain 72 volatile flavor compounds, while Laminaria japonica had a total of 70. This study proved the applicability of GC-IMS combined with E-nose technology to detect the changes of volatile components of brown seaweeds after processing, providing beneficial knowledge and basic theory for the deep processing of brown seaweeds.

Explorative study for the rapid detection of adulterated surimi using gas chromatography-ion mobility spectrometry

Driven by economic interests, surimi adulteration has become a high-frequency issue. This study aims to assess the feasibility of gas chromatography-ion mobility spectrometry (GC-IMS) in detecting surimi adulteration. In this work, three common adulterated surimi models were established by mixing with different fish species and ratios. The fingerprints enabled a clear discrimination among different tuna surimi, and other two surimi models with different mixing ratios also showed VOCs (volatile organic compounds) differences. Results of unsupervised principal component analysis (PCA) and supervised partial least-squares discrimination analysis (PLS-DA) revealed that different types of adulterated surimi models can be well separated from each other. A total of 12, 16, and 9 VOCs were selected as the potential markers in three simulated models by PLS-DA method, respectively. Therefore, GC-IMS coupled with certain chemometrics is expected to serve as an alternative analytical tool to directly and visually detect adulterated surimi.

Evaluation of Loquat Jam Quality at Different Cooking Times Based on Physicochemical Parameters, GC-IMS and Intelligent Senses

The study compared and analyzed the quality of loquat jam with different cooking times through physicochemical parameters, headspace-gas chromatography-ion migration spectroscopy (HS-GC-IMS) and intelligent senses. The results showed that with the prolongation of the cooking time, the color of loquat jam slowly deepened, the energy significantly increased, the adhesiveness, gumminess, hardness and chewiness enhanced, the free amino acid content increased from 22.40 to 65.18 mg/g. The organic acid content increased from 1.64 to 9.82 mg/g. Forty-seven volatile flavor compounds were identified in five types of loquat jam using HS-GC-IMS, among which the relative content of aldehydes was sharply higher than that of other chemical substances, playing an important role in the flavor formation of loquat jam. LJ0, LJ1 and LJ2 had higher aldehyde content, followed by LJ3 and LJ4 had the lowest aldehyde content. The orthogonal partial least squares-discriminant analysis (OPLS-DA) screened 15 marker compounds that could distinguish five types of loquat jam. The E-nose results showed a significant difference in olfactory sense between loquat jam cooked for 100 and 120 min. The E-tongue results corroborated the results of free amino acids (FAAs) and organic acids, indicating that the gustatory sense of loquat jam changed significantly when the cooking time reached 120 min. The results provided a basis for further research on the relationship between the cooking process and quality characteristics of loquat jam.

Simultaneous qualitative and quantitative analyses of volatile components in Chinese honey of six botanical origins using headspace solid-phase microextraction and gas chromatography-mass spectrometry

BACKGROUND

Honey aroma is one of its most important properties and it depends on the qualitative and quantitative composition of the volatile compounds. The volatile profile of honey could reveal its botanical origin to avoid a false characterization. Thus, it is of great significance to honey authentication. This study developed and validated a headspace solid-phase microextraction and gas chromatography-mass spectrometry (HS-SPME-GC-MS) method for simultaneous qualitative and quantitative analyses of 34 volatile components in honey. The developed method was applied to 86 honey samples from six different botanical origins, including linden honey, rape honey, jujube honey, vitex honey, lavender honey and acacia honey.

RESULTS

The volatile fingerprints and quantitative results were simultaneously obtained by using the full scan and selected ion monitoring (SCAN+SIM) MS scanning mode. The limits of quantification (LOQs) and limits of detection (LODs) of 34 volatile compounds were in the ranges of 1-10 ng/g and 0.3-3 ng/g, respectively. And the spiked recoveries ranged between 70.6% and 126.2%, with the relative standard deviations (RSDs) not higher than 45.4%. A total of 98 volatile compounds were found with relative contents determined, and the 34 volatile compounds were determined with absolute concentrations. Based on the volatile fingerprints and the contents of volatile compounds, honey samples from six botanical origins were well classified by principal component analysis and orthogonal partial least-squares discrimination analysis.

CONCLUSIONS

The HS-SPME-GC-MS method was successfully applied to achieve the volatile fingerprints of six types of honey and to quantitatively analyze 34 volatile compounds with satisfying sensitivity and accuracy. Chemometrics analysis showed significant correlations between honey types and volatiles. These results reveal the characteristics of volatile compounds in six types of unifloral honey and provide some supports for honey authentication. © 2023 Society of Chemical Industry.

A comprehensive review of the current trends and recent advancements on the authenticity of honey

The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.

