Effects of Broth pH and Chilling Storage on the Changes in Volatile Profiles of Boiled Chicken Flesh.

This study investigated the changes in volatile compounds in chicken flesh after boiling at various pHs (6.0-9.0) and after chilling storage (4.0±1.0°C) for 7 d. The volatile compounds were assessed qualitatively and quantitatively by using a headspace gas chromatography-mass spectrometry analysis. Twenty-one volatile compounds were discovered and categorized as amine, aldehyde, alcohol, ketone, acid, and furan. One type of amine, (2-aziridinylethyl) amine, was the most prevalent volatile component, followed by aldehyde, ketone, aldehyde, acid, ester, and furan. The results showed that the quantity and quality of the volatile compounds were influenced by a pH of the boiling medium. Additionally, the types and volatile profiles of the chicken were altered during chilling. In particular, in the chicken that was boiled at a pH of 8.0, the hexanal (an aldehyde) content increased the most after 7 d of chilling. Moreover, various alcohols formed after the 7 d of chilling of the chicken that was boiled at pHs of 8.0 and 9.0. Because of the oxidation and degradation of fat and proteins, the most altering volatile compounds were the reducing amines and the increasing aldehydes.

Rapid determination of volatile benzene derivatives and chlorobenzenes in goat's milk by HS-SPME-GC-MS/MS.

A method for the determination of eight benzenes (BTEXs) and twelve chlorobenzenes (CBs) in goat's milk by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS/MS) was developed. The study investigated the impact of various factors such as extraction fiber type, salt amount, equilibrium conditions, and desorption conditions on the outcomes. Target analytes were separated on a DB-HeavyWAX column and quantified using the external standard method. The results showed that the target compounds had a good linear relationship in the range of 0.01 ∼ 50 µg/L (R2 > 0.997), the limit of detection (LOD) was 0.003 ∼ 0.150 µg/L, and the limit of quantification (LOQ) was 0.01 ∼ 0.50 µg/L. The average recoveries were 82%-116% and the relative standard deviation (RSD) was 0.8%-17.3% under the three addition levels of 1×, 2×, and 10 × LOQ. In a survey of twenty goat's milk samples, only ethylbenzene, xylenes, cumene, chlorobenzene, and 1,4-dichlorobenzene were detected at levels exceeding their respective limits of quantification. The method was evaluated using two ecological scales (Eco-Scale), GAPI and AGREEN, to verify its environmental friendliness and applicability. This method is simple, green, and efficient, which provides a certain theoretical basis for the production and quality safety evaluation of dairy products.

Rapid screening of volatile chemicals in surface water samples from the East Palestine, Ohio chemical disaster site with proton transfer reaction mass spectrometry.

The increasing prevalence of hazardous chemical incidents in the United States necessitates the implementation of analytically robust, rapid, and reliable screening techniques for toxicant mixture analysis to understand short- and long-term health impacts of environmental exposures. A recent chemical disaster in East Palestine, Ohio has underscored the importance of thorough contamination assessment. On February 03, 2023, a Norfolk Southern train derailment prompted a chemical spill and fires. An open burn involving over 100,000 gal of vinyl chloride was conducted three days later. Hazardous compounds were released into air, water, and soil. To provide time-sensitive exposure data for emergency response, this study outlines a novel methodology for rapid characterization of chemical contamination of environmental media to support disaster response efforts. A controlled static headspace sampling system, in conjunction with a high-resolution proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS), was developed to characterize volatile organic compounds (VOCs) in surface water samples collected near the East Palestine train derailment site. Spatial variations were observed in the chemical composition of surface water samples collected at different locations. Hydrocarbons were found to be the most abundant chemical group of all surface water samples, contributing 50 % to 97 % to the total headspace VOC mass. Compounds commonly detected in surface water samples, including benzene, styrene, xylene, and methyl tert-butyl ether (MTBE) were also observed in most surface water samples, with aqueous concentrations typically at ng/L levels. This study demonstrated the potential of the proposed methodology to be applied for rapid field screening of volatile chemicals in water samples in order to enable fast emergency response to chemical disasters and environmental hazards.

