Comprehensive Two-dimensional Gas Chromatography Research Articles

Observation of chromatographic differences by non-specialist viewers for one-dimensional gas chromatography and comprehensive two-dimensional gas chromatography output

In the context of forensic investigations, chromatography is used to characterize a sample’s components, providing a chemical pattern to compare with known references which is often presented to individuals without specialized training in analytical chemistry. Comprehensive two-dimensional gas chromatography (GC × GC) has recently become popular in forensic research for performing analyzing samples such as fire debris samples, drugs, chemical threats, human remains detection, and more. New methods are developed in forensic research regularly, which challenge our view of what may be increasingly complex to convey through scientific communication. This study investigated individuals’ ability to observe differences in images for non-chromatographic photographs, one-dimensional gas chromatography (GC) chromatograms, and comprehensive two-dimensional gas chromatography (GC × GC) contour plots. The goal was to identify whether comparative observations between two outputs were facilitated or hindered when observing GC chromatograms compared to GC × GC contour plots, using photographs as a control. Participants indicated low difficulty in finding differences between pairs of images in all categories. They scored highly at indicating when two images were distinguishable or indistinguishable, with no significant difference between control images and each category. These results support that GC × GC output can be implemented in expert testimony without challenges over traditional one-dimensional techniques. Ongoing research should avoid statements that GC × GC may facilitate or hinder juror comprehension, as the results currently indicate no significant benefit or drawback. Additional research is needed to improve understanding of how technique explanation could aid expert witness testimony to better evaluate how this increasingly common technique will fit into future forensic casework opportunities.

Gcxgclab: An R Package for Two-Dimensional Gas Chromatography Preprocessing and Analysis.

Comprehensive two-dimensional gas chromatography (GC×GC) is an established technique capable of chromatographically separating thousands of analytes in complex matrices. When coupled with highly sensitive detectors such as a high-resolution mass spectrometer, these instruments produce large multidimensional data sets. A prevailing challenge for GC×GC users is efficient data handling and analysis. Although commercial software packages exist for GC×GC data analysis, these platforms are typically optimized for low-throughput qualitative data interpretation utilizing desktop computer systems. Additionally, commercial GC×GC data processing packages offer little flexibility to explore custom or novel data processing concepts. In this work, an open-source R package, called "gcxgclab", was developed as an alternative data processing package for GC×GC users and offers data preprocessing and analysis functions including baseline correction, smoothing, phase shift, peak detection, peak alignment, extracted ion chromatogram, mass spectra extraction, mass defect analysis, and targeted and nontargeted analysis. This package was designed to be customizable and allows for batch data processing on desktops or high-performance computing systems to increase the throughput. gcxgclab is available for free on the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/gcxgclab/index.html.

Translating 2D-Chromatographic Fingerprinting to Quantitative Volatilomics: Unrevealing Compositional Changes in Maize Silage Volatilome for Robust Marker Discovery.

This study examines the complex volatilome of maize silage, both with and without commercial heterolactic strain inoculation, conserved for 100 days, using quantitative volatilomics. Chemical classes linked to microbial metabolism were analyzed across a concentration range from 10 μg g-1 to 1 ng g-1. A reference method using comprehensive two-dimensional gas chromatography (GC × GC) and time-of-flight mass spectrometry (TOF MS) with loop-type thermal modulation (TM) was translated to a differential-flow modulation (FM) platform with parallel MS and flame ionization detector (FID) detection. With translation, the original method's analyte elution order and resolution are preserved. The new method allowed for accurate quantification using multiple headspace solid-phase microextraction (MHS-SPME) and FID-predicted relative response factors (RRFs). Both methods showed comparable discriminatory power with FM GC × GC-MS/FID achieving satisfactory quantification accuracy without external calibration. Analysis of 98 volatiles provided insights into silage fermentation, supporting marker discovery and correlations with silage quality and stability.