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.

Uncovering the differences in flavor volatiles of different colored foxtail millets based on gas chromatography-ion migration spectrometry and chemometrics

The differences of volatile organic compounds in commercially available foxtail millets with different colors (black, green, white and yellow) were assayed through gas chromatography-ion migration spectrometry (GC-IMS) to explore their volatile flavor characteristics. Fifty-five volatile components were found in various colored foxtail millets, including 25 kinds of aldehydes (accounting for 39.19-48.69%), 10 ketones (25.36-32.37%), 15 alcohols (20.19-24.11%), 2 ethers (2.29-2.45%), 2 furans (1.49-2.95%) and 1 ester (0.27-0.39%). Aldehydes, alcohols and ketones were the chief volatiles in different colored foxtail millet, followed by furans, esters and ethers. These identified volatile flavor components in various colored foxtail millets obtained by GC-IMS could be well distinguished by principal components and cluster analysis. Meanwhile, a stable prediction model was fitted via partial least squares-discriminant analysis (PLS-DA), in which 17 kinds of differentially volatile components were screened out based on variable importance in projection (VIP>1). These findings might provide certain information for understanding the flavor traits of colored foxtail millets in future.

Application of GC-IMS coupled with chemometric analysis for the classification and authentication of geographical indication agricultural products and food

Geographical indications (GI) are used to protect the brand value of agricultural products, foodstuffs, and wine and promote the sustainable development of the agricultural and food industries. Despite the necessity for the traceability and recognition of GI product characteristics, no rapid, non-destructive approaches currently exist to identify, classify, and predict these properties. The application of gas chromatography-ion mobility spectrometry (GC-IMS) has increased exponentially due to instrument robustness and simplicity. This paper provided a detailed overview of recent GC-IMS applications in China for the quality evaluation of GI products and food, including agricultural products, as well as traditional Chinese food and liquor. The general workflow of GC-IMS coupled with chemometric analysis is presented, including sample collection, model construction and interpretation, and data acquisition, processing, and fusion. Several conclusions are drawn to increase partial least squares-discriminant analysis (PLS-DA) model precision, a chemometric technique frequently combined with GC-IMS.

Characterization and discrimination of flavor volatiles of different colored wheat grains after cooking based on GC-IMS and chemometrics

Changes in flavor volatiles of three colored wheat grains (black, green, and yellow) after cooking were detected via gas chromatography-ion migration spectrometry (GC-IMS) to explore corresponding volatile flavor traits. A total of 52 volatile chemicals were spotted among these cooked wheat grains, including 30 aldehydes (accounting for 73.86-83.78%), 11 ketones (9.53-16.98%), 3 alcohols (0.88-1.21%), 4 furans (4.82-7.44%), 2 esters (0.28-0.42%), and 2 pyrazines (0.18-0.32%). Aldehydes, ketones, and furans were the main volatile compounds in three different cooked wheat. For black-colored wheat, the relative contents of benzene acetaldehyde, benzaldehyde, 2-methyl butanal, and 3-methyl butanal were much higher (p < 0.05). For green-colored wheat, the relative contents of nonanal, 2-pentyl furan, (E)-hept-2-enal, 2-butanone, and acetone were significantly higher (p < 0.05). For yellow-colored wheat, the relative amounts of heptanal, hexanal, and pentanal were much higher (p < 0.05). The overall volatile substances of the three cooked wheat grains might be classified by GC-IMS data coupled with principal component analysis and heatmap clustering analysis. A reliable forecast set was established through orthogonal partial least squares-discriminant analysis (OPLS-DA), and 22 differential volatile compounds were screened out based on variable importance in projection (VIP) being higher than 1.0, as flavor markers for distinguishing the three cooked wheat grains. These results suggest that GC-IMS could be used for characterizing the flavor volatiles of different colored wheat, and the findings could contribute certain information for understand the aroma traits in different colored cooked wheat and related products in the future.

Characterization of volatile organic compounds of different pigmented rice after puffing based on gas chromatography-ion migration spectrometry and chemometrics

The distinctness in volatile profiles of pigmented rice with various colors (black, green, purple, red, and yellow) after puffing were assayed through gas chromatography-ion migration spectrometry (GC-IMS) to explore their odor characteristics. Fifty-two volatile components were found in those puffed rice, including 27 kinds of aldehydes (accounting for 59.69-64.37 %), 9 ketones (25.55-29.73 %), 5 alcohols (2.45-5.29 %), 4 pyrazines (1.38-2.36 %), 3 ethers (0.81-1.27 %), 2 furans (0.95-1.39 %), 1 pyridine (1.0-1,16 %), and 1 pyrrole (0.59-0.71 %). Aldehydes and ketones were the two chief volatiles in different pigmented puffed rice. These identified volatile flavor components in various pigmented puffed rice obtained by GC-IMS might be well differentiated by principal component and cluster interpretation. Meanwhile, a stable prediction model was fitted via orthogonal partial least squares-discriminant analysis, and 19 differentially volatile components were screened out based on variable importance projection (VIP) above 1. These findings could add certain information for understanding the flavor profiles of pigmented puffed rice and related products.