Determination of volatile impurities and ethanol content in ethanol-based hand sanitizers: Compliance and toxicity.

This study aimed to assess volatile impurities and ethanol content in ethanol-based hand sanitizers. A total of 31 different brands of hand sanitizers were analyzed using headspace gas chromatography-mass spectrometry to detect impurities and determine alcohol content for compliance. Volatile impurities were identified through Mass Spectrometry database analysis, and regression analysis was employed to ascertain ethanol percentage. Furthermore, a simulated toxicological analysis was conducted to evaluate the potential toxic effects associated with hand sanitizer usage. The detected impurities primarily included ethyl acetate, benzene, acetone, and acetal, along with contaminations such as isobutanol and non-recommended alcohols. In addition, 71 % of samples contained less than the recommended 60 % v/v alcohol concentration, failing to comply with guidelines from the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO). Additionally, the simulation study underscored acute and chronic toxicities primarily linked to benzene contamination. Given that some of the studied products are imported while others are locally produced, it is imperative for consumers worldwide to be informed that certain hand sanitizers may not only be ineffective but also contain harmful residues.

Volatile Organic Compounds from Ceratocystis cacaofunesta, a Causal Agent of Ceratocystis Wilt of Cacao.

Fungi of the genus Ceratocystis are aggressive tree pathogens that cause serious diseases in several crops around the world. Ceratocystis wilt disease caused by C. cacaofunesta has been shown to be responsible for severe reductions in cacao production. In this study, headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was used in combination with chemometric analysis for monitoring volatile organic compounds (VOCs) released from C. cacaofunesta. Low-molecular-weight esters, alcohols, ketones, and sulphur compounds were identified in the liquid broth. Monitoring the volatile profile over five days of fungal growth revealed that the concentrations of alcohol and esters were inversely proportional. Acetate esters were responsible for the intense fruity aroma of the C. cacaofunesta culture produced within the first hours after fungal inoculation, which decreased over time, and are likely associated with the attraction of insect vectors to maintain the life cycle of the pathogen. PCA revealed that 3-methylbutyl acetate was the metabolite with the highest factor loading for the separation of the VOC samples after 4 h of fungal growth, whereas ethanol and 3-methylbutan-1-ol had the highest factor loadings after 96 and 120 h. 3-Methylbutan-1-ol is a phytotoxic compound that is likely associated with host cell death since C. cacaofunesta is a necrotrophic fungus. Fungal VOCs play important roles in natural habitats, regulating developmental processes and intra- and interkingdom interactions. This is the first report on the volatiles released by C. cacaofunesta.

Chemometrics methods, sensory evaluation and intelligent sensory technologies combined with GAN-based integrated deep-learning framework to discriminate salted goose breeds.

The authenticity of salted goose products is concerning for consumers. This study describes an integrated deep-learning framework based on a generative adversarial network and combines it with data from headspace solid phase microextraction/gas chromatography-mass spectrometry, headspace gas chromatography-ion mobility spectrometry, E-nose, E-tongue, quantitative descriptive analysis, and free amino acid and 5'-nucleotide analyses to achieve reliable discrimination of four salted goose breeds. Volatile and non-volatile compounds and sensory characteristics and intelligent sensory characteristics were analyzed. A preliminary composite dataset was generated in InfoGAN and provided to several base classifiers for training. The prediction results were fused via dynamic weighting to produce an integrated model prediction. An ablation study demonstrated that ensemble learning was indispensable to improving the generalization capability of the model. The framework has an accuracy of 95%, a root mean square error (RMSE) of 0.080, a precision of 0.9450, a recall of 0.9470, and an F1-score of 0.9460.

Determination of specific surface area of biomass activated carbon vial headspace gas chromatography technique.

