Flint glass bottles cause white wine aroma identity degradation.

Due to marketing recommendations, white wines are often bottled in flint glass to improve aesthetics and showcase wine color. Although this practice is known to cause a wine fault, the influence of light on the fruity and flowery aromatic profile of wine is unknown. The aim of this study was to investigate the changes to the white wine volatilome under typical supermarket shelf conditions, using 1,052 bottles of 24 white wines. After only 7 d of shelf life in flint glass bottles, a dramatic loss in terpenes (10 to 30%) and norisoprenoids (30 to 70%) was recorded, whereas colored glass bottles did not evidence such behavior even after 50 d, and darkness preserved the wine's fruity and flowery aromatic integrity. We also proposed an alternative mechanism for the insurgence of the lightstrike off-odor, which takes the varietal aroma loss into account. In light of this understanding of the flint glass negative impact on white wine aroma identity and sensorial character, this packaging should be strongly discouraged. The same findings should be valid for a wide range of several daily consumed foodstuff where transparent packaging is used.

Analysis of VOCs in Urine Samples Directed towards of Bladder Cancer Detection.

Bladder cancer is one of most common types of cancer diagnosed in the genitourinary tract. Typical tests are costly and characterized by low sensitivity, which contributes to a growing interest in volatile biomarkers. Head space solid phase microextraction (SPME) was applied for the extraction of volatile organic compounds from urine samples, and gas chromatography time of flight mass spectrometry (GC×GC TOF MS) was used for the separation and detection of urinary volatiles. A cohort of 40 adult patients with bladder cancer and 57 healthy persons was recruited. Different VOC profiles were obtained for urine samples taken from each group. Twelvecompounds were found only in the samples from theBC group.The proposed candidate biomarkers are butyrolactone; 2-methoxyphenol; 3-methoxy-5-methylphenol; 1-(2,6,6-trimethylcyclohexa-1,3-dien-1-yl)-2-buten-1-one; nootkatone and 1-(2,6,6-trimethyl-1-cyclohexenyl)-2-buten-1-one.Since most of the studies published in the field are proving the potential of VOCs detected in urine samples for the screening and discrimination of patients with bladder cancer from healthy, but rarely presenting the identity of proposed biomarkers, our study represents a novel approach.

Breath metabolome of mice infected with Pseudomonas aeruginosa.

INTRODUCTION: The measurement of specific volatile organic compounds in breath has been proposed as a potential diagnostic for a variety of diseases. The most well-studied bacterial lung infection in the breath field is that caused by Pseudomonas aeruginosa. OBJECTIVES: To determine a discriminatory core of molecules in the "breath-print" of mice during a lung infection with four strains of P. aeruginosa (PAO1, PA14, PAK, PA7). Furthermore, we attempted to extrapolate a strain-specific "breath-print" signature to investigate the possibility of recapitulating the genetic phylogenetic groups (Stewart et al. Pathog Dis 71(1), 20-25, 2014. https://doi.org/10.1111/2049-632X.12107 ). METHODS: Breath was collected into a Tedlar bag and shortly after drawn into a thermal desorption tube. The latter was then analyzed into a comprehensive multidimensional gas chromatography coupled with a time-of-flight mass spectrometer. Random forest algorithm was used for selecting the most discriminatory features and creating a prediction model. RESULTS: Three hundred and one molecules were significantly different between animals infected with P. aeruginosa, and those given a sham infection (PBS) or inoculated with UV-killed P. aeruginosa. Of those, nine metabolites could be used to discriminate between the three groups with an accuracy of 81%. Hierarchical clustering showed that the signature from breath was due to a specific response to live bacteria instead of a generic infection response. Furthermore, we identified ten additional volatile metabolites that could differentiate mice infected with different strains of P. aeruginosa. A phylogram generated from the ten metabolites showed that PAO1 and PA7 were the most distinct group, while PAK and PA14 were interspersed between the former two groups. CONCLUSIONS: To the best of our knowledge, this is the first study to report on a 'core' murine breath print, as well as, strain level differences between the compounds in breath. We provide identifications (by running commercially available analytical standards) to five breath compounds that are predictive of P. aeruginosa infection.

Metabolic Changes of Amino Acids and Flavonoids in Tea Plants in Response to Inorganic Phosphate Limitation.