Development of a Flavor Fingerprint Using HS-GC-IMS for Volatile Compounds from Steamed Potatoes of Different Varieties

The variations in flavor substances across different varieties of steamed potatoes were determined by headspace-gas chromatography ion mobility spectrometry (HS-GC-IMS) combined with sensory evaluation. Results showed that 63 representative compounds, including 27 aldehydes, 14 alcohols, 12 ketones, 4 esters, 2 furans, 1 acid and others, together acted as contributors to the flavors in steamed potatoes. Analysis found that species and concentrations of aldehydes, alcohols and ketones in six varieties were the most abundant. In addition, esters, furans and acid were also responsible for flavor. PCA results showed that volatile compounds in Atlantic, Longshu No. 23, Longshu No. 7 and Longshu No. 14 were similar, while Russet Burbank and Longshu No. 16 had distinct characteristic volatiles, which was consistent with sensory evaluation. The combination of sensory evaluation and HS-GC-IMS provided useful knowledge for charactering volatile compounds of steamed potatoes from different varieties, and also demonstrated the promising application of HS-GC-IMS in the detection of potato flavor with various cooking methods.

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

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

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

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

Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage

The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing.

A non-targeted metabolomic strategy for characterization of the botanical origin of honey samples using headspace gas chromatography-ion mobility spectrometry

In this work, characterization of the botanical origin of honey was carried out using headspace gas chromatography coupled to ion mobility spectrometry (HS-GC-IMS). The proposed methodology was applied for the analysis of 89 samples from ten different botanical origins. A total of 15 volatile compounds could be identified, namely, 3-methyl-1-butanol, heptanal, valeraldehyde, octanal, trans-2-hexenal, nonanal, hexanal, benzaldehyde, 2-heptanone, 2-butanone, 2-hexanone, 6-methyl-5-hepten-2-one, 2-pentanone, ethyl acetate and linalool. The analytical method was characterized in terms of limits of detection and quantification, and precision, in order to quantify the identified compounds. Compounds were quantified using the sum of the protonated monomer and proton-bound dimer and logarithmic regression (R² > 0.98), although the establishment of a concentration threshold that would allow creation of classification rules was not possible since there was variability within the group. Consequently, the establishment of chemometric models was necessary. A non-targeted strategy using 275 features is proposed. Orthogonal partial least squares-discriminant analysis (OPLS-DA) allowed the differentiation of five botanical origins: thousand flowers, rosemary, albaida, orange blossom, and "others" (rest of the investigated botanical origins, since a limited number of samples was available). A success validation rate of 100% allowed the classification of 14 honeys with unknown botanical origin.

Rapid authentication of Chaenomeles species by visual volatile components fingerprints based on headspace gas chromatography-ion mobility spectrometry combined with chemometric analysis

INTRODUCTION

Chaenomeles, including Chaenomeles speciosa (ZP), Chaenomeles sinensis (GP), Chaenomeles tibetica (XZ), and Chaenomeles japonica (RB), has been widely used as food in China for thousands of years. However, only ZP, was recorded to be the authentic medicinal Chaenomeles. Therefore, the rapid and accurate method for the authenticity identification of Chaenomeles species is urgently needed.

OBJECTIVE

To develop a method for rapid differentiation of Chaenomeles species.

METHODS

The visual volatile components fingerprints based on headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with chemometric analysis, including principal component analysis (PCA), linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLS-DA), were utilised for the authentication of Chaenomeles species.

RESULTS

The visual volatile components fingerprints by the GC-IMS intuitively showed the distribution features of the volatile components for different Chaenomeles samples. The LDA and PLS-DA models successfully discriminated Chaenomeles species with original discrimination accuracy of 100%. Fifteen volatile compounds (VOCs) (peaks 9, 12, 13, 19, 23, 24, 35, 48, 57, 65, 67, 76, 79, 80, 83) were selected as the potential species-specific markers of Chaenomeles via variable importance of projection (VIP > 1.2) and one-way analysis of variance (P < 0.05).

CONCLUSIONS

This study showed that the visual volatile components fingerprints by HS-GC-IMS combined with chemometric analysis is a meaningful method in the Chaenomeles species authentication.

