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

Analysis and discrimination of adhesive species using ATR-FTIR combined with Raman, and HS-GC-IMS together with multivariate statistical analysis

Identifying the species and origin of adhesives in criminal investigations aids in narrowing inquiry scope and supporting case detection. This study introduces two advanced combined analytical techniques for distinguishing adhesive species, including attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with Raman spectroscopy, and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) together with multivariate statistical analysis. ATR-FTIR categorized seven adhesives into three groups based on the base materials, with further differentiation achieved via Raman spectra. Analysis of volatile components identified 79 volatile organic compounds (VOCs), with esters being the most concentrated. The fingerprint profile clearly illustrated the characteristic fingerprint sequence and unique marker compounds of each adhesive, effectively enabling their differentiation. Multivariate statistical analysis methods, including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), heatmap, and hierarchical cluster analysis (HCA), were utilized to visually interpret the classification of adhesives. This integrated analytical approach provides a comprehensive analysis of adhesive compositions, facilitating the diversification and precision of adhesive species identification, and broadening the scope for detecting and analyzing trace evidence in forensic science.

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Use of GC-IMS and Stoichiometry to Characterize Flavor Volatiles in Different Parts of Lueyang Black Chicken during Slaughtering and Cutting

Chilled and cut chicken is preferred by consumers for its safeness and readiness to cook. To evaluate the quality characteristics of various chilled chicken products, differences in volatile organic components (VOCs) of six different cut parts (breast, back, leg, heart, liver, and gizzard) of Lueyang black chicken were characterized through gas chromatography-ion mobility spectroscopy (GC-IMS) combined with stoichiometry. A total of 54 peaks in the signal of VOCs were detected by GC-IMS, and 43 VOCs were identified by qualitative analysis. There were 22 aldehydes (20.66-54.07%), 8 ketones (25.74-62.87%), 9 alcohols (4.17-14.69%), 1 ether (0.18-2.22%), 2 esters (0.43-1.54%), and 1 furan (0.13-0.52%), in which aldehydes, ketones, and alcohols were the main categories. Among the six cut parts, the relative content of aldehydes (54.07%) was the highest in the gizzard, and the relative content of ketones (62.87%) was the highest in the heart. Meanwhile, the relative content of alcohols (14.69%) was the highest in the liver. Based on a stable and reliable predictive model established by orthogonal partial least squares-discriminant analysis (OPLS-DA), 3-hydroxy-2-butanone (monomer and dimer), acetone, 2-butanone monomer, hexanal (monomer and dimer), isopentyl alcohol monomer, and n-hexanol monomer were picked out as characteristic VOCs based on variable importance in projection (VIP value > 1.0, p < 0.05). Principal component analysis (PCA) and the clustering heatmap indicated that the characteristic VOCs could effectively distinguish the six cut parts of Lueyang black chicken. The specific VOCs responsible for flavor differences among six different cut parts of Lueyang black chicken were hexanal (monomer and dimer) for the gizzard, 2-butanone monomer and hexanal dimer for the breast, hexanal monomer for the back, 3-hydroxy-2-butanone monomer for the leg, 3-hydroxy-2-butanone (monomer and dimer) for the heart, and acetone and isopentyl alcohol monomer for the liver. These findings could reveal references for quality assessment and development of chilled products related to different cut parts of Lueyang black chicken in the future.

Characterization of flavor volatiles in raw and cooked pigmented onion (Allium cepa L) bulbs: A comparative HS-GC-IMS fingerprinting study

Variations in volatile flavor components in pigmented onion bulbs (purple, white, and yellow) before and after cooking were characterized by headspace gas chromatography-ion migration spectrometry (HS-GC-IMS) to investigate their odor traits. Results showed that 39 and 45 volatile flavor compounds were identified from pigmented onion bulbs before and after cooking via the HS-GC-IMS fingerprinting, respectively. Sulfurs (accounting for 50.65%-63.42%), aldehydes (13.36%-22.11%), and alcohols (11.32%-17.94%) ranked the top three prevailing compound categories in all pigmented onions (both raw and cooked). Compared to the raw colored onion bulbs, the relative proportion of sulfurs in cooked onions decreased, whereas the relative proportion of alcohols, esters, pyrazines, and furans increased. Two reliable prediction models were established through orthogonal partial least squares-discriminant analysis (OPLS-DA), and 8 and 22 distinctive odor compounds were sieved out by variable importance in projection (VIP>1.0) as volatile labels, respectively. Both principal component analysis (PCA) and clustering heatmap exhibited favorable distinguishing effects for various pigmented onion bulbs before and after cooking. These results might offer insights into understanding the odor characteristics of different pigmented onions.

Exploration of Raw Pigmented-Fleshed Sweet Potatoes Volatile Organic Compounds and the Precursors

Sweet potato provides rich nutrients and bioactive substances for the human diet. In this study, the volatile organic compounds of five pigmented-fleshed sweet potato cultivars were determined, the characteristic aroma compounds were screened, and a correlation analysis was carried out with the aroma precursors. In total, 66 volatile organic compounds were identified. Terpenoids and aldehydes were the main volatile compounds, accounting for 59% and 17%, respectively. Fifteen compounds, including seven aldehydes, six terpenes, one furan, and phenol, were identified as key aromatic compounds for sweet potato using relative odor activity values (ROAVs) and contributed to flower, sweet, and fat flavors. The OR sample exhibited a significant presence of trans-β-Ionone, while the Y sample showed high levels of benzaldehyde. Starch, soluble sugars, 20 amino acids, and 25 fatty acids were detected as volatile compounds precursors. Among them, total starch (57.2%), phenylalanine (126.82 ± 0.02 g/g), and fatty acids (6.45 μg/mg) were all most abundant in Y, and LY contained the most soluble sugar (14.65%). The results of the correlation analysis revealed the significant correlations were identified between seven carotenoids and trans-β-Ionone, soluble sugar and nerol, two fatty acids and hexanal, phenylalanine and 10 fatty acids with benzaldehyde, respectively. In general, terpenoids and aldehydes were identified as the main key aromatic compounds in sweet potatoes, and carotenoids had more influence on the aroma of OR than other cultivars. Soluble sugars, amino acids, and fatty acids probably serve as important precursors for some key aroma compounds in sweet potatoes. These findings provide valuable insights for the formation of sweet potato aroma.

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.

Effect of raw material frozen storage on physicochemical properties and flavor compounds of fermented mandarin fish (Siniperca chuatsi)

Frozen mandarin fish (MF) is utilized for preparation fermented MF. However, how raw material (RM) affects the quality and flavor of fermented MF is unclear. This study investigated the impact and mechanism of RM frozen storage on the microstructure, texture, water distribution, and flavor of fermented MF by light microscopy, texture profile analysis, low-field nuclear magnetic resonance, gas chromatography-ion mobility spectrometry, and multivariate analysis. With increasing RM frozen storage time, both frozen MF and frozen-based fermented MF decreased in muscle fiber density while increased in muscle fiber diameter. Additionally, RM frozen storage exhibited a significant impact on the water distribution of frozen MF, while no obvious effect on that of frozen-based fermented MF. Seven odorant (2-methyl-1-propanol, 3-hydroxy-2-butanone, 2,3-butanedione, hexanal-D, ethyl acetate-D, 3-pentanone, and acetone) were shown as potential markers to distinguish fermented MF. This study could provide a theoretical basis for the production of high-quality frozen-based fermented MF.

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.

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.