Metagenomics reveals the differences in flavor quality of rice wines with Hongqu and Maiqu as the fermentation starters.

Chinese rice wine (CRW) is an alcoholic beverage made mainly from rice or grain through saccharification and fermentation with Jiuqu (starter). Jiuqu makes an important contribution to the formation of the flavor characteristics of rice wine. Hongqu and Maiqu are two kinds of Jiuqu commonly used in CRW brewing. This study compared the microbial community, biogenic amines (BAs), and volatile flavor components (VFCs) of two types of rice wine brewed with Hongqu and Maiqu as fermentation agents. The results showed that the amino acid content of rice wine fermented with Maiqu (MQW) was significantly lower than that of rice wine fermented with Hongqu (HQW). On the contrary, the majority of BAs in MQW were significantly higher than those in HQW, except for putrescine. Multivariate statistical analysis indicated that most of the VFCs detected were enriched in HQW, while ethyl 3-phenylpropanoate and citronellol were enriched in MQW. The results of metagenomic analysis showed that Weissiella, Enterobacter, Leuconostoc, Kosakonia, Saccharomyces, Aspergilus and Monascus were identified as the predominant microbial genera in HQW brewing process, while Saccharopolyspora, Lactococcus, Enterobacter, Leuconostoc, Kosakonia, Pediococcus, Pantoea, Saccharomyces, Aspergillus, Lichtheimia and Nakaseomyces were the predominant microbial genera in MQW brewing. In addition, some VFCs and BAs were strongly correlated with dominant microbial genera in HQW and MQW brewing. Bioinformatics analysis showed that the abundance of genes involved in BAs synthesis in MQW brewing was much higher than that in HQW brewing, while the abundances of genes related to metabolic pathway of characteristic VFCs in HQW brewing were obviously higher than those in MQW, which explained the differences in flavor quality between HQW and MQW from the perspective of microbial genes. Collectively, these findings provide scientific evidence for elucidating the contribution of different microbial genera to the formation of flavor quality of CRW, and is helpful for screening beneficial microbes to enhance flavor quality and drinking comfort of CRW.

Influence of spatial and temporal diversity and succession of microbial communities on physicochemical properties and flavor substances of soy sauce.

In this study, the influence and relationship between the microbial structure composition at different spatial locations during soy sauce fermentation and the quality of soy sauce were investigated. Within 3-7 days of fermentation, the abundance of Chromohalobacter in the surface and upper layers of moromi was initially high but subsequently decreased. In contrast, Tetragenococcus exhibited low abundance on the surface of moromi at the beginning of fermentation but emerged as the absolute dominant bacteria by the end of the fermentation process. Throughout the fermentation period of 3-42 days, Staphylococcus and Bacillus were the predominant bacterial genera observed at the bottom of the moromi. In addition, Halanaerobium was the dominant bacterial genus in the crude soy sauce layer throughout the fermentation process. Tetragenococcus and Zygosaccharomyces were strongly positively correlated with total acid and ammonia nitrogen. Bacillus and Staphylococcus were significantly negatively correlated with the salt content.

Comparison of Flavor Differences between the Juices and Wines of Four Strawberry Cultivars Using Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry and Sensory Evaluation.

Fruit wine production is a practical approach for extending the shelf life and enhancing the value of strawberries (Fragaria × ananassa). Fruit cultivars and juices are important sources of volatile organic compounds (VOCs) that determine fruit wine sensory quality. In this study, VOCs in the juices and wines of four strawberry cultivars were identified using two-dimensional gas chromatography-time-of-flight mass spectrometry, and a sensory analysis of the wines was performed. A total of 1028 VOCs were detected. PCA and OPLS-DA distinguished the four cultivars from which the juices and wines were made. Six VOCs with variable importance in projection values greater than one were the main aroma and flavor components of strawberry wines. ZJ wine had the highest sensory scores for coordination (9.0) and overall evaluation (8.9) among the 18 descriptors of strawberry wine evaluated. Overall, the ZJ wine had the highest alcohol content (13.25 ± 0.59%, v/v) and sensory evaluation score, indicating that the ZJ cultivar is more suitable for fermentation. This study reflects the differences between wines made from four strawberry cultivars and provides a reference for brewing fruit wines.

Changes in the Volatile Flavor Substances, the Non-Volatile Components, and the Antioxidant Activity of Poria cocos during Different Drying Processes.