Acrylamide formation and aroma evaluation of fried pepper sauce under different exogenous Maillard reaction conditions

To explore the impact of the Maillard reaction on fried pepper sauce (FPS) flavor and safety quality, acrylamide and volatile organic compounds (VOCs) were measured in FPS. Acrylamide was detected in 10 Maillard treated groups and a total of 110 VOCs were identified, mainly aldehydes, ketones, alcohols, acids, etc., but the content of each group differed. Partial least squares discriminant analysis showed that acrylamide in white sugar-sodium glutamate group and xylose-soy peptide group processing accumulated most acrylamide and least VOCs; Lactose-glycine, lactose-cysteine, lactose-soy peptide, and white sugar-glycine groups were positively correlated with typical Maillard reaction product (2,3-Dihydro-3,5-dihydroxy-6-methyl-4(H)-pyran-4-One); Xylose-glycine, xylose-cysteine, and white sugar-cysteine groups were weakly correlated with typical products, but positively correlated with most VOCs, whereas white sugar-cysteine group lipids showed high oxidation levels. Although white sugar-soy peptide group is not harmful on acrylamide, it has little correlation with VOCs with large responses. Conventional excipient group aroma is relatively simple with a fresh fatty taste, whereas xylose-glycine, xylose-cysteine, xylose-soy peptide, lactose-glycine, and white sugar-cysteine groups all present basic fresh and fatty tastes; lactose-cysteine group has a fruity base note; and lactose-soybean peptide, white sugar-glycine, and white sugar-soybean peptide groups have a fruity base note on an unpleasant fatty aroma. Therefore, processing different exogenous Maillard reaction substrates can achieve FPS aroma regulation and reduce acrylamide harm.

HS-GC-IMS identification of volatile aromatic compounds of freshly-cooked rice packaged with different disposable lunchboxes

The rapid development of online-to-offline food delivery service has necessitated the replacement of plastic lunchbox using biodegradable ones. In current study, a total number of fourteen panelists were firstly recruited and trained to investigate how different commercial disposable lunchboxes affect the freshly cooked rice sensory properties during heat preservation (60 °C, 60 min). The lunchboxes were made of pure polypropylene (PP), polypropylene-starch (PP-S), pure wheat-straw and sugarcane-straw (WS & SS) and Paper. The discrepancy of volatile aromatic substances was then analyzed using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to study the possible mechanism beneath the variations of the influences of different lunchboxes on the aromatic properties of rice. Results showed that, compared with the textural attributes, the aroma was significantly and positively correlated with panelist's acceptability, among which, the aroma of starchy, sulfur and smoky are the most important ones. The moisture absorption plays an important role in affecting the aromatic characteristics of the packaged rice. While all lunchboxes have inhibitory effects on the production of volatile flavor substances including 2,6-Dimethylpyrazine, 2-Acetylpyrazine and γ-Octalactone, pure PP and PP-S lunchboxes generated undesirable flavor substances including 2-Ethyl-1-hexanl and Camphene, and thus reduced panelist's preferences. It was also found that the panelist liked the rice packaged by Paper lunchbox the best because of its better performance in maintaining the aroma of starchy and sulfur, the two substances that are associated with the higher concentration of ethereal and fruity volatile flavor substances. This study provides important information for manufacturers to understand how different disposable lunchboxes may impact the textural and aromatic properties of packaged foods.

Volatile organic compounds produced by Bacillus velezensis L1 as a potential biocontrol agent against postharvest diseases of wolfberry

Volatile organic compounds (VOCs) produced by antagonistic microorganisms have good biocontrol prospects against postharvest diseases. Infection caused by Alternaria iridiaustralis and 10 other significant fungal diseases can be successfully inhibited by VOCs produced by an identified and screened endophytic strain L1 (Bacillus velezensis). This study revealed the in vivo and in vitro biocontrol effects of VOCs released by B. velezensis L1 on A. iridiaustralis, a pathogenic fungus responsible for rot of wolfberry fruit. The inhibition rates of VOCs of B. velezensis L1 on the mycelial growth of A. iridiaustralis in vitro were 92.86 and 90.30%, respectively, when the initial inoculum concentration on the plate was 1 × 10⁹ colony forming unit (CFU)/ml. Spore germination and sporulation were 66.89 and 87.96%, respectively. VOCs considerably decreased the wolfberry’s disease index and decay incidence in vivo. Scanning electron microscopy revealed that the morphological and structural characteristics of A. iridiaustralis could be altered by VOCs. Ten VOCs were identified through headspace-gas chromatography-ion mobility spectrometry. Pure chemical tests revealed that 2.3-butanedione had the strongest antifungal effects, totally inhibiting A. iridiaustralis in wolfberry fruit at a 60 μl/L concentration. The theory underpinning the potential application of VOCs from B. velezensis is provided herein. This is also the first study to document the antifungal capabilities of the B. velezensis strain on postharvest wolfberry fruit.