Enantioselective-GCxGC determination of α-terpinyl ethyl ether in wine: Quantitative analysis and identification of main terpene precursors

The present study investigates the presence of α-terpinyl ethyl ether in wine and gives insights on the chemical processes leading to its formation. The analytical determination of (S)-α-terpinyl ethyl ether and (R)-α-terpinyl ethyl ether enantiomers was obtained by enantioselective comprehensive two-dimensional gas chromatography. Applying the two isomers as variables in combination with closely related terpenes, an accurate classification model of wines for the grape variety was successfully applied to a representative set of single-variety wine samples. Although presenting relatively low absolute concentrations, α-terpinyl ethyl ether (along with α-terpineol) resulted to be an inevitable and irreversible degradation product of linalool. In fact, a conversion study from enantiomerically pure (R)-linalool showed a major loss of the initial chiral configuration, i.e. only a very small enantiomeric excess characterized the product. α-Terpineol itself was also confirmed to be a precursor of α-terpinyl ethyl ether, however this process showed a smaller conversion over two weeks than from linalool, and without losses of the initial chiral configuration. In the real samples, the concentration of α-terpinyl ethyl ether was found to be much lower than that of α-terpineol, regardless of the alcohol-to-water ratio. Finally, olfactory descriptors were qualitatively attributed to each α-terpinyl ethyl ether enantiomer.

In-bottle thin film solid phase microextraction coupled to flow modulated comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry for monitoring of organic pollutants in environmental waters

The monitoring of organic compounds in water is critical for assessing environmental health and the effectiveness of treatment processes. In this study, we present a robust and eco-friendly approach to environmental water analysis that integrates thin film solid phase microextraction (TF-SPME) with comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry (GC × GC-TOFMS). This method is designed to detect multiclass organic pollutants in environmental water, thus enabling applications such as detailed analyses of changes post-treatment processes. The supervised PCA results revealed distinct clustering of the three water sample classes - raw wastewater, outflow from WWTF, and river water - each occupying separate regions in the principal component space. Several organohalogen compounds were identified as key differentiators among the water samples, highlighting significant compositional differences across the analyzed classes. Notably, an increased abundance of certain chlorinated compounds was observed in raw wastewater before it underwent purification treatment at the WWTF. Additionally, the greenness evaluation of the in-bottle TF-SPME-GC × GC-TOFMS indicated whiteness scores of 96.7% for the in-bottle TF-SPME-GC × GC-TOFMS method and 79.0% for the LLE (US EPA 8270)-GC/MS method. This approach facilitates the identification of a wide array of organic compounds, characterized by diverse physicochemical properties, through their mass spectral profiles. We applied this method to various environmental water samples, including raw wastewater, effluent from wastewater treatment facilities, and river water, to assess the impact of treatment processes on organic pollutant levels. Our developed strategy effectively monitored alterations in several organic compounds within these environmental water samples. Our results demonstrate that TF-SPME coupled with GC × GC-TOFMS proves to be both straightforward and comparable in performance to other methods for analyzing low-level organic pollutants in water samples, making it a valuable tool for environmental monitoring and discovering new emerging contaminates.

Automated compound speciation, cluster analysis, and quantification of organic vapors and aerosols using comprehensive two-dimensional gas chromatography and mass spectrometry

Abstract. The advancement of analytical techniques, such as comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC–MS), enables the efficient separation of complex organics. Developing innovative methods for data processing and analysis is crucial to unlock the full potential of GC×GC–MS in understanding intricate chemical mixtures. In this study, we proposed an innovative method for the semi-automated identification and quantification of complex organic mixtures using GC×GC–MS. The method was formulated based on self-constructed mass spectrum patterns and the traversal algorithms and was applied to organic vapor and aerosol samples collected from the tailpipe emissions of heavy-duty diesel vehicles and the ambient atmosphere. Thousands of compounds were filtered, speciated, and clustered into 26 categories, including aliphatic and cyclic hydrocarbons, aromatic hydrocarbons, aliphatic oxygenated species, phenols and alkylphenols, and heteroatom-containing species. The identified species accounted for over 80 % of all the eluted chromatographic peaks at the molecular level. A comprehensive analysis of quantification uncertainty was undertaken. Using representative compounds, quantification uncertainties were found to be less than 37.67 %, 22.54 %, and 12.74 % for alkanes, polycyclic aromatic hydrocarbons (PAHs), and alkyl-substituted benzenes, respectively, across the GC×GC space, excluding the first and the last time intervals. From a source apportionment perspective, adamantane was clearly isolated as a potential tracer for heavy-duty diesel vehicle (HDDV) emissions. The systematic distribution of nitrogen-containing compounds in oxidized and reduced valences was discussed, and many of them served as critical tracers for secondary nitrate formation processes. The results highlighted the benefits of developing self-constructed models for the enhanced peak identification, automated cluster analysis, robust uncertainty estimation, and source apportionment and achieving the full potential of GC×GC–MS in atmospheric chemistry.