Poria cocos (Schw.) wolf (P. cocos) is an important medicinal material with both therapeutic and edible properties. This study investigated volatile constituents, amino acids, proteins, polysaccharides, triterpenoid ingredients, and alcohol-soluble extracts on P. cocos during eight drying processes. A total of 47 volatile components were found and identified; the main volatile components of shade drying (SD) and hot-air drying at 50 °C (HD50) were esters and alcohols, while for drying in hot air at 60 °C~100 °C (△ = 10 °C) and infrared drying (ID), the main compounds were aldehydes and hydrocarbons. The amino acids in P. cocos remained the same when dried with various methods. Compared with SD samples, with the temperature increase, the content of amino acids showed a trend of first decreasing and then increasing, while the content trend of proteins was the opposite. The HD70 samples had the highest content of polysaccharide, triterpenoid ingredients, alcohol-soluble extracts, and antioxidant activity. Furthermore, volatile compounds showed a correlation between non-volatile constituents. This research provides evidence that the aroma, active components, and activity of P. cocos were affected by the drying method.

Dynamic Changes and Potential Correlations between Microbial Diversity and Volatile Flavor Compounds in Chinese Medium-Temperature Daqu during Manufacturing.

To investigate the dynamic changes and potential correlations between microbial diversity and volatile organic compounds (VOCs) during Chinese medium-temperature Daqu (MTD) manufacturing at different key stages, in this study, high-throughput sequencing (HTS) and gas chromatography-ion mobility spectrometry (GC-IMS) were employed to analyze the microbial diversity and VOCs of MTD, respectively. The results showed that Weissella, Staphylococcus, Thermoactinomyces, Kroppenstedtia, and Lactobacillus were the dominant bacterial genera, while Aspergillus, Alternaria, Thermoascus, Thermomyces, Wickerhamomyces, and Saccharomyces were the dominant fungal genera. A total of 61 VOCs were detected by GC-IMS, among which, 13 differential VOCs (VIP > 1) were identified, that could be used as potential biomarkers to judge the fermentation stage of MTD. Kroppenstedtia and Saccharopolyspora were positively correlated with 3-methyl-2-butenal and 2,2,4,6,6-pentamethylheptane-D, respectively, and both of these were positively correlated with butanal-D. Acetobacter, Streptomyces, and lactic acid bacteria (LAB) including Leuconostoc, Pediococcus, Weissella, and Lactobacillus were negatively correlated with their associated VOCs, while fungi were generally positively correlated with VOCs. Wickerhamomyces, Saccharomyces, and Candida were positively correlated with butan-2-one-M. This study provides a theoretical basis for explaining the mechanisms of MTD flavor formation and screening functional microorganisms to improve the quality of MTD.

Characterization of cooked cheese flavor: Volatile components.

The aim of this work was to identify volatiles that contribute to the aroma of cooked cheese, including the role of fat content in their development during cooking. Volatiles and odorants in cooked mature Cheddar were identified using a combination of SPME (solid-phase microextraction)/GC-O (gas chromatography-olfactometry) and SPME/GC-MS (gas chromatography-mass spectrometry). A selection of the odorants was quantitated in six cheeses, uncooked and cooked, (mature Cheddar, high-, medium-, and low-fat mild Cheddar, mozzarella, and Parmesan). Many compounds showed significant differences between cooked and uncooked cheese; Strecker aldehydes, pyrazines, and furanones were all significantly higher in cooked cheeses than in uncooked cheese, while ethyl esters (key odorants in uncooked cheese) were not detected in any of the cooked cheese. Principal component analysis demonstrated that fat concentration in mild Cheddar was positively correlated with the formation of potential odorants (the Strecker aldehydes, methanethiol, 2-methylketones, and fatty acids) upon cooking. Potential lipid precursors for these compounds are discussed. PRACTICAL APPLICATION: This research can be used by the dairy industry to develop better cheeses, especially low- and reduced-fat cheeses, for use in cooked applications such as toppings for pizzas and ready meals. Alternatively, this research describes key volatile compounds in cooked cheese that can be used by the flavoring industry to develop authentic cooked cheese flavorings.

The Influence of Maceration and Flavoring on the Composition and Health-Promoting Properties of Roasted Coffee.

