Development of a HS-SPME/GC–MS method for the analysis of volatile organic compounds from fabrics for forensic reconstruction applications

Volatile Organic Compounds Emitted by Flowers: Ecological Roles, Production by Plants, Extraction, and Identification

Volatile organic compounds (VOCs) with a large chemical diversity are emitted by plant flowers. These compounds play an important role in the ecology of plants. This review presents the different ecological roles of VOCs present in the odor plumes of plant flowers, such as pollination, defense, adaptation to their environment, and communication with other organisms. The production and accumulation sites of VOCs in plants with their spatial and temporal variations, including environmental issues, are also summarized. To evaluate the qualitative and quantitative chemical composition of VOCs, several methods of extraction and analysis were used. Headspace (HS) sampling coupled with solid phase microextraction (SPME) is now well-developed for the extraction process. Parameters are known, and several fibers are now available to optimize this extraction. Most of the time, SPME is coupled with gas chromatography-mass spectrometry (GC-MS) to determine the structural identification of the VOCs, paying attention to the use of several complementary methods for identification like the use of databases, retention indices, and, when available, comparison with authentic standards analyses. The development of the knowledge on VOCs emitted by flowers is of great importance for plant ecology in the context of environmental and climate changes.

Profiling flavourings in strawberry-flavoured e-liquid using headspace-gas chromatography-mass spectrometry

E-liquids typically contain nicotine and flavourings in a matrix of propylene glycol (PG) and vegetable glycerine (VG). Some nicotine-free e-liquids are flavouring only in the aerosol carrier with the option for users to add their own nicotine. It is only the nicotine that is monitored in terms of level, as specified by the manufacturers. Little is known of the toxicological effect for some of the flavourings in the context of vaping as these are only regulated for ingestion and not inhalation. A method was developed to analyse volatile organic compounds (VOCs) evolved when e-liquids are vaporised based on headspace-gas chromatography-mass spectrometry (HS-GC-MS) for e-liquids. An in-house standard was prepared with sample matrix and purchased strawberry flavouring to simulate a simple e-liquid but with known levels. This standard was then used to optimise the analysis for use with e-liquid samples but not for full quantification purposes. These were purchased from a range of retailers and with different batches but mainly focussed on strawberry flavour. The results identified three key components indicative of strawberry flavour (ethyl-3-methyl butanoate, ethyl 2-methyl butanoate and ethyl butanoate) and showed considerable variation between both manufacturers and batches. Flavouring VOCs are regulated for ingestion but are not regulated for e-liquid inhalation, so these could have toxicological implications. In addition, the inconsistency between samples suggests further issues when users add their own nicotine to the e-liquids as the viscous sample matrix makes homogeneous mixing difficult.

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects' hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

Volatile-Based Diagnosis for Pathogenic Wood-Rot Fungus Fulvifomes siamensis by Electronic Nose (E-Nose) and Solid-Phase Microextraction/Gas Chromatography/Mass Spectrometry

Wood rot fungus Fulvifomes siamensis infects multiple urban tree species commonly planted in Singapore. A commercial e-nose (Cyranose 320) was used to differentiate some plant and fungi volatiles. The e-nose distinctly clustered the volatiles at 0.25 ppm, and this sensitivity was further increased to 0.05 ppm with the use of nitrogen gas to purge the system and set up the baseline. Nitrogen gas baseline resulted in a higher magnitude of sensor responses and a higher number of responsive sensors. The specificity of the e-nose for F. siamensis was demonstrated by distinctive clustering of its pure culture, fruiting bodies collected from different tree species, and in diseased tissues infected by F. siamensis with a 15-min incubation time. This good specificity was supported by the unique volatile profiles revealed by SPME GC-MS analysis, which also identified the signature volatile for F. siamensis-1,2,4,5-tetrachloro-3,6-dimethoxybenzene. In field conditions, the e-nose successfully identified F. siamensis fruiting bodies on different tree species. The findings of concentration-based clustering and host-tree-specific volatile profiles for fruiting bodies provide further insights into the complexity of volatile-based diagnosis that should be taken into consideration for future studies.