This paper introduces a method for determining the specific surface area (SSA) of biomass activated carbon (BAC) using a tracer-based headspace gas chromatography (HS-GC) technique. The method relies on the adsorption equilibrium of methanol on BAC samples at elevated temperature. A mathematical model allows for the calculation of SSA from the methanol signal obtained during the headspace analysis. The results demonstrate high precision (relative standard deviation < 2.44%) and strong accuracy (correlation with the conventional BET-N2 adsorption method, R² = 0.986). This method offers several advantages over traditional techniques, including ease of operation, significant time efficiency, and the the ability to perform batch determinations of SSA, as multiple samples can be processed simultaneously during the phase equilibrium step.

Determination of Volatile Halogenated Hydrocarbons in Drinking and Environmental Waters by Headspace Gas Chromatography.

Volatile halogenated hydrocarbons (VHHs) are annually produced and released into the environment, posing a threat to public health. In this study, a simple, rapid, sensitive and automated method based on headspace and gas chromatography (GC) with electron-capture detection was described for the determination of VHHs in different concentration levels in water samples. The proposed headspace GC method was initially optimized, and the optimum experimental conditions found were 10-mL water sample containing 20% w/v sodium chloride placed in a 20-mL vial and stirred at 60°C for 35 min, and then 14 VHHs were well separated on DB-35 MS capillary column with a split ratio of 12.5: 1. The limits of detection were in the low µg/L level, ranging between 0.01 and 0.6 µg/L. Finally optimized method was applied for determination 14 VHHs in drinking and environmental waters. The total mean concentrations of VHHs were 34.962, 26.183, 3.228 and 647.344 µg/L in tap water, purified water with 1-year-old filter element, seawater and effluents, respectively. However, no VHHs was detected in purified water with a new filter element. The main composition is different among different water matrix, which may be attributed to their different sources.

[A headspace injection double-column dual-detector gas chromatography system for the analysis of 12 volatile compounds such as ethanol in human blood].

Based on the technical methods of GB/T 42430-2023 and GA/T 204-2019, this study established an analytical method for headspace injection double-column dual-detector (hydrogen flame ion detector) gas chromatography for the simultaneous analysis of at least 12 volatile compounds, including ethanol, in human blood using two different equipment platforms and chromatographic columns. A 100 µL blood or urine sample and a 0.04 g/L tert-butanol working solution prepared as an internal standard are introduced into the headspace sample bottle and then sealed, mixed, and placed on the headspace sampler rack. Using different equipment platforms and columns, methodological parameters such as the limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy of the method were systematically evaluated. The chromatographic separation of acetone, alcohols and benzenes using the established method was satisfactory. The linear ranges, linear correlation coefficients (r), and LODs of acetone and six alcohols, including ethanol, were 0.10-3.00 g/L, >0.997, and 0.05 g/L, respectively. The LOQs were 0.10 g/L for all other compounds, excluding n-propanol (0.005 g/L). Additionally, the linear ranges, r values, LODs, and LOQs of benzene and four benzene derivatives were 0.05-50 mg/L, >0.995, 0.02 mg/L, and 0.05 mg/L, respectively (Column J&W DB-BAC1 UI and Column Rtx-BAC-PLUS 2). The average recoveries of compounds on J&W DB-BAC1 UI and Rtx-BAC-PLUS 2 columns ranged from 92.2% to 111.6%, and the relative standard deviations (RSDs, n=6) ranged from 0.4% to 7.4%. The LOD, LOQ, precision, accuracy, and linearity of the established method met the requirements of relevant standards, and no significant differences arose between the methodological parameters of the two platforms. CNAS-GL006 (2019) and JJF 1059.1-2012 were used as guides to evaluate the uncertainty of ethanol on two different sets of equipment platforms and chromatographic columns. The ethanol uncertainty was mainly derived from the calibration curve; however, the confidence probability was 95% (k=2). According to the analysis of the verification samples and real samples, the established method is suitable for the high-precision quantitative analysis of acetone and six alcohols and five benzene derivatives in human blood and other body fluids. It can be used in practical scenarios such as judicial identification and the detection of poisons.