Over the years, many methods of refining green beans have been developed, including maceration aimed at enriching the coffee aroma and improving the overall quality. This study aimed to evaluate the influence of different methods of maceration (fruit and wine) and the addition of food flavors to coffee beans on antioxidant activity, caffeine, phenolic and organic acid content, as well as health-promoting properties. This research showed that the use of the maceration in melon and apple fruit pulp (100 g of fruit pulp per 100 g of green coffee, incubated for 24 h, coffee roasting at 230 °C, control trial roasted coffee) ensured the highest polyphenol (hydroxycinnamic acids and their esters-chlorogenic acids) content (in melon pulp-13.56 g/100 g d.b. (dry bean); in apple pulp-13.22 g/100 g d.b., p < 0.05 (one-way ANOVA)) and antioxidant activity. Melon (92.11%, IC50 = 3.80 mg/mL extract) and apple (84.55%, IC50 = 4.14 mg/mL) showed the highest α-amylase (enzyme concentration 10 µmol/mL) inhibition activity (0.5 mg/mL for both fruits). The addition of food flavors reduced the total content of chlorogenic acids to the range of 4.64 to 6.48 g/100 g d.b. and increased the content of acrylamide and 5-HMF, which positively correlated with a low antioxidant potential compared to the macerated samples and the control. Studies have shown that coffee macerated in the pulp of melon and apple fruit, due to its great potential to inhibit α-amylase in vivo, may have a preventive effect on type II diabetes. This study complements the current knowledge on the potential health-promoting properties of coffee flavored using different methods; further research should include more advanced models for testing these health-promoting properties. Statistical analysis was based on the determination of the average values of six measurements and their standard deviation, as well as on the one-way ANOVA (analysis of variation) and the Pearson correlation coefficient, using Statistic 10.0 software. The significance was defined at p ≤ 0.05.

Applications of an Electrochemical Sensory Array Coupled with Chemometric Modeling for Electronic Cigarettes.

This study investigates the application of an eNose (electrochemical sensory array) device as a rapid and cost-effective screening tool to detect increasingly prevalent counterfeit electronic cigarettes, and those to which potentially hazardous excipients such as vitamin E acetate (VEA) have been added, without the need to generate and test the aerosol such products are intended to emit. A portable, in-field screening tool would also allow government officials to swiftly identify adulterated electronic cigarette e-liquids containing illicit flavorings such as menthol. Our approach involved developing canonical discriminant analysis (CDA) models to differentiate formulation components, including e-liquid bases and nicotine, which the eNose accurately identified. Additionally, models were created using e-liquid bases adulterated with menthol and VEA. The eNose and CDA model correctly identified menthol-containing e-liquids in all instances but were only able to identify VEA in 66.6% of cases. To demonstrate the applicability of this model to a commercial product, a Virginia Tobacco JUUL product was adulterated with menthol and VEA. A CDA model was constructed and, when tested against the prediction set, it was able to identify samples adulterated with menthol 91.6% of the time and those containing VEA in 75% of attempts. To test the ability of this approach to distinguish commercial e-liquid brands, a model using six commercial products was generated and tested against randomized samples on the same day as model creation. The CDA model had a cross-validation of 91.7%. When randomized samples were presented to the model on different days, cross-validation fell to 41.7%, suggesting that interday variability was problematic. However, a subsequently developed support vector machine (SVM) identification algorithm was deployed, increasing the cross-validation to 84.7%. A prediction set was challenged against this model, yielding an accuracy of 94.4%. Altered Elf Bar and Hyde IQ formulations were used to simulate counterfeit products, and in all cases, the brand identification model did not classify these samples as their reference product. This study demonstrates the eNose's capability to distinguish between various odors emitted from e-liquids, highlighting its potential to identify counterfeit and adulterated products in the field without the need to generate and test the aerosol emitted from an electronic cigarette.

Exploration of the flavor diversity of oolong teas: A comprehensive analysis using metabolomics, quantification techniques, and sensory evaluation.