The qualities of tea (Camellia sinensis) are not clearly understood in terms of integrated leading molecular regulatory network mechanisms behind inorganic phosphate (Pi) limitation. Thus, the present work aims to elucidate transcription factor-dependent responses of quality-related metabolites and the expression of genes to phosphate (P) starvation. The tea plant organs were subjected to metabolomics analysis by GC×GC-TOF/MS and UPLC-Q-TOF/MS along with transcription factors and 13 metabolic genes by qRT-PCR. We found P starvation upregulated SPX2 and the change response of Pi is highly dependent on young shoots. This led to increased change in abundance of carbohydrates (fructose and glucose), amino acids in leaves (threonine and methionine), and root (phenylalanine, alanine, tryptophan, and tyrosine). Flavonoids and their glycosides accumulated in leaves and root exposed to P limitation was consistent with the upregulated expression of anthocyanidin reductase (EC 1.3.1.77), leucoanthocyanidin dioxygenase (EC 1.4.11.19) and glycosyltransferases (UGT78D1, UGT78D2 and UGT57L12). Despite the similar kinetics and high correlation response of Pi and SPX2 in young shoots, predominating theanine and other amino acids (serine, threonine, glutamate, valine, methionine, phenylalanine) and catechin (EGC, EGCG and CG) content displayed opposite changes in response to Pi limitation between Fengqing and Longjing-43 tea cultivars.

Hepatic and fecal metabolomic analysis of the effects of Lactobacillus rhamnosus GG on alcoholic fatty liver disease in mice.

The interactions among the gut, liver, and immune system play an important role in liver disease. Probiotics have been used for the treatment and prevention of many pathological conditions, including liver diseases. Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) was used herein, in conjunction with chemometric data analysis, to identify metabolites significantly affected by probiotics in mice fed with or without alcohol. The metabolomics analysis indicates that the levels of fatty acids increased in mouse liver and decreased in mouse feces when mice were chronically exposed to alcohol. Supplementing the alcohol-fed mice with culture supernatant from Lactobacillus rhamnosus GG (LGGs) normalized these alcohol-induced abnormalities and prevented alcoholic liver disease (ALD). These results agree well with previous studies. In addition to diet-derived long chain fatty acids (LCFAs), LGGs may positively modify the gut's bacterial population to stimulate LCFA synthesis, which has been shown to enhance intestinal barrier function, reduce endotoxemia, and prevent ALD. We also found that several amino acids, including l-isoleucine, a branched chain amino acid, were downregulated in the liver and fecal samples from animals exposed to alcohol and that the levels of these amino acids were corrected by LGGs. These results demonstrate that LGGs alleviates alcohol-induced fatty liver by mechanisms involving increasing intestinal and decreasing hepatic fatty acids and increasing amino acid concentration.

Artificial intelligence decision making tools in food metabolomics: Data fusion unravels synergies within the hazelnut (Corylus avellana L.) metabolome and improves quality prediction.

This study investigates the metabolome of high-quality hazelnuts (Corylus avellana L.) by applying untargeted and targeted metabolome profiling techniques to predict industrial quality. Utilizing comprehensive two-dimensional gas chromatography and liquid chromatography coupled with high-resolution mass spectrometry, the research characterizes the non-volatile (primary and specialized metabolites) and volatile metabolomes. Data fusion techniques, including low-level (LLDF) and mid-level (MLDF), are applied to enhance classification performance. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) reveal that geographical origin and postharvest practices significantly impact the specialized metabolome, while storage conditions and duration influence the volatilome. The study demonstrates that MLDF approaches, particularly supervised MLDF, outperform single-fraction analyses in predictive accuracy. Key findings include the identification of metabolites patterns causally correlated to hazelnut's quality attributes, of them aldehydes, alcohols, terpenes, and phenolic compounds as most informative. The integration of multiple analytical platforms and data fusion methods shows promise in refining quality assessments and optimizing storage and processing conditions for the food industry.

Comparative evaluation of physical characteristics and volatile flavor components of Bangia fusco-purpurea subjected to hot air drying and vacuum freeze-drying.