[Analysis of phthalate esters from vegetable oils by gas chromatography-mass spectrometry coupled with headspace solid-phase microextraction using cyclodextrin-based hypercrosslinked polymer coated fiber].

Phthalate esters (PAEs) are used as additives to enhance the pliability and malleability of plastics. These substances frequently migrate from packaging materials to vegetable oils because of the absence of covalent bonds. Over time, this migration could result in the accumulation of PAEs in the human body through ingestion, contributing to various diseases. Therefore, accurate qualitative and quantitative analyses of PAEs in vegetable oils are imperative to assess the origins of contamination and investigate their toxicity, degradation, migration, and transformation patterns. However, the concentration of PAEs in most samples is low, and the composition of vegetable oils is complex. Thus, PAEs must be enriched and purified using appropriate sample pretreatment procedures before analysis. Common methods for pretreating PAEs in oil include solid-phase extraction (SPE), dispersive SPE, and magnetic SPE. These techniques require time-consuming and labor-intensive procedures such as oil dissolution, solvent extraction, and degreasing. These approaches also require numerous solvents and containers, increasing the risk of sample cross-contamination. Solid-phase microextraction (SPME) integrates sampling, extraction, purification, concentration, and injection into a single process, significantly accelerating analytical testing and reducing the potential for sample cross-contamination. In headspace (HS) mode, the analytes achieve equilibrium on the coating and are extracted in the gas phase. The fibers are shielded from nonvolatile and high-relative molecular mass substances in the sample matrix. Thus, SPME is an ideal method for extracting volatile compounds in vegetable oils. When HS-SPME coupled with gas chromatography-mass spectrometry (GC-MS), it can achieve the rapid screening of PAEs in vegetable oil. In this study, an SPME with cyclodextrin-based hypercrosslinked polymers (BnCD-HCP) coated on stainless steel fibers was employed to extract PAEs from vegetable oil. The structure and morphology of the polymers were characterized using Fourier-transform infrared spectroscopy, nuclear magnetic spectroscopy, and scanning electron microscopy. BnCD-HCP exhibited high stability and diverse interactions, including π-π, hydrophobic, and host-guest interactions. The oil samples were incubated with methanol, and the PAEs were extracted from the headspace using the probe. The optimal extraction parameters included an extraction time of 20 min, extraction temperature of 50 ℃, desorption time of 4 min, and desorption temperature of 275 ℃. The BnCD-HCP/HS-SPME method was evaluated under optimized experimental conditions. The limits of detection (LODs) and quantification (LOQs) were determined by applying signal-to-noise ratios (S/N) of 3 and 10, respectively. Method accuracy was evaluated using relative standard deviations (RSDs). Single-needle precision was evaluated by conducting three consecutive analyses at 3 h intervals within a day. Inter-needle precision was assessed by conducting the same analyses (three replicates) with differently coated fibers. The 12 PAE compounds exhibited good linearity with correlation coefficients (R2) of at least 0.99. The LODs and LOQs ranged from 0.21 to 3.74 µg/kg and from 0.69 to 12.34 µg/kg, respectively. The RSDs were in the range of 1.8%-11.4% and 5.1%-13.9% for the single-needle and needle-to-needle methods, respectively. The proposed method was applied to soybean, peanut, and sunflower oils, and two PAEs were found in all three oils. Moreover, the method demonstrated good precision (RSD=1.17%-11.73%) and recoveries (72.49%-124.43%). Compared with other methods, the developed method was able to extract many target analytes and had a low or comparable LOD and high recovery. More importantly, this method does not require tedious operations such as solvent extraction and purification. Consequently, the developed method can be used to extract not only PAEs in oils but also other substances with a high lipid content.

Influence of Different Packaging Materials on the Composition of the Headspace of Rennet Cheeses under Different Modified Atmosphere Conditions.