Conversion of soybean oil under subcritical water conditions into liquid biofuels with low oxygen contents

Although the hydrotreatment of natural triglycerides is a well-established route for producing sustainable aviation fuel and renewable diesel, its high hydrogen consumption is a concern. The hydrothermolysis of natural triglycerides is considered a highly promising alternative route; however, the correlation between process parameters and fuel properties and detailed chemical structures of the produced fuel have not been established. Herein, we investigated the conversion of soybean oil to gasoline-, jet fuel- and diesel-fraction hydrocarbons with low oxygen contents. The properties of fuels produced under various reaction conditions were analyzed comprehensively using simulated distillation, total acid number (TAN), and elemental analysis. Under the optimized reaction conditions of 420 °C, 4.5 MPa, an oil-to-water ratio of 6:1, and reaction time of 10 min, 26 % gasoline-, 62 % jet fuel-, and 90 % diesel-range hydrocarbons with a low oxygen content of 5.1 %, low TAN of 0.04 mg KOH g−1, and high calorific value of 42.7 MJ kg−1 resulted. To elucidate the reaction mechanism, the liquid products produced from soybean oil were analyzed using comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry. In addition, based on the oleic acid conversion under varying hydrothermal conditions, we proposed deoxygenation, cracking, cyclization, and aromatization pathways. The findings of this study present possibilities for producing sustainable biofuels with low oxygen contents for the aviation industry.

In-depth multi-component analysis of bio-aviation fuel derived from waste cooking oil using comprehensive two-dimensional gas chromatography mass spectrometry

In-depth multi-component analysis of bio-aviation fuel derived from waste cooking oil using comprehensive two-dimensional gas chromatography mass spectrometry

GC×GC-TOFMS Analysis of Fecal Metabolome Stabilized Using an At-Home Stool Collection Device

Stool is a mixture of excrement, microbiota, enzymes, undigested material, and small molecules. Fecal metabolomics has gained interest recently, owing to advances in metabolomics and growing research into both the host’s physiology and the gut microbiome. One challenge with fecal metabolomics is preserving the sample integrity from collection until analysis, as the microbiota and enzymes continue to alter the metabolome following defecation. Currently, flash-freezing or lyophilization are utilized to minimize post-collection metabolome changes; however, this requires complex equipment and immediate processing, precluding the possibility for at-home sampling. Commercial devices containing stabilizing solvents have been developed to facilitate at-home collection, ambient transport, and sample storage. Here, we explore the efficacy of a commercially available stool collection device with a stabilization reagent tailored to fecal metabolomics. Stool samples from six donors were either processed shortly post-collection or stored at room temperature for seven days in the tube, with and without the stabilization reagent. Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS)-based untargeted metabolomics was utilized for analyzing extracted metabolites. Chemometric analysis was used to evaluate the performance of the device. We found that the device with the stabilization reagent minimized changes in the metabolite profile relative to unstabilized stool left at room temperature for one week.

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.

Identification of organic constituents on atmospheric particulate matter in the East Asian background air of free troposphere by GC×GC-TOFMS

The presence of organic compounds on the particulate matter (PM) or aerosols can arise from the condensation of gaseous organic compounds on the existing aerosols, or from organic precursors to form secondary organic aerosols (SOA) through photochemistry. The objective of this study is to characterize organic constituents on aerosols relevant to their emission sources and the key compounds revealing the evolution of aerosols with the use of a novel analytical technique. A time-of-flight mass spectrometry (TOFMS) coupled with comprehensive two-dimensional gas chromatography (GC×GC) was developed using a flow type of modulator instead of a thermal type as a prelude to field applications without the need for cryogen. The methodology of GC×GC-TOFMS is discussed in this study in detail.Since the coarse PM (PM10-2.5) may exhibit with a relatively high OC content compared to PM2.5, the GC×GC results have been obtained by analyzing PM10 samples collected in parallel with OC/EC analysis of PM2.5 samples at the Lulin Atmospheric Background Station (LABS, 23.47°N, 120.87°E, 2862 m ASL) as the high-mountain background site in East Asia. We found that the organic analytes were in a majority in the range of 12–30 carbon numbers falling in the category of semi-volatile organic compounds (SVOCs) with 43 compounds of alcohol, aldehyde, ketone, and ester varieties if excluding alkanes. Intriguingly, trace amounts of plasticizers and phosphorus flame retardants such as phthalates (PAEs) and triphenyl phosphate (TPP) were also found, likely originating from regions involved in open burning of household solid waste in Southeast Asia or e-waste recycling in southern China and along the long-range transport route. Compounds such as these are unique to the specific sources, demonstrating the wide spread of these hazardous compounds in the environment.