Bangia fusco-purpurea is an economically important seaweed with Fujian characteristics. Given that its harvest is seasonal, drying is often used to remove moisture, extend storage time, and facilitate further processing. Hence, the current study sought to explore the impact of different drying processes on the quality and volatile fingerprints of Bangia fusco-purpurea. To this end, the effects of hot air drying (HAD) and vacuum freeze drying (VFD) on the drying characteristics, microstructure, rehydration, and volatile components of dried B. fusco-purpurea were investigated. The results showed that the water removal efficiency of HAD was significantly higher than that of VFD. However, VFD better preserved the skeletal structure of B. fusco-purpurea than HAD, with a faster rehydration rate and a more uniform cell structure after rehydration. Using electronic nose and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF MS), significant differences in the volatile profiles of fresh, HAD, and VFD B. fusco-purpurea were assessed. E-nose analysis revealed that both HAD and VFD treatments significantly reduced sulfides, aromatic compounds, and nitrogen oxides in fresh B. fusco-purpurea. However, the alcohol, aldehyde, and ketone contents were lower in the VFD samples compared with HAD and fresh samples, whereas the content of methyl flavor substances was significantly higher. GC × GC-TOF MS analysis revealed that the most abundant volatile categories in HAD and VFD were hydrocarbons, alcohols, and esters. The number of volatile components in the HAD samples was significantly lower than in the VFD and fresh samples. As drying progressed, hydrocarbons and alcohols were formed in dried B. fusco-purpurea due to the thermal degradation of carbohydrates, lipids, amino acids, and the Maillard reaction. There were also significant flavor differences between HAD and VFD B. fusco-purpurea. Thus, although HAD exhibits better drying efficiency, VFD has more significant advantages in terms of product quality.

Micron-size tire tread particles leach organic compounds at higher rates than centimeter-size particles: Compound identification and profile comparison.

Tire tread particles (TTP) are environmentally prevalent microplastics and generate toxic aqueous leachate. We determined the total carbon and nitrogen leachate concentrations and chemical profiles from micron (∼32 µm) and centimeter (∼1 cm) TTP leachate over 12 days. Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) were used to measure the concentration of leached compounds. Nontargeted chemical analysis by comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOF-MS) was used to compare the chemical profiles of leachates. After leaching for 12 days, DOC was 4.0 times higher in the micron TTP leachate than in the centimeter TTP leachate, and TDN was 2.6 times higher. The total GC×GC/TOF-MS chromatographic feature peak area was 2.9 times greater in the micron TTP leachate than the centimeter TTP leachate, and similarly, the total relative abundance of 54 tentatively identified compounds was 3.3 times greater. We identified frequently measured tire-related chemicals, such as 6PPD, N-cyclohexyl-N'-phenylurea (CPU), and hexa(methoxymethyl)melamine (HMMM), but nearly 50% of detected chemicals were not previously reported in tire literature or lacked toxicity information. Overall, the results demonstrate that smaller TTP have a greater potential to leach chemicals into aquatic systems, but a significant portion of these chemicals are not well-studied and require further risk assessment.

Application of GC-TOF/MS and GC×GC-TOF/MS to Discriminate Coffee Products in Three States (Bean, Powder, and Brew).

The volatiles in coffee play an important part in the overall flavor profile. In this study, GC-TOF/MS and GC×GC-TOF/MS were used to detect the volatile organic compounds (VOCs) in coffee samples of three different brands at three states (bean, powder, and brew). The differences between the two methods in characterizing VOCs were analyzed using the Venn diagram and PCA (principal component analysis). The important aroma-contributing compounds were further compared and analyzed. The results of the venn diagrams of different coffee samples showed that most VOCs existed in 2-3 kinds of coffee. The PCA of VOCs in different coffee samples showed that the VOCs detected by GC-TOF/MS could distinguish the coffee samples in the different states. GC×GC-TOF/MS was suitable for the further identification and differentiation of the different brands of coffee samples. In addition, pyridine, pyrrole, alcohols, and phenols greatly contributed to distinguishing coffee in three states, and alcohols greatly contributed to distinguishing the three brands of coffee.

Characterization of the differences in aroma-active compounds in strong-flavor Baijiu induced by bioaugmented Daqu using metabolomics and sensomics approaches.

Bioaugmenting Daqu is an effective strategy to improve the quality of Baijiu, but its effect on overall flavor profiles and aroma-active compounds is unknown. Here, 168 volatiles were determined from fresh strong-flavor Baijiu (SFB) and bioaugmented Daqu increased their diversity and altered the flavor characteristics. Among 49 odorants identified by aroma extraction dilution analysis, 29 aroma-active compounds had odor activity values ≥1, of which 18, 8, and 3 components exhibited the highest content in the SFB fermented by fortified-, space- and conventional-Daqu, respectively. The contribution of increasing ethyl hexanoate and decreasing ethyl lactate of fresh SFB by bioaugmented Daqu was confirmed, and their content changed from 4650 and 1890 mg/L (conventional-SFB) to 6680 and 1760 mg/L (fortified-SFB) and 6130 and 1710 mg/L (space-SFB). Meanwhile, the discriminators among different samples were determined by multivariate statistical analysis. These findings are beneficial for the optimization and improvement of Baijiu aroma.