GRAPHICAL ABSTRACT

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.

Effect of Flaxseed Supplementation in Diet of Dairy Cow on the Volatile Organic Compounds of Raw Milk by HS-GC-IMS

Flaxseed supplementation in diet of dairy cow can effectively enhance the production of ω-3 polyunsaturated fatty acids (n-3 PUFA) in raw milk, which further give rise to the changes of volatile organic compounds (VOCs). In this study, we used headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to investigate the VOCs in milk from cows fed three different diets (CK: supplemented with 0 g/d flaxseed; WF: 1,500 g/d whole flaxseed and GF: 1,500 g/d ground flaxseed). A total of 40 VOCs including three acids, six esters, 11 aldehydes, seven alcohols, 13 ketones were identified in all the raw milk samples. Compared with GF supplementation, suppling with WF could influence more compounds in raw milk (GF: five compounds; WF: 22 compounds). Supplementation with WF could increase the concentration of nonanal, heptanal, hexanal, which could cause the occurrence of off-flavors, and reduce the concentration of hexanoic acid (monomer; M), 2-hexanol, ethanol (M), 2-heptanone (dimer; D), 2-pentanone (M), 2-pentanone (D), acetoin (M) in raw milk. GF supplementation in diet could reduce the 2-pentanone (M), 2-pentanone (D). In addition, principal component analysis (PCA) based on the signal intensity of identified VOCs indicated that it is possible to distinguish between the CK and WF milk. However, GF milk could not be distinguished from CK milk. The results demonstrate that compared with GF milk, WF supplementation in diet of dairy cows could increase fishy (heptanal) cardboard-like (pentanal) flavor in milk and decrease sweet (hexanoic acid, 2-heptanone), fruity (ethyl butanoate, ethyl hexanoate, 2-heptanone) flavor which may lead the milk less acceptable. In conclusion, compared with WF, GF supplementation in diet of dairy cow showed higher increase in n-3 PUFA in raw milk, and less influence in VOCs of raw milk and this study might provide theoretical supports for the production of milk rich in n-3 PUFA.

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.

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.

Investigation of the Maturity Evaluation Indicator of Honey in Natural Ripening Process: The Case of Rape Honey

Honey maturity, a critical factor for quality evaluation, is difficult to detect in the current industry research. The objective of this study was to explore the changes in the composition and find potential maturity indicators of rape honey at different maturity stages through evaluating physicochemical parameters (moisture, sugars, pH, electrical conductivity, total protein, total phenols, total flavonoids, proline, and enzyme activity), the antioxidant capacity, and volatile components. The relevant results are as follows: 1. As the maturity increased, the moisture, sucrose, and maltose content of rape honey gradually decreased, while the glucose, fructose, and total protein content gradually increased. The activities of diastase, invertase, and β-glucosidase showed a significant increase with the elevation of ripening days, and the activity of glucose oxidase reached the highest before completely capping. 2. The antioxidant capacity of honey increased with the increase in honey maturity. There is a significant and strong correlation between the bioactive components of rape honey and antioxidant capacity (p < 0.01, |r| > 0.857). 3. Thirty-five volatile components have been identified. Nonanal, benzaldehyde monomer, and benzaldehyde dimer can be used as potential indicators for the identification of honey maturity stages. Principal component analysis (PCA) based on antioxidant parameters and volatile components can identify the maturity of honey.

Untargeted Headspace-Gas Chromatography-Ion Mobility Spectrometry in Combination with Chemometrics for Detecting the Age of Chinese Liquor (Baijiu)

This paper proposes the combination of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and chemometrics as a method to detect the age of Chinese liquor (Baijiu). Headspace conditions were optimized through single-factor optimization experiments. The optimal sample preparation involved diluting Baijiu with saturated brine to 15% alcohol by volume. The sample was equilibrated at 70 °C for 30 min, and then analyzed with 200 μL of headspace gas. A total of 39 Baijiu samples from different vintages (1998–2019) were collected directly from pottery jars and analyzed using HS-GC-IMS. Partial least squares regression (PLSR) analysis was used to establish two discriminant models based on the 212 signal peaks and the 93 identified compounds. Although both models were valid, the model based on the 93 identified compounds discriminated the ages of the samples more accurately according to the goodness of fit value (R²) and the root mean square error of prediction (RMSEP), which were 0.9986 and 0.244, respectively. Nineteen compounds with variable importance for prediction (VIP) scores > 1, including 11 esters, 4 alcohols, and 4 aldehydes, played vital roles in the model established by the 93 identified compounds. Overall, we determined that HS-GC-IMS combined with PLSR could serve as a rapid and accurate method for detecting the age of Baijiu.