The aim of this study was to analyze the influence of different packaging materials on the composition of the headspace (CO2 and O2) of rennet cheeses packed in unit packaging under different modified atmosphere (MAP) conditions during a storage period of 90 days at 2 °C and 8 °C. The packaging materials comprised different combinations of BOPP-biaxially oriented polypropylene; PET-polyester; PE-polyethylene; PP-polypropylene; EVOH-ethylene-vinyl alcohol copolymer; PET-polyethylene terephthalate; and PA-polyamide. As the properties of the packaging material (foil) affect the gas conditions inside the packaging, it is important to study whether the modifications, i.e., properties and thickness, of the foils will result in significant differences in the composition of the headspace of packed cheeses. The CO2 content in the headspace of Gouda cheese packages ranged from 35% to 45%, while for Maasdamer and Sielski Klasyczny cheese, it varied between 55% and 65%. Throughout the storage period, the O2 content in the headspace of cheeses packaged in tested foils (1-5) did not exceed 0.5%. The type of foil used did not influence the modified atmosphere packaging (MAP) conditions.

A Comparative Analysis of Cold Brew Coffee Aroma Using the Gas Chromatography-Olfactometry-Mass Spectrometry Technique: Headspace-Solid-Phase Extraction and Headspace Solid-Phase Microextraction Methods for the Extraction of Sensory-Active Compounds.

Coffee, one of the most widely consumed commodities globally, embodies a sensory experience deeply rooted in social, cultural, and hedonic contexts. The cold brew (CB) method, characterized by cold extraction, is a refreshing and unique alternative to traditional coffee. Despite its growing popularity, CB lacks defined preparation parameters and comprehensive analysis of its aromatic composition. In this study, we aimed to obtain a representative extract of the volatile matrix of CB and characterize the aroma of sensory-active compounds using advanced techniques such as headspace-solid-phase Microextraction (HS-SPME) and headspace-solid-phase extraction (HS-SPE) for volatile compound extraction, followed by gas chromatography-olfactometry-mass Spectrometry (GC-O-MS) for compound identification. Optimization of the HS-SPME parameters resulted in the identification of 36 compounds, whereas HS-SPE identified 28 compounds, which included both complementary and similar compounds. In HS-SPME, 15 compounds exhibited sensory activity with descriptors such as floral, caramel, sweet, and almond, whereas seven exhibited sensory activity with descriptors such as chocolate, floral, coffee, and caramel. This comprehensive approach to HS-SPME and HS-SPE aroma extraction with GC-O-MS offers an efficient methodology for characterizing the aroma profile of CB, paving the way for future research and quality standards for this innovative coffee beverage.

Innovative insights into the roasting-driven transformation of volatile compounds and quality markers in flaxseed (Linum usitatissimum L.) oil.

Roasting is essential for developing the characteristic aroma of flaxseed oil (FSO), yet its impact on oil quality remains underexplored. This study employed headspace-gas chromatography-mass spectrometry coupled with multivariate analysis to elucidate the dynamic changes in volatile compounds and quality characteristics of FSO subjected to varying roasting temperatures. Our findings revealed that seven key aroma compounds, identified through the variable importance in the projection scores of partial least square-discrimination analysis models and relative aroma activity value, served as molecular markers indicative of distinct roasting temperatures. These compounds included 2,5-dimethylpyrazine, 2-pentylfuran, (E)-2-pentenal, 2-ethyl-3,6-dimethylpyrazine, heptanal, octanal, and 2-hexenal. Notably, roasting at 200°C was found to enhance oil stability and antioxidant capacity, with phenolic compounds and Maillard reaction products playing synergistic roles in bolstering these qualities. Network analysis further uncovered significant correlations between these key aroma compounds and quality characteristics, offering novel perspectives for assessing FSO quality under diverse roasting conditions. This research not only enriched our understanding of the roasting process's impact on FSO but also provided valuable guidance for the optimization of industrial roasting practices. This study would provide important practical applications in aroma regulation and process optimization of flaxseed oil. .

Headspace-SERS assay for early mildewing tobacco leaves.