The taste profile of oolong tea is intricately shaped by origins and roasting. Herein, a comprehensive approach integrating non-targeted metabolomics, quantitative analysis and sensory evaluations was employed to analyze the taste profile of oolong tea. 25 selected representative oolong teas, including Southern Fujian (MN), Northern Fujian (MB), and Taiwan (TW), were meticulously were classified into SX-RG-DD, GS, and TGY based on the chemical taste phenotypes. A total of 314 non-volatile compounds were identified, among which 87 and 77 compounds, including catechin, theaflavins, flavonoids and amino acids were screened as critical taste metabolites responsible for regions and roasting degree, respectively. The reduction of bitter and astringent, coupled with the enhancement of umami, sweet and sweet aftertaste exhibited a correlation with the decrease in (-)-epigallocatechin (EGC), (-)-epicatechin (EC), (-)-epicatechin gallate (ECG) and (-)-epigallocatechin gallate (EGCG), while the increase in catechin (C). These findings provide insights for further research on optimizing tea quality and refining processing techniques.

Characterization and Profiling of Key Odorants in Roasted Hybrid American-European Hazelnuts.

American-European hybrid hazelnuts (Corylus americana × Corylus avellana) are an emerging crop in the Upper Midwest of the United States that have been reported to have unique sensory characteristics compared to traditionally grown European hazelnuts. In this study, key odor-active compounds in a roasted hybrid hazelnut variety (C. americana × C. avellana) were identified and profiled across different hybrid hazelnut varietals to understand sensory differences. Gas chromatography/mass spectrometry/olfactometry analysis identified 33 odorants with high flavor dilution factors (FD ≥ 16) in the roasted hybrid hazelnut, including 2-acetylpyrazine and 2-aminoacetophenone as first reported hazelnut odorants. Descriptive sensory analysis profiles of the roasted hazelnut and an aroma recombination model consisting of 27 odorants quantified above their odor detection thresholds were not significantly different for the six evaluated attributes, confirming the aroma contribution of the identified odorants. Variation in all 33 aroma-active compounds across 12 hybrid and two European hazelnut varieties was visualized through principal component analysis and related to aroma profiles previously characterized by consumers.

Two flavors in adulterated sesame oil: discovery, confirmation, and content regularity study.

Exploring and accurately detecting new adulteration markers in sesame oil is an important measure for sesame oil adulteration monitoring. In this study, two endogenous flavors sulfurol and γ-nonalactone which can be used as potential adulteration markers were first discovered in sesame oil and accurately quantified. First, the two endogenous flavors were discovered using gas chromatography-mass spectrometry (GC-MS), and their structures were confirmed by comparing the mass spectrograms with the NIST spectral library. Then the liquid chromatography-tandem mass spectrometry (LC-MS/MS) method using direct methanol extraction pretreatment and vanillin-D3 as an internal standard was developed for rapid quantitation and application. The method was successfully validated with recoveries ranging from 88.5% to 102.2% and relative standard deviations between 2.6% and 10.5% (n = 6). The combined method of GC-MS and LC-MS/MS was indicated to be efficient and highly sensitive for detection of sulfurol and γ-nonalactone in edible oil. Subsequently, 31 sesame oils from the market were detected, revealing that 31 samples contained the identified flavors within a relatively consistent range. However, the concentration of these flavor substances in one sample was abnormally high, indicating that there was a potential risk of adulteration. Therefore, the developed method shows good potential for quality evaluation and adulteration screening of sesame oil.

Volatile flavor profiles of douchis from different origins and varieties based on GC-IMS and GC-O-QTOF/MS analysis.

The present study comprehensively characterized the flavor differences between different varieties of douchis from different origins using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) coupled with gas chromatography-olfactometry-quadrupole time-of-flight mass spectrometry (GC-O-QTOF/MS). A total of 91 volatile organic compounds (VOCs) were identified using HS-GC-IMS and 70 VOCs were identified using GC-O-QTOF/MS, mainly including acids, aldehydes, esters and alcohols. Additionally, 23 key aroma-presenting compounds were screened in five douchi species using relative odor activity value (ROAV) and the aroma compounds that contributed the most to the aroma varied among the five douchi species. Comparative analysis of the GC-IMS and GC-O-QTOF/ MS results yielded 13 VOCs that were detected by both techniques. Nonanal, hexanal, eucalyptol, 1-octen-3-ol, isoamyl acetate, and 2-pentylfuran were identified as key VOCs in the douchi species using both methods. These findings will provide deeper insights for exploring flavor differences in douchi from different geographic sources.

The changes of fungal community and flavor substances in Yunnan-style sausages: A comparative analysis of different drying methods.