Effects of different cooking methods on free fatty acid profile, water-soluble compounds and flavor compounds in Chinese Piao chicken meat

Piao chicken breast meat was cooked by three different methods (boiling, frying and roasting). Non-volatile and volatile substances in the three cooked chicken were analyzed by GC-MS, UPLC-Q-Exactive-MS and GC-IMS, respectively. Arachidonic acid was the highest in boiled chicken, oleic acid was the highest in roasted chicken, linoleic acid, EPA and DHA were the highest in fried chicken. Compared with the control group, the total content of small molecular metabolites of chicken in each treatment group decreased. The total amount of amino acids in roasted chicken was 2.90 times of that in boiled chicken (P < 0.05), and 2.23 times of that in fried chicken (P < 0.05). A total of 26 volatile flavor compounds were detected. Phenylacetaldehyde etc. were the main volatile flavor compounds in boiled chicken, 3-butanedione etc. were the main volatile flavor compounds in fried chicken, while 3-methylbutyraldehyde etc. were the main volatile flavor compounds in roasted chicken.

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.

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 Characterization of Winter Jujube from Different Regions via HS-SPME-GC/MS and GC-IMS

A combined untargeted and targeted approach was established for fingerprinting volatile organic compounds in winter jujubes from eight regions of China. Volatiles, including alcohols, aldehydes, acids, esters, and alkenes, were identified by gas chromatography-ion mobility spectrometry (GC-IMS). Benzyl alcohol, octanoic acid, 2-hexenal, linalool, 2-nonenal, and ethyl decanoate were the most common compounds present in all jujubes. Principal component analysis (PCA) from GC-IMS and untargeted E-nose showed that the main volatile organic compounds (VOCs) of most jujubes were similar. The volatile organic compounds of winter jujubes from Yuncheng city, Shanxi province, and Aksu region, Xinjiang province, were significantly different from those from other regions. 1-Penten-3-ol, ethyl hexanoate, methyl laurate, and 2-formyltoluene were the markers of XJAKS with green and fruity aroma, and SXYC could be labeled by acetone and 2-methoxyphenol with woody and pungent aroma. GC-IMS was an effective method for volatile fingerprinting of jujubes with high sensitivity and accuracy.

HS-GC-IMS detection of volatile organic compounds in Acacia honey powders under vacuum belt drying at different temperatures

Honey is a commodity of great nutritional value, but deep-processed honey products are uncommon. Herein, we used vacuum belt dryer to dry Acacia honey at 60°C, 70°C, and 80°C, prepared it into powder, and analyzed its volatile compound differences. We established HS-GC-IMS method to detect the volatile organic compounds (VOCs) of these three Acacia honey powders (AHPs). In total, 77 peaks were detected, and 23 volatile compounds were identified, including eight aldehydes, six ketones, three furans, one alcohol, one phenol, one lactone, one ester, one acid, and one nitrile. Moreover, principal component analysis (PCA) and fingerprint similarity analysis based on the Euclidean distance distinguished the three heating temperature treatments. Clearly, it was concluded that there are significant differences in volatile substances at different tested temperatures, and when the AHP was incubated at 80°C, more volatile compounds were detected.

The Use of SPME-GC-MS IR and Raman Techniques for Botanical and Geographical Authentication and Detection of Adulteration of Honey

The aim of this review is to describe the chromatographic, spectrometric, and spectroscopic techniques applied to honey for the determination of botanical and geographical origin and detection of adulteration. Based on the volatile profile of honey and using Solid Phase microextraction-Gas chromatography-Mass spectrometry (SPME-GC-MS) analytical technique, botanical and geographical characterization of honey can be successfully determined. In addition, the use of vibrational spectroscopic techniques, in particular, infrared (IR) and Raman spectroscopy, are discussed as a tool for the detection of honey adulteration and verification of its botanical and geographical origin. Manipulation of the obtained data regarding all the above-mentioned techniques was performed using chemometric analysis. This article reviews the literature between 2007 and 2020.