Analysis of aroma compounds in different grades of Luzhou Laojiao strong-aroma Baijiu by molecular sensory science

Strong-aroma Baijiu is a beloved drink in China because of its elegant cellar aroma, sweetness and mellow taste, and its sales account for more than half of the Baijiu production. In this study, three different grades of strong-aroma Baijiu were analyzed systematically using comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry coupled with molecular sensory science. A total of 342 aroma compounds were identified in the three samples, including 152 aroma-active compounds. Principal component analysis revealed that higher-grade Baijiu contained more terpenes, acetals, and esters. In contrast, lower-grade Baijiu contained fewer esters and many compounds likely generated by the Maillard reaction, such as 5-methylfurfural, 2-propanoylfuran, 2,6-dimethylpyrazine, and 5-ethyl-2(5H)-furanone. Most of the aroma attributes of Baijiu samples could be simulated through aroma recombination experiments, but there were still some slight differences in individual aromas. Finally, the key aroma compounds of the three different grades of Baijiu were revealed through omission experiments. This study provided a scientific basis for the classification of strong-aroma Baijiu quality grades, thereby contributing to the high-quality development of the Baijiu industry.

Comprehensive two-dimensional gas chromatography using a miniaturized multiloop splitter-based non-cryogenic artificial trapping (M-SNAT) modulation device for analysis of cannabis samples

Multiloop splitter-based non-cryogenic artificial trapping (M-SNAT) modulation technique was developed, miniaturized and applied in comprehensive two-dimensional gas chromatography (GC×GC) for analysis of cannabis samples. The approach employed deactivated fuse silica (DFS) columns configured into multiple loop splitter system halving the perimeters of the progressively upstream loops. This splitter device was located between the first (1D) semi-nonpolar column outlet and a microfluidic Deans switch (DS). Each splitter loop splits a peak into two subpeaks having the same area with different void times. Three loops were then applied resulting in the number of the split subpeaks (nsplit) of 8 for each peak, and retention time differences between any two adjacent subpeaks (∆tR,split) were the same. By applying periodic heartcut event (H/C) within every artificial modulation period (PAM) of nsplit×∆tR,split, comprehensive split-and-trapped modulation profiles of analytes could be selectively transferred onto the second (2D) polar column (30 m) without cryogen consumption. This artificial modulation system was applied for analysis of cannabis samples with enhanced 2D peak capacity (2nc∼15). The established method was applied to analyse cannabis extracts using vegetable oils with or without frying process. This reveals 454 different peaks with 76, 92, 35 and 70 specific components specifically observed by using olive oil extraction (OE), fried OE, coconut oil extraction (CE) and fried CE, respectively.

Development of a Standardized Protocol for the Classification of Column Sets in Comprehensive Two-Dimensional Gas Chromatography

One-dimensional gas chromatography (1D-GC) stationary phases are generally classified according to their relative polarity into non-polar, semi-polar, and polar columns. In comprehensive two-dimensional gas chromatography (GC×GC), it is the polarity difference between the two tandem-assembled stationary phases that determines the selectivity of the column ensemble. This polarity difference is called orthogonality, and GC×GC column sets can be broadly categorized into four groups based on the direction of the serial coupling between the primary and secondary columns. A significant portion of the GC×GC column sets in use today are operated in forward-orthogonality mode, which means that the secondary column is more polar than the primary column. A growing number of reported GC×GC applications operate in reversed-orthogonality configurations, where the secondary column is less polar than the primary column. Very few examples exist of non-orthogonal column sets because of the fact that there is limited additional selectivity that the secondary column can offer over the separation that has already been achieved in the primary column when the two phases are either identical or close in polarity. The fourth group of GC×GC column sets, called hybrid orthogonality, involves the coupling of stationary phases with peculiar selectivity differences that manifest themselves in the bi-dimensional separation plots. In this work, we are presenting a normalized approach to GC×GC column set characterization that is based on the use of a reference mixture of standards called the Century Mix. The Century Mix contains 100 chemical probes of different functionalities that span a reasonable range of volatilities and polarities to capture the selectivity profile of any GC×GC column set. The Century Mix also contains important chemical probes that are used for 1D-GC column characterization (such as the Grob mix and the Rohrschneider/McReynolds compounds) to make some connections between the 1D-GC building block columns and the GC×GC column sets. We finally also outline some other important metrics of comparison that should be taken into consideration to assess the overall performance of a GC×GC system.