This study aimed to investigate alterations in the fungal community and flavor substances in Yunnan-style sausages subjected to natural air-dried fermentation (NF), variable-temperature drying (VT), and constant-temperature drying (CT) and analyze the potential relationship between fungal community and flavor substances. The findings revealed that the NF group and VT group were more conducive to enhancing the accumulation of dominant fungi and characteristic flavor substances in Yunnan-style sausages. Glu, Ala, His, and Lys were identified as key taste substances based on their taste activity values (TAV ≥ 1). A total of 272 volatile compounds(VOCS) were detected in the sausage samples, while 28 key aroma compounds were screened based on the odor activity value (OAV ≥ 1). Multivariate statistical analysis showed that 12 key aroma compounds (VIP > 1) could be considered discriminative compounds, including (E,E)-2,4-nonadienal, nonanal, heptanal, benzaldehyde, Dodecanal, cyclohexanol, and hexyl-Benzene, etc. Furthermore, Wickerhamoomyces and Debaryomyces were positively correlated with most of the key flavor substances and physicochemical indices (|r| > 0.6, P < 0.05), which were potential flavor-contributing fungi in Yunnan-style sausages.

A comparative study to determine the key aroma components of yogurt aroma types based on Sensomics and Flavoromics.

This study used Sensomics to examine four previously obtained yogurt aroma type profiles. 14 key aroma-active compounds were identified as significant contributors (p ≤ 0.05) in the four aroma types using gas chromatography-mass spectrometry-olfactometry (GC-MS/O), aroma extract dilution analysis (AEDA), odor activity values (OAV), and aroma recombination and omission experiments. The Sensomics and previous Flavoromics results were compared, showing that Flavoromics identified 10 indicator compounds for distinguishing aroma types. Eight were the same as the key aroma-active compounds identified via Sensomics, namely acetic acid, pentanoic acid, decanoic acid, 3-hydroxy-2-butanone, 2,3-pentanedione, acetaldehyde, δ-decalactone, and dimethyl sulfone. Sensomics revealed a prominent similarity between the categories of key aroma-active compounds of the four aroma types, with a higher sensory contribution. Flavoromics showed less overlapping between the indicator compounds, mainly related to the distinction between the four aroma types. Sensomics and Flavoromics serve distinct research objectives and should be selected according to the study subject.

Characterization of the key odorants in goji wines in three levels of sweetness by applications of sensomics approach.

The correlations and differences of the key odorants were systematically conducted among three sweetness of goji wines by the sensomics approach. After aroma (extract) dilution analysis, 67, 67, and 66 odorants were screened in sweet goji wine, semi-dry goji wine, and dry goji wine, in which, 63 odorants were identified in all goji wines. Determination of 53 odorants revealed a total of 30 odorants with the concentrations surpassing their olfactory thresholds. Overall, the odor activity values (OAVs) of ketones decreased, while esters, alcohols, phenols, and aldehydes increased with the decrease in sweetness in goji wine samples. Nevertheless, (E)-ß-damascenone, trans- and cis-whisky lactones, and 3-methyl-2,4-nonanedione, evoked cooked apple-like, coconut-like, and hay-like odor impressions in goji wines and showed the highest OAVs. A reliable evaluation of the aroma contributions was executed as aroma recombinations and suggested a successful evaluation of key odorants in goji wines.

Effects of different thermal methods and degrees on the flavor of channel catfish (Ictalurus punctatus) fillets: Fatty acids, volatile flavor and taste compounds.

The effects of different thermal processing conditions on the flavor profiles of channel catfish were evaluated in terms of fatty acids, volatile flavor and taste compounds using steaming, boiling, roasting, and microwaving with different degrees. After thermal processing, 72 volatile organic compounds were detected, including 20 hydrocarbons, 5 ketones, 20 aldehydes, 7 heterocyclic compounds, 12 alcohols and others. Meanwhile, the contents of unsaturated fatty acids like oleic acid and linoleic showed a significant decline due to their heat-sensitive properties. With regard to taste compounds, thermal processing contributed to umami amino acids and free nucleotides conversion, with the initial glutamate and IMP contents of 15.87 and 164.91 mg/100 g in raw samples mainly increasing by 2.8-10.3 and 14.4-105.5 mg/100 g in processed ones. Compared to other methods, microwaving had limited effects on flavor compounds, and steaming and roasting had better performance to improve the flavor complexity of channel catfish.

[Rapid determination of nine preservatives in tobacco flavor by three phase-hollow fiber-liquid phase microextraction-high performance liquid chromatography].