Monofloral Honeys as a Potential Source of Natural Antioxidants, Minerals and Medicine

Background: vegetative diversity is based on different climate and geographical origins. In terms of beekeeping, herbal diversity is strongly correlated to the production of a wide variety of honey. Therefore, based on the existing plant diversity in each country, multiple honey varieties are produced with different health characteristics. While beekeeping potential and consumption preferences are reflected in products’ variety, this leads to an increase in the region’s economy and extensive export. In the last years, monofloral honey has gained interest from consumers and especially in the medicinal field due to the presence of phytochemicals which are directly linked to health benefits, wound healing, antioxidant, anticancer and anti-inflammatory activities. Scope and approach: this review aims to highlight the physicochemical properties, mineral profiles and antioxidant activities of selected monofloral honeys based on their botanical and geographical origin. Moreover, this review focuses on the intercorrelation between monofloral honey’s antioxidant compounds and in vitro and in vivo activities, focusing on the apoptosis and cell proliferation inhibition in various cell lines, with a final usage of honey as a potential therapeutic product in the fight towards reducing tumor growth. Key findings and conclusions: multiple studies have demonstrated that monofloral honeys have different physicochemical structures and bioactive compounds. Useful chemical markers to distinguish between monofloral honeys were evidenced, such as: 2-methoxybenzoic acid and trimethoxybenzoic acid are distinctive to Manuka honey while 4-methoxyphenylacetic acid is characteristic to Kanuka honey. Furthermore, resveratrol, epigallocatechin and pinostrobin are markers distinct to Sage honey, whereas carvacrol and thymol are found in Ziziphus honey. Due to their polyphenolic profile, monofloral honeys have significant antioxidant activity, as well as antidiabetic, antimicrobial and anticancer activities. It was demonstrated that Pine honey decreased the MDA and TBARS levels in liver, kidney, heart and brain tissues, whereas Malicia honey reduced the low-density lipoprotein level. Consumption of Clover, Acacia and Gelam honeys reduced the weight and adiposity, as well as trygliceride levels. Furthermore, the antiproliferative effect of chrysin, a natural flavone in Acacia honey, was demonstrated in human (A375) and murine (B16-F1) melanoma cell lines, whereas caffeic acid, a phenolic compound found in Kelulut honey, proves to be significant candidate in the chemoprevention of colon cancer. Based on these features, the use of hiney in the medicinal field (apitherapy), and the widespread usage of natural product consumption, is gaining interest by each year.

HS-GC-IMS with PCA to analyze volatile flavor compounds across different production stages of fermented soybean whey tofu

The variations in flavor substances across the different stages of fermented soybean whey tofu (FSWT) production were analyzed by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with principal component analysis (PCA). The results revealed 24 representative flavor compounds in the samples across all production stages. After heating, the signal intensity of hexanal, 1-octen-3-ol, heptanal, and (E)-2-hexenol, which are unpleasant flavor substances found in raw soymilk, weakened, whereas those of some aroma substances increased. Furthermore, fermented flavor compounds, namely, 2-heptanone, 2-pentylfuran, pentanal, and 2,3-butanedione, were produced after the addition of fermented soybean whey as a coagulant. A PCA based on the signal intensity of the detected volatile compounds revealed effective differentiation of samples from different stages into comparatively independent spaces. These results showed that the flavor fingerprints of the samples from different stages of FSWT production can be successfully built using HS-GC-IMS and PCA based on the detected volatile compounds.

Chemical Analyses and Antimicrobial Activity of Nine Kinds of Unifloral Chinese Honeys Compared to Manuka Honey (12+ and 20+)

Honey has good antimicrobial properties and can be used for medical treatment. The antimicrobial properties of unifloral honey varieties are different. In this study, we evaluated the antimicrobial and antioxidant activities of nine kinds of Chinese monofloral honeys. In addition, headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology was used to detect their volatile components. The relevant results are as follows: 1. The agar diffusion test showed that the diameter of inhibition zone against Staphylococcus aureus of Fennel honey (21.50 ± 0.41 mm), Agastache honey (20.74 ± 0.37 mm), and Pomegranate honey (18.16 ± 0.11 mm) was larger than that of Manuka 12+ honey (14.27 ± 0.10 mm) and Manuka 20+ honey (16.52 ± 0.12 mm). The antimicrobial activity of Chinese honey depends on hydrogen peroxide. 2. The total antioxidant capacity of Fennel honey, Agastache honey, and Pomegranate honey was higher than that of other Chinese honeys. There was a significant positive correlation between the total antioxidant capacity and the total phenol content of Chinese honey (r = 0.958). The correlation coefficient between the chroma value of Chinese honey and the total antioxidant and the diameter of inhibition zone was 0.940 and 0.746, respectively. The analyzed dark honeys had better antimicrobial and antioxidant activities. 3. There were significant differences in volatile components among Fennel honey, Agastache honey, Pomegranate honey, and Manuka honey. Hexanal-D and Heptanol were the characteristic components of Fennel honey and Pomegranate honey, respectively. Ethyl 2-methylbutyrate and 3-methylpentanoic acids were the unique compounds of Agastache honey. The flavor fingerprints of the honey samples from different plants can be successfully built using HS-GC-IMS and principal component analysis (PCA) based on their volatile compounds. Fennel honey, Agastache honey, and Pomegranate honey are Chinese honey varieties with excellent antimicrobial properties, and have the potential to be developed into medical grade honey.