Characterization of selected commercially available grilled lamb shashliks based on flavor profiles using GC-MS, GC × GC-TOF-MS, GC-IMS, E-nose and E-tongue combined with chemometrics.

HS-SPME-GC-MS, SPME-Arrow-GC × GC-TOF-MS, HS-GC-IMS, Electronic-nose, and Electronic-tongue systems were applied in a feasibility study of the flavor characterization of five commercially available Chinese grilled lamb shashliks. A total of 198 volatile organic compounds (VOCs) were identified (∼71% by GC × GC-TOF-MS). Using data fusion strategies, five predictive models were applied to the composition of VOCs and brand identification of the lamb shashliks. Compared with partial least squares regression, support vector machine, deep neural network, and RegBoost modeling, a momentum deep belief network model performed best in predicting VOCs content and identifying shashlik brands (R2 above 0.96, and RMSE below 0.1). Intelligent sensory technology combined with chemometrics is a promising approach to the flavor characterization of shashliks and other food matrices.

In vitro assessment of polychlorinated biphenyl bioaccessibility in meat: Influence of fat content, cooking level and consumer age on consumer uptake.

In a risk assessment perspective, this work aims to assess the bioaccessibility of PCBs in meat. A standardised in vitro static digestion protocol was set up and coupled with extraction, clean-up and GC × GC-ToF/MS multianalyte method to monitor the fate of PCBs in meat during digestion. Starting with spiked meat, PCB bioaccessibility in 11% fat medium-cooked meat varied in adults from 20.6% to 30.5% according to congeners. PCB bioaccessibility increased to 44.2-50.1% in 5% fat meat and decreased to 6.2-9.1% and to 14.6-19.4% in digestion conditions mimicking infants and elderly, respectively. Intense cooking also decreased PCB bioaccessibility to 18.0-26.7%. Bioaccessibility data obtained with spiked meat were validated with measurements carried out in incurred meat samples. Finally, mean uptake distributions are obtained from a modular Bayesian approach. These distributions feature a lower mode when the fat content is higher, the meat is well-done cooked, and the consumers are older.

Persistence and removal of trace organic compounds in centralized and decentralized wastewater treatment systems.

The persistence of trace organic chemicals in treated effluent derived from both centralized wastewater treatment plants (WWTPs) and decentralized wastewater treatment systems (DEWATS) is of concern due to their potential impacts on human and ecosystem health. Here, we utilize non-targeted analysis (NTA) with comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry (GC × GC/TOF-MS) to conduct an evaluation of the common persistent and removed compounds found in two centralized WWTPs in the USA and South Africa and one DEWATS in South Africa. Overall, removal efficiencies of chemicals were similar between the treatment plants when they were compared according to the number of chemical features detected in the influents and effluents of each treatment plant. However, the DEWATS treatment train, which has longer solids retention and hydraulic residence times than both of the centralized WWTPs and utilizes primarily anaerobic treatment processes, was able to remove 13 additional compounds and showed a greater decrease in normalized peak areas compared to the centralized WWTPs. Of the 111 common compounds tentatively identified in all three influents, 11 compounds were persistent in all replicates, including 5 compounds not previously reported in effluents of WWTPs or water reuse systems. There were no significant differences among the physico-chemical properties of persistent and removed compounds, but significant differences were observed among some of the molecular descriptors. These results have important implications for the treatment of trace organic chemicals in centralized and decentralized WWTPs and the monitoring of new compounds in WWTP effluent.

GC × GC-ToF-MS and GC-IMS based volatile profile characterization of the Chinese dry-cured hams from different regions.