Tobacco flavors are extensively utilized in traditional tobacco products, electronic nicotine, heated tobacco products, and snuff. To inhibit fungal growth arising from high moisture content, preservatives such as benzoic acid (BA), sorbic acid (SA), and parabens are often incorporated into tobacco flavors. Nonetheless, consuming preservatives beyond safety thresholds may pose health risks. Therefore, analytical determination of these preservatives is crucial for both quality assurance and consumer protection. For example, BA and SA can induce adverse reactions in susceptible individuals, including asthma, urticaria, metabolic acidosis, and convulsions. Parabens, because of their endocrine activity, are classified as endocrine-disrupting chemicals. Despite extensive research, the concurrent quantification of trace-level hydrophilic (BA and SA) and hydrophobic (methylparaben, ethylparaben, isopropylparaben, propylparaben, butylparaben, isobutylparaben, and benzylparaben) preservatives in tobacco flavors remains challenging. Traditional liquid phase extraction coupled with high performance liquid chromatography (HPLC) often results in high false positive rates and inadequate sensitivity. In contrast, tandem mass spectrometry offers high sensitivity and specificity; however, its widespread application is limited by laborious sample preparation and significant operational costs. Therefore, it is crucial to establish a fast and sensitive sample pretreatment and analysis method for the nine preservatives in tobacco flavors. In this study, a method for the simultaneous determination of the nine preservatives (SA, BA and seven parabens) in tobacco flavor was established based on three phase-hollow fiber-liquid phase microextraction (3P-HF-LPME) technology combined with HPLC. To obtain the optimal pretreatment conditions, extraction solvent type, sample phase pH, acceptor phase pH, sample phase volume, extraction time, and mass fraction of sodium chloride, were examined. Additionally, the HPLC parameters, including UV detection wavelength and mobile phase composition, were refined. The optimal extraction conditions were as follows: dihexyl ether was used as extraction solvent, 15 mL sample solution (pH 4) was used as sample phase, sodium hydroxide aqueous solution (pH 12) was used as acceptor phase, and the extraction was carried out at 800 r/min for 30 min. Chromatographic separation was accomplished using an Agilent Poroshell 120 EC-C18 column (100 mm×3 mm, 2.7 µm) and a mobile phase comprising methanol, 0.02 mol/L ammonium acetate aqueous solution (containing 0.5% acetic acid), and acetonitrile for gradient elution. Under the optimized conditions, the nine target analytes showed good linear relationships in their respective linear ranges, the correlation coefficients (r) were ≥0.9967, limits of detection (LODs) and quantification (LOQs) were 0.02-0.07 mg/kg and 0.08-0.24 mg/kg, respectively. Under two spiked levels, the enrichment factors (EFs) and extraction recoveries (ERs) of the nine target analytes were 30.6-91.1 and 6.1%-18.2%, respectively. The recoveries of the nine target analytes ranged from 82.2% to 115.7% and the relative standard deviations (RSDs) (n=5) were less than 14.5% at low, medium and high levels. The developed method is straightforward, precise, sensitive, and well-suited for the rapid screening of preservatives in tobacco flavor samples.

[Application of ion chromatographic fingerprint analysis for quality evaluation of tobacco flavors].