Effect of microorganisms on the fingerprint of the volatile compounds in pine nut (Pinus koraiensis) peptide powder during storage

Pine nut (Pinus koraiensis) peptide (PNP) powder possesses promising bioactivities. However, the powder may have the quality problem of becoming sticky and smelly. Therefore, the volatile compounds' fingerprint of PNP powder was established by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The essential spoilage microorganisms were confirmed by 16S rDNA amplicon sequencing. The antioxidant activity, which presents PNP powder's quality, decreased during storage with the highest value of (1.88 ± 0.18) × 10¹⁴ at day 30. Fifty-nine significantly changed signals were detected; eight compounds were considered as volatile marker compounds. Besides, Firmicutes and Cyanobacteria were the essential spoilage microorganisms in PNP powder at the phylum level. Significantly, unidentified_Chloroplast, which belongs to Cyanobacteria, had a positive correlation with volatile marker compounds. The results proved that microorganisms indeed affect volatile compounds of PNP powder and induced off-flavor, including hexanal, which can be used as the detection indicator for the quality control of PNP powder. PRACTICAL APPLICATIONS: In the present study, we controlled the influence of moisture migration on PNP powder and investigated microorganisms' effects on volatile compounds of PNP powder. HS-GC-IMS could be used to establish fingerprints of volatile compounds in PNP powder. 16S rDNA amplicon sequencing method could be used to screen the dominant spoilage bacteria in PNP powder and established essential spoilage microorganisms of PNP powder. This work provides a reference for category identification of PNP powder, which was infected by spoilage bacteria or not, and stored at day 0 or 30 days. Hexanal can be considered as the volatile marker compound generated from microorganisms. It helps to realize the controllability of PNP powder storage and prolongs the shelf life of PNP powder.

Food safety and quality assessment: comprehensive review and recent trends in the applications of ion mobility spectrometry (IMS)

Ion mobility spectrometry (IMS) is an analytical separation and diagnostic technique that is simple and sensitive and a rapid response and low-priced technique for detecting trace levels of chemical compounds in different matrices. Chemical agents and environmental contaminants are successfully detected by IMS and have been recently considered to employ in food safety. In addition, IMS uses stand-alone or coupled analytical diagnostic tools with chromatographic and spectroscopic methods. Scientific publications show that IMS has been applied 21% in the pharmaceutical industry, 9% in environmental studies and 13% in quality control and food safety. Nevertheless, applications of IMS in food safety and quality analysis have not been adequately explored. This review presents the IMS-related analysis and focuses on the application of IMS in food safety and quality. This review presents the important topics including detection of traces of chemicals, rate of food spoilage and freshness, food adulteration and authenticity as well as natural toxins, pesticides, herbicides, fungicides, veterinary, and growth promoter drug residues. Further, persistent organic pollutants (POPs), acrylamide, polycyclic aromatic hydrocarbon (PAH), biogenic amines, nitrosamine, furfural, phenolic compounds, heavy metals, food packaging materials, melamine, and food additives were also examined for the first time. Therefore, it is logical to predict that the application of the IMS technique in food safety, food quality, and contaminant analysis will be impressively increased in the future. HighlightsCurrent status of IMS for residues and contaminant detection in food safety.To assess all the detected contaminants in food safety, for the first time.Identified IMS-related parameters and chemical compounds in food safety control.

Recent applications of ion mobility spectrometry in natural product research

Ion mobility spectrometry (IMS) is a rapid separation technique capable of extracting complementary structural information to chromatography and mass spectrometry (MS). IMS, especially in combination with MS, has experienced inordinate growth in recent years as an analytical technique, and elicited intense interest in many research fields. In natural product analysis, IMS shows promise as an additional tool to enhance the performance of analytical methods used to identify promising drug candidates. Potential benefits of the incorporation of IMS into analytical workflows currently used in natural product analysis include the discrimination of structurally similar secondary metabolites, improving the quality of mass spectral data, and the use of mobility-derived collision cross-section (CCS) values as an additional identification criterion in targeted and untargeted analyses. This review aims to provide an overview of the application of IMS to natural product analysis over the last six years. Instrumental aspects and the fundamental background of IMS will be briefly covered, and recent applications of the technique for natural product analysis will be discussed to demonstrate the utility of the technique in this field.