Comprehensive comparison of fatty acid methyl ester profile in different food matrices using microwave-assisted extraction and derivatization methods and comprehensive two-dimensional gas chromatography coupled with flame ionization detection

Analyzing fatty acids provides key insights into fat composition for industrial applications and their implications for nutrition and health. Typically, fatty acid analysis involves extracting lipids from the matrix and converting them into fatty acid methyl esters (FAME) through a derivatization process before gas chromatography (GC) analysis. Either one-step or two-step procedures can be found in the literature and as official methods. In this work, different methods exploiting microwave-assisted processes were compared with two official methods from the American Oil Chemical Society (AOCS). Especially, two types of microwave-assisted extractions were employed: solvent extraction and extraction with hydrolysis. The extracts were derivatized using either BF3 or a microwave-assisted methanolic hydrogen chloride solution. These combinations of extraction and derivatization methods were compared also with one-step microwave-assisted extraction and derivatization, and two AOCS reference methods, resulting in seven different methods applied to six different food matrices. The performance of the different procedures was compared based on the FAME profile obtained from the comprehensive two-dimensional GC (GC × GC)-FID analysis.Microwave-assisted processes were shown to be effective, yielding results comparable to the official methods in both the one-step and two-step methods. Moreover, it was shown that the BF3 derivatization could be safely replaced with microwave-assisted derivatization with methanolic hydrogen chloride, providing equivalent performances while enhancing operator safety and environmental friendliness. Some discrepancies in the FAMEs profile were highlighted for the sample of oats, the only explicitly requiring acidic hydrolysis for lipid extraction. Further studies are required to understand the reasons behind these differences and develop a suitable modified method. In conclusion, all the methods were evaluated for greenness and blueness with two specific tools: AGREEprep and BAGI.

Characterization of semi-volatile compounds in 56 Italian ciders using GC×GC-TOF-MS and multivariate analysis

Fifty-six samples of differently produced commercial Italian ciders were analysed for semi-volatile organic compounds (SVOCs) profiling, using comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-TOF-MS) technique for the very first time. To properly support the compositional investigation of this emerging beverage, a chemometric approach through Principal Component Analysis (PCA) was employed. This revealed a sample distribution in agreement with results of the sensory tasting panel performed on such ciders, highlighting an excellent correlation between variables and perceived odorants. In particular, the positions of peculiar and anomalous objects in the Principal Components (PCs) space are explicitly evaluated, exploring the associated loadings (i.e., the importance of the identified chemical compounds), paying attention to their biochemical origin along the cider-making process and their impact on the sample olfactory analysis. Besides this, the t-distributed Stochastic Neighbor Embedding (t-SNE) method was shown to be an efficient tool for gathering pear ciders from the other samples (apple ciders), better than PCA. This study stands for the first survey on Italian commercial craft cider, and its results are aimed to be a milestone for its characterization and to start and promote cider culture in this country.

Optimization of headspace high-capacity tool coupled to two-dimensional gas chromatography–mass spectrometry for mapping the volatile organic compounds of raw pistachios. A proof-of-concept on the classification ability by geographic origin

An optimized procedure for extracting and analyzing raw pistachio volatiles was developed through headspace sampling with high-capacity tools and subsequent analysis using comprehensive two-dimensional gas chromatography coupled with mass spectrometry. The examination of 18 pistachio samples belonging to different geographic areas led to the identification of a set of 99 volatile organic compounds (VOCs). Molecules were putatively identified using linear retention index, mass spectra similarity, and two-dimensional plot location. The impact of preprocessing and processing techniques on the aligned data matrix from a set of samples of different geographical origins, after removing contaminants, was evaluated. The combination of scaling with log-transformation, normalization with z-score, and data reduction with random forest machine learning algorithm generated a panel of 16 discriminatory VOC molecules. As a proof of concept, raw pistachios' VOC profile was employed for the first time to tentatively classify them based on their geographical origin.