Chinese dry-cured hams have unique aroma characteristics appreciated by local consumers. The volatile organic compounds (VOCs) of six selected Chinese dry-cured hams (Mianning, Nuodeng, Saba, Sanchuan, Wanhua, and Xuanen) were analyzed by solvent assisted flavor evaporation (SAFE) combined with GC × GC-ToF-MS and head-space (HS) injection combined with GC-IMS. To visualize VOCs and differentiate samples, principal component analysis (PCA) and multiple factor analysis (MFA) were performed. GC × GC-ToF-MS resulted in over five times more VOCs (265) than GC-IMS (45). However, PCA and MFA indicated similar results using GC-IMS or GC × GC-ToF-MS data, suggesting HS-GC-IMS as a good choice to differentiate dry-cured hams from different regions. Xuanen ham from Yunnan Province having smoky aroma was significantly different from other hams, likely due to its unique process. Many aldehydes (heptanal, nonanal, etc.) played an important role in Sanchuan ham. Ketones were related to other four dry-cured hams, though they came from different regions. This study provides valuable analytical data to characterize and discriminate the flavor profile of Chinese dry-cured hams.

Organic contaminants in human breast milk identified by non-targeted analysis.

Understanding the health implications of human exposure to mixtures of chemical contaminants is aided by analytical methods that can screen for a broad range of both expected and unexpected compounds. We performed a proof-of-concept analysis combining human breast milk, a biomonitoring matrix for determining contaminant exposure to mothers and infants, with a non-targeted method based on comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOF-MS). A total of 172 presumably anthropogenic halogenated compounds and non-halogenated cyclic and aromatic compounds were tentatively identified in breast milk from San Diego, California through mass spectral database searches. Forty of the compounds were prioritized for confirmation based on halogenation or 100% frequency of detection, and the identities of 30 were verified using authentic standards. Thirty-four (85%) of the prioritized contaminants are not typically monitored in breast milk surveys, and 31 (77%) are regulated in at least one market worldwide, indicating breast milk may be a useful biomonitoring matrix for non-targeted analysis and the assessment of human exposure to future emerging or undiscovered contaminants.

Identification and Quantitation of Linear Alkanes in Lubricant Base Oils by Using GC×GC/EI TOF Mass Spectrometry.

Linear alkanes are a class of compounds known to negatively affect the physical performance of lubricant base oils. The ability to rapidly identify and quantify linear alkanes in lubricant base oils would enable oil companies to more effectively evaluate their refinery methods for converting crude oil to lubricant base oils. While mass spectrometry is a powerful method for elucidation of the structures of compounds in complex mixtures, it is not innately quantitative. An approach is presented here for the identification and quantitation of linear alkanes in base oil samples by utilizing GC×GC/EI TOF MS. Identification of the linear alkanes in base oils was achieved based on their retention times in both GC columns as well as their EI mass spectra. Linear alkane model compound mixtures were used to generate calibration plots for quantitation of the linear alkanes in the base oils. The accuracy of this method was greater than 83.8%, within-day precision lower than 6.2%, between-day precision lower than 16.2%, and total precision lower than 17.2%. All noted figures of merit surpass the acceptable limits for a new validated quantitative method, where accuracy must be better than 80% and precision lower than 20% at the lower limit of quantitation. The n-alkane content in both base oil samples was further validated using a GC×GC/FID method (the gold standard for quantitation), which provided nearly identical results to those obtained using the GC×GC/EI TOF MS method. Therefore, GC×GC/EI TOF MS can be used to both identify and quantitate linear alkanes.

Biodegradation of the aromatic fraction from petroleum diesel fuel by Oerskovia sp. followed by comprehensive GC×GC-TOF MS.

Polycyclic aromatic hydrocarbons (PAHs) from petroleum and fossil fuels are one of the most dominant pollutants in the environment. Since aromatic fraction from petroleum diesel fuel is mainly composed of PAHs, it is important to discover new microorganisms that can biodegrade these compounds. This article describes the biodegradation of the aromatic fraction separated from petroleum diesel fuel using the strain Oerskovia sp. CHP-ZH25 isolated from petroleum oil-contaminated soil. The biodegradation was monitored by gravimetry and GC × GC-TOF MS. An innovative method was applied to visualize degraded compounds in the data provided by a GC × GC-TOF MS. It was shown that Oerskovia sp. CHP-ZH25 degraded 77.4% based on gravimetric analysis within 30 days. Average rate of degradation was 14.4 mg/L/day, 10.5 mg/l/day and 4.0 mg/l/day from 0 to 10 day, 10-20 and 20-30 day, respectively. The order of PAH degradation based on decrease in peak volume after 30 days of incubation was as follows: dibenzothiophene derivatives > benzo[b]thiophene derivatives > naphthalene derivatives > acenaphthene derivatives > acenaphthylene/biphenyl derivatives > fluorene derivatives > phenanthrene/anthracene derivatives. Here we demonstrated that Oerskovia sp. CHP-ZH25 could potentially be a suitable candidate for use in bioremediation of environments polluted with different PAHs.