Mildewed tobacco leaves seriously impact on cigarette product quality and pose a health risk to person. However, early moldy tobacco leaves are hardly found by naked eyes in the workshop. In this work, we self-assemble AuAg nanoalloys on silicon wafers to construct Si/AuAg chips. The headspace-surface enhanced Raman scattering (SERS) protocol is developed to monitor volatile 1,2-dichloro-3-methoxybenzene (2,3-DCA) and 2,4,6-trichloroanisole (2,4,6-TCA) released from postharvest tobacco. Consequently, the visualization of the SERS peak at 1592 cm-1 assigned to ν(CC) after headspace collection for 10 min and the SERS intensity ratio of 1054 and 1035 cm-1 from 2,3-DCA and 2,4,6-TCA less than 0.5 could be used as indicators to predict early moldy tobacco. Additionally, with headspace collection time prolonging to 2 h, a SERS band at 682 cm-1 due to ν(CCl) of 2,4,6-TCA occurs, confirming the mildew of leaves. The headspace-SERS protocol paves a path for rapid and on-site inspection of the quality of tobacco leaves and cigarettes during storage with a portable Raman system.

Efficient Estimation of ascorbic acid in vitamin C tablets enabled by phase-transfer strategy.

In this paper, we introduced a novel phase-transfer strategy tailored for the efficient batch detection of ascorbic acid in vitamin C tablets. This method entailed the reaction between ascorbic acid and an excess of potassium permanganate. Subsequent reaction of the residual potassium permanganate with sodium oxalate in an acidic medium led to the generation of carbon dioxide. The quantification of the produced carbon dioxide was achieved using headspace GC, enabling the indirect measurement of ascorbic acid. The obtained findings revealed that the headspace method exhibited satisfied precision with a relative standard deviation of less than 2.11 % and high sensitivity with a limit of quantitation of 0.27 µmol. These results firmly establish the reliability of this innovative approach for determining ascorbic acid. In addition, the highly automated feature of headspace method significantly enhances the efficiency of batch sample detection and reduces the errors caused by human operation. Thus, the adoption of the transformed phase strategy has demonstrated its effectiveness in assessing ascorbic acid, especially for large-scale sample analysis in industrial applications, owing to its efficiency, precision, and sensitivity.

Novel multiple extraction thermal desorption approach prior to gas chromatography for the determination of residual solvents applied to modified cellulose.

In this work, multiple extraction thermal desorption (METD), as a sample introduction method for GC, was developed. This technique was used for the determination of residual solvents (RS) in modified cellulose, because it is practically impossible to dissolve or distribute it uniformly in water and common organic solvents. Moreover, METD facilitates the optimization of the desorption time and it is more sensitive to quantify trace level volatiles in insoluble material, compared to direct dynamic desorption (DDD). In addition, METD provides diagnostic information about the sample-sorbent interaction. Three solvents (methanol, ethanol and tert-butanol) were determined in two types of modified cellulose (dialdehyde cellulose (DAC) and DAC-ethylenediamine (DAC-EDA)). It was shown that good linearity over a wide concentration range was achieved. The limits of detection (LOD) and limits of quantification (LOQ) for the different solvents ranged from 0.1 to 0.3 µg and from 0.3 to 0.9 µg per tube, respectively. Accuracy of the METD method was verified by using an alternative method based on the decomposition of the modified celluloses by Trichoderma reesei cellulase, followed by headspace-trap-GC (HS-trap-GC). The results obtained from the two validated methods were found to be similar (relative deviation < 17.0 %). However, the developed METD-GC method is preferable for the analysis of RS in modified cellulose since it does not require sample pretreatment and possesses higher sensitivity.

Characterization of key aroma compounds in a novel Chinese rice wine Xijiao Huojiu during its biological-ageing-like process by untargeted metabolomics.