Comparison of head space solid phase micro extraction with conventional and comprehensive gas chromatography mass spectrometry for volatile profiling of Irish whiskey

Whiskey is a traditional distilled product produced on the island of Ireland that is currently experiencing a major expansion in export volume. Different styles of Irish whiskey exist, however only some very limited published information exists on the volatile congener profile of the different styles of Irish whiskey. Such information is potentially indispensable from a quality, flavour and authenticity perspective. As gas chromatography is the established analytical method of choice to identify volatile congeners, this study compared headspace-solid phase microextraction (HS-SPME) using conventional gas chromatography single quadrupole mass spectrometry, to HS-SPME and HS-SPME-Arrow using comprehensive two-dimensional gas chromatography (GC×GC) modulated using reverse flow in tandem with time-of-flight mass spectrometry (TOFMS) detection. Six representative Irish whiskey samples were evaluated consisting of new make spirit and mature whiskies representing Single Malts, Pot Stills and Blends. The number of volatile congeners identified in these samples by HS-SPME/HS-SPME Arrow GC×GC-TOFMS was approximately twice that detected by conventional HS-SPME GCMS. In total 145 unique individual volatile congeners, excluding ethanol were identified, with the majority consisting of esters, but also benzenes, alcohols, aldehydes, terpenoids, furans, ketones, alkanes, alkenes, norisoprenoids, acetals, acids, lactones and phenols. The use of HS-SPME Arrow GC×GC-TOFMS significantly enhances the number of volatile congeners that can be identified and therefore provides much more information that can convey insights into product quality, consistency, flavour and also for authentication purposes.

Forensic significance of VOCs profiling in decayed ante- and post-mortem injuries by GC×GC-TOF/MS.

Accurately identifying and differentiating the types of injuries in decomposed corpses is a major challenge in forensic identification. Forensic investigations involving decomposed cadavers pose challenges in determining the cause of death. Traditional methods often lack conclusive evidence. However, the implementation of advanced analytical techniques, such as comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOF/MS), shows promise in overcoming these limitations, but the potential in this area remains limited. Therefore, this study aims to bridge this gap by exploring the potential of GC × GC-TOF/MS in the analysis of volatile organic compounds (VOCs) changes within decaying ante- and post-mortem injuries.The research emphasizes the forensic significance of VOCs changes in decomposed cadavers. We used GC × GC-TOF/MS analysis to identify the specific volatile compounds in putrefied corpse tissue samples from mice. The GC × GC-TOF/MS analysis results showed that under winter conditions, PC1 explained 57.16% of the variance, and PC2 explained 25.23% of the variance; while under summer conditions, PC1 explained 71.89% of the variance, and PC2 explained 24.49% of the variance. This demonstrates the potential of GC × GC-TOF/MS in identifying specific VOCs present in tissue samples that can serve as potential biomarkers for distinguishing between antemortem and postmortem injury. GC × GC-TOF/MS analysis revealed distinct VOC patterns in both conditions. Comprehensive use of GC × GC-TOF/MS analysis enhances accuracy in identifying and characterizing ante- and post-mortem injuries in decomposed cadavers. This study can significantly contribute to the field of forensic medicine and improve the accuracy of forensic investigations.

Impact of deodorisation time and temperature on the removal of different MOAH structures: a lab-scale study on spiked coconut oil

Vegetable fats and oils are prone to contamination by mineral oil hydrocarbons due to the lipophilic and ubiquitous character of the latter. As the aromatic fraction of these hydrocarbons, MOAH, is associated with carcinogenicity, mutagenicity, and detrimental effects on foetal development, finding strategies to limit or reduce their contamination is highly relevant. Deodorisation (i.e. a refining step) has shown the ability to remove MOAH < C25 in vegetable fats and oils, but there is little information about the structures removed. Therefore, the present study investigated the impact of deodorisation conditions on the removal of different structures of MOAH in spiked coconut oil. An inscribed central composite design was built with time and temperature as variables (0.5-4h, 150-240 °C), while pressure (3 mbar) and steam flow (1 g water/g oil per hour) were kept constant. The analysis of MOAH in the oil was performed using a fully automated liquid chromatography coupled with two parallel comprehensive two-dimensional gas chromatography systems with flame ionisation and time-of-flight mass spectrometric detection. Response surfaces plotting the MOAH loss according to time and temperature were built for different MOAH fractions. The latter were defined based on the number of aromatic rings (>3 or ≤3) and the number of carbon atoms present (C16-C20, C20-C24, C24-C35, C35-C40). It was found that at 200 °C, compounds < C24, including weakly alkylated triaromatics, could be reduced to below the limit of quantification, while at 230 °C, it was possible to remove >60% of the C24-C35 fraction, including pentaromatics of low alkylation.