Tobacco flavor, an important tobacco additive, is an essential raw material in cigarette production that can effectively improve the quality of tobacco products, add aroma and taste, and increase the suction flavor. The quality consistency of tobacco flavors affects the quality stability of branded cigarettes. Therefore, the quality control of tobacco flavors is a major concern for cigarette and flavor manufacturers. Physical and chemical indices, odor similarity, and sensory efficacy are employed to evaluate the quality of tobacco flavors, and the analysis of chemical components in tobacco flavors is usually conducted using gas chromatography (GC) and high performance liquid chromatography (HPLC). However, because the composition of tobacco flavors is complex, their quality cannot be fully reflected using a single component or combination of components. Therefore, establishing an objective analytical method for the quality control of tobacco flavors is of extreme importance. Chromatographic fingerprint analysis is routinely used for the discriminative analysis of tobacco flavors. Chromatographic fingerprints refer to the general characteristics of the concentration profiles of different chemical compounds. In the daily procurement process, fingerprints established by GC and HPLC are effective for the evaluation and identification of tobacco flavors. However, given continuous improvements in aroma-imitation technology, some flavors with high similarity cannot be directly distinguished using existing methods. In this study, a method for the determination of organic acids and inorganic anions in tobacco flavors based on ion chromatography (IC) was developed to ensure the quality consistency of tobacco flavors. A 1.0 g sample of tobacco flavors and 10 mL of deionized water were mixed and vibrated for 30 min. The aqueous sample solution was passed through a 0.45 µm membrane filter and RP pretreatment column in succession to eliminate interferences and then subjected to IC. Standard solutions containing nine organic acids and seven inorganic anions were used to identify the anions in the tobacco flavors, and satisfactory reproducibility was obtained. The relative standard deviations (RSDs) for retention times and peak areas were <0.71% and <6.02%, respectively. The chromatographic fingerprints of four types of tobacco flavors (samples A-D) from five different batches were obtained. Nine tobacco flavor samples from different manufacturers (samples AY1-AY3, BY1-BY2, CY1-CY2, DY1-DY2) were also analyzed to obtain their chromatographic fingerprints. Hierarchical cluster and similarity analyses were used to evaluate the quality of tobacco flavors from different manufacturers. Hierarchical clustering refers to the process of subdividing a group of samples into clusters that exhibit a high degree of intracluster similarity and intercluster dissimilarity. The dendrograms obtained using SPSS 12.0 indicated good quality consistency among the samples in different batches. Samples AY3, BY2, CY2, and DY1 clustered with the batches of standard tobacco flavors. Therefore, hierarchical cluster analysis can effectively distinguish the quality of products from different manufacturers. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (version 2.0) was used to evaluate the similarity between the standard tobacco flavors and products from different manufacturers. Among the samples analyzed, samples AY3, BY2, CY2, and DY1 showed the highest similarity values (>97.7%), which was consistent with the results of the hierarchical cluster analysis. This finding indicates that IC combined with chromatographic fingerprint analysis could accurately determine the quality of tobacco flavors. GC combined with ultrasonic-assisted liquid-liquid extraction was also used to analyze the tobacco flavors and verify the accuracy of the proposed method. Compared with GC coupled with ultrasonic-assisted liquid-liquid extraction, IC demonstrated more significant quality differences among certain tobacco flavors.

Quality characterization of tobacco flavor and tobacco leaf position identification based on homemade electronic nose.

A set of nine unique tobacco extract samples was analyzed using a self-developed electronic nose (E-nose) system, a commercial E-nose, and gas chromatography-mass spectrometry (GC-MS). The evaluation employed principal component analysis, statistical quality control, and soft independent modeling of class analogies (SIMCA). These multifaceted statistical methods scrutinized the collected data. Subsequently, a quality control model was devised to assess the stability of the sample quality. The results showed that the custom E-nose system could successfully distinguish between tobacco extracts with similar odors. After further training and the development of a quality control model for accepted tobacco extracts, it was possible to identify samples with normal and abnormal quality. To further validate our E-nose and extend its use within the tobacco industry, we collected and accurately classified the flavors of different tobacco leaf positions, with a remarkable accuracy rate of 0.9744. This finding facilitates the practical application of our E-nose system for the efficient identification of tobacco leaf positions.

Comparative Analysis of Commercially Available Flavor Oil Sausages and Smoked Sausages.

This study utilized gas chromatography-ion mobility spectrometry (GC-IMS) to analyze the volatile flavor compounds present in various commercially available sausages. Additionally, it conducted a comparative assessment of the distinctions among different samples by integrating sensory evaluation with textural and physicochemical parameters. The results of the GC-IMS analysis showed that a total of 65 volatile compounds were detected in the four samples, including 12 hydrocarbons, 11 alcohols, 10 ketones, 9 aldehydes, 12 esters, and 1 acids. Fingerprinting combined with principal component analysis (PCA) showed that the volatiles of different brands of sausages were significantly different (p < 0.05). The volatiles of S1 and S4 were more similar and significantly different from the other two samples (p < 0.05). Among them, there were 14 key volatile substances in the four samples, of which 3-hydroxy-2-butanone and diallyl sulfide were common to all four sausages. Combined textural and sensory evaluations revealed that smoked sausages exhibited superior characteristics in resilience, cohesiveness, springiness, gumminess, and chewiness. Additionally, smoked sausages were found to be more attractive in color, moderately spicy, and salty, while having a lower fat content. In conclusion, smoked sausages are preferred by consumers over flavored oil sausages.