Xijiao Huojiu (Xijiao), an ancient Chinese rice wine (ACRW), is produced using traditional methods, which involve biological-ageing-like process and result in distinctive sensory profiles. However, its aroma composition is still unclear. In this study, the aroma characteristics of three samples with varying ageing times were examined. Xijiao_SCT, with a short cellar time, exhibited a strong fruity and floral aroma and a less grain-like aroma. Conversely, Xijiao_LCT, which had a long cellar time, had a deep cocoa- and caramel-like aroma. A total of 27 key odorants that greatly influenced the aroma characteristics of Xijiao were identified. Comparative studies were used to identify 12 key odorants that distinguish Xijiao from modern Chinese rice wine (MCRW) and grape wines (GW). Additionally, 13 dominant latent ageing markers differentiated Xijiao_SCT from Xijiao_LCT. Our results suggested that ACRW and MCRW have overlapping but distinct volatile metabolomic profiles, highlighting the characteristics of ACRW during ageing process.

Odor Fingerprinting of Chitosan and Source Identification of Commercial Chitosan: HS-GC-IMS, Multivariate Statistical Analysis, and Tracing Path Study.

Chitosan samples were prepared from the shells of marine animals (crab and shrimp) and the cell walls of fungi (agaricus bisporus and aspergillus niger). Fourier-transform infrared spectroscopy (FT-IR) was used to detect their molecular structures, while headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was employed to analyze their odor composition. A total of 220 volatile organic compounds (VOCs), including esters, ketones, aldehydes, etc., were identified as the odor fingerprinting components of chitosan for the first time. A principal component analysis (PCA) revealed that chitosan could be effectively identified and classified based on its characteristic VOCs. The sum of the first three principal components explained 87% of the total variance in original information. An orthogonal partial least squares discrimination analysis (OPLS-DA) model was established for tracing and source identification purposes, demonstrating excellent performance with fitting indices R2X = 0.866, R2Y = 0.996, Q2 = 0.989 for independent variable fitting and model prediction accuracy, respectively. By utilizing OPLS-DA modeling along with a heatmap-based tracing path study, it was found that 29 VOCs significantly contributed to marine chitosan at a significance level of VIP > 1.00 (p < 0.05), whereas another set of 20 VOCs specifically associated with fungi chitosan exhibited notable contributions to its odor profile. These findings present a novel method for identifying commercial chitosan sources, which can be applied to ensure biological safety in practical applications.

Identification of floral aroma components and molecular regulation mechanism of floral aroma formation in Phalaenopsis.

BACKGROUND: Most Phalaenopsis cultivars have almost no aroma, with a few exceptions. Phalaenopsis presents significant challenges in fragrance breeding due to its weak aroma and low fertility. It is therefore necessary to identify the aroma components and key regulatory genes in Phalaenopsis cultivars like 'Orange Beauty', 'Brother Sara Gold', 'Purple Martin', 'H026', 'SK16', 'SX098', and 'SH51', to improve the aroma of the common Phalaenopsis. RESULTS: Floral aroma components were tested on nine Phalaenopsis species, using smell identification and headspace gas chromatography-mass spectrometry. The result showed that alcohols, esters, and alkenes were the key specific components in the different species and cultivar aromas and the aroma intensity and component content of cultivars with different colors were different. The main components of the floral aromas in Phalaenopsis were alcohols (including eucalyptol, linalool, citronellol, and 1-hexanol), esters (including hexyl acetate, leaf acetate, and dibutyl phthalate), alkenes (including pinene and sabinene) and arenes (like fluorene). The transcriptome of flowers in the bud stage and bloom stage of P. 'SH51' was sequenced and 5999 differentially expressed genes were obtained. The contributions of the phenylpropionic acid/phenyl ring compound and the terpene compound to the aroma were greater. Sixteen genes related to phalaenopsis aroma were found. TC4M, PAL, CAD6, and HR were related to phenylpropanoid synthesis pathway. SLS, TS10, and P450 were related to the synthesis pathway of terpenes. TS10 and YUCCA 10 were involved in tryptophan metabolism. CONCLUSION: This is the first report on the floral aroma components and regulatory genes in Phalaenopsis. The proposed method and research data can provide technical support for Phalaenopsis breeding. © 2024 Society of Chemical Industry.

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.