Identification of key aroma-active compounds in sesame oil from microwaved seeds using E-nose and HS-SPME-GC×GC-TOF/MS.

The study investigated the volatile compounds of sesame oil and the effects of microwave processing (0-8 min with 1-min intervals), mainly focusing on the integral flavor characteristics and individual aroma-active compounds. A total of 82 characteristic odors were identified using GC×GC-TOF/MS. Fifteen volatile compounds with the highest odor activity values (OAV > 100) were selected as the key odors contributing to the flavor profile of microwaved sesame oil, including 2-methyl-propanal (pungent, malt, green), 2-methyl-butanal (cocoa, almond), furaneol (caramel), 1-octen-3-one (mushroom), 4-methyl-3-penten-2-one (sweet), 1-nonanol (fat, citrus, green), 2-methyl-phenol (phenol), 2-methoxy-phenol (smoke, sweet), 2-methoxy-4-vinylphenol (clove, curry), 2,5-dimethyl-pyrazine (cocoa, roasted nut, roast beef), 2-furfurylthiol (coffee, roast), 2-thiophenemethanethiol (sulfur), methanethiol (gasoline, garlic), methional (cooked potato), and dimethyl trisulfide (fish, cabbage). The OAVs significantly increased with a longer microwave process. Meanwhile, PCA results based on E-nose and cluster analysis results based on GC×GC-TOF/MS were similar to distinguish flavor formation during the microwave process. PRACTICAL APPLICATIONS: Sesame oils were prepared by a microwave process. Aroma-active compounds with the highest OAVs in sesame oils were not clear. Identification of key aroma compounds of sesame oils could adopt a comprehensive assessment method in combination with E-nose and individual odors detection. Microwave pretreatment as a new processing technology for sesame oil extraction could reduce the time consumption and produce a unique fragrant flavor compared to the traditional roasting process.

Characterization of key aroma compounds in Chinese Guojing sesame-flavor Baijiu by means of molecular sensory science.

Key odorants of Guojing sesame-flavor Baijiu were identified using the concept of molecular sensory science, including aroma extract dilution analysis (AEDA) based on gas chromatography-olfactometry (GC-O) combined with gas chromatography-mass spectrometry (GC-MS). A total of 509 volatile compounds were detected by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC-TOF-MS). Sixty-one aroma-active compounds were identified via AEDA. Among them, two compounds with strong roasted aroma showed the highest flavor dilution (FD) factors of 19,683 and 6561. By using pure standards, aroma tests, and GC-MS, the compound with FD = 19683 was identified as benzenemethanethiol, which is reported for the first time in Baijiu. Sixty compounds were quantified by means of internal standard curve method, and 39 of them had odor activity values (OAVs) ≥ 1. Ethyl hexanoate, ethyl octanoate, and dimethyl trisulfide showed the highest OAVs, indicating that they contribute significantly to the aroma of Guojing sesame-flavor Baijiu.

Profiling of volatile flavor compounds in nkui (a Cameroonian food) by solid phase extraction and 2D gas chromatography time of flight mass spectrometry (SPME-GC×GC-TOF-MS).

The objective of this study was to investigate the volatile flavor compounds of nkui, a Cameroonian food, using solid phase microextraction (SPME) and a two-dimensional gas chromatography time of flight mass spectrometry GC×GC-TOF-MS system. Using SPME, volatile compounds were extracted from nkui and analyzed by GC×GC-TOF-MS. The data retrieved revealed the presence of flavor volatiles including acids (20%), alcohols (4%), aldehydes (10%), aromatic compounds (4%), esters (7%), furans (4%), ketones (11%), terpenes and terpernoids (27%). Although the terpene compounds were the most predominant, an ester (linalyl acetate) had the highest percentage of 19%, conferring a sweet, green and citrus flavor. Results obtained from this study suggest that the characteristic flavor of nkui was due to the combination of different volatile flavor compounds, which contributed to its aroma. Considering the medicinal importance of these compounds, their presence positions nkui as a vital food source with health benefits and medicinal properties.