Deep learning-based method for automatic resolution of gas chromatography-mass spectrometry data from complex samples

Modern gas chromatography-mass spectrometry (GC-MS) is the workhorse for the high-throughput profiling of volatile compounds in complex samples. It can produce a considerable amount of two-dimensional data, and automatic methods are required to distill chemical information from raw GC-MS data efficiently. In this study, we proposed an Automatic Resolution method (AutoRes) based on pseudo-Siamese convolutional neural networks (pSCNN) to extract the meaningful features swamped by the noises, baseline drifts, retention time shifts, and overlapped peaks. Two pSCNN models were trained with 400,000 augmented spectral pairs, respectively. They can predict the selective region (pSCNN1) and elution region (pSCNN2) of compounds in an untargeted manner. The accuracies of the pSCNN1 model and the pSCNN2 model on their test sets are 99.9% and 92.6%, respectively. Then, the chromatographic profile of each component was automatically resolved by full rank resolution (FRR) based on the predicted regions by these models. The performance of AutoRes was evaluated on the simulated and plant essential oil datasets. Compared to AMDIS and MZmine, AutoRes resolves more reasonable mass spectra, chromatograms, and peak areas to identify and quantify compounds. The average match scores of AutoRes (925 and 936) outperformed AMDIS (909 and 925) and MZmine (888 and 916) when resolving mass spectra from overlapped peaks on the Set Ⅰ and Set Ⅱ of plant essential oil dataset and matching them against the NIST17 library. It extracted peak areas and mass spectra automatically from 10 GC-MS files of plant essential oils, and the entire process was completed in 8 min without any prior information or manual intervention. It is implemented in Python and is available as an open-source package at https://github.com/dyjfan/AutoRes.

A comparison between mobile and stationary gas chromatography-mass spectrometry devices for analysis of complex volatile profiles

On-site analysis of volatile organic compounds (VOCs) with miniaturized gas chromatography-mass spectrometry (GC-MS) systems is a very rapidly developing field of application. While, on the one hand, major technological advances are improving the availability of these systems on the market, on the other hand, systematic studies to assess the performance of such instruments are still lacking. To fill this gap, we compared three portable GC-MS devices to a state-of-the-art benchtop (stationary) system for analysis of a standard mixture of 18 VOCs. We systematically compared analytical parameters such as the sensitivity and similarity of the signal response pattern and the quality of the obtained mass spectra. We found that the investigated mobile instruments (i) showed different response profiles with a generally lower number of identified analytes. Also, (ii) mass spectral reproducibility (% relative standard deviation (RSD) of the relative abundance of selective fragments) was generally worse in the mobile devices (mean RSD for all targeted fragments ~9.7% vs. ~3.5% in the stationary system). Furthermore, mobile devices (iii) showed a poorer mass spectral similarity to commercial reference library spectra (>20% deviation of fragment ion relative intensity vs. ~10% in the stationary GC-MS), suggesting a less reliable identification of analytes by library search. Indeed, (iv) the performance was better with higher-mass and/or more abundant fragments, which should be considered to improve the results of library searches for substance identification. Finally, (v) the estimation of the signal-to-noise ratio (S/N) in mobile instruments as a measure of sensitivity revealed a significantly lower performance compared to the benchtop lab equipment (with a ratio among medians of ~8 times lower). Overall, our study reveals not only a poor signal-to-noise ratio and poor reproducibility of the data obtained from mobile instruments, but also unfavorable results with respect to a reliable identification of substances when they are applied for complex mixtures of volatiles.

The First Application of 1H NMR Spectroscopy for the Assessment of the Authenticity of Perfumes

The manufacture of counterfeit goods is one of the world’s largest underground businesses and is rapidly growing. Counterfeits can lead not only to the loss of profit for honest producers but also have a negative impact on consumers who pay excessive prices for poor quality goods that may result in health or safety problems. The perfume industry is constantly vulnerable to counterfeits, particularly in the fast developing market of “smell-alike” designer-inspired perfumes because these prompt the identification of the methods that classify their quality. In this paper, the application of proton nuclear magnetic resonance (¹H NMR) spectroscopy is employed for the first time to authenticate perfumery products. The molecular composition of several types of authentic brand fragrances for women was compared with cheap inspired equivalents and fakes. Our approach offers the prospect of a fast and simple method for detecting counterfeit perfumes using ¹H NMR spectroscopy.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Untargeted SPME-GC-MS Characterization of VOCs Released from Spray Paint

Paints are a common form of physical evidence encountered at crime scenes. This research presents an optimized method for the untargeted analysis of volatile organic compounds (VOCs) in spray paint using solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). The presence and persistence of VOCs were monitored in 30 minute intervals, over a 4 hour period, in a triplicate time study. As predicted, spray paint solvents are lost to the environment readily, whereas few VOCs remained present in the headspace in low concentrations beyond 4 hours. The VOCs that were observed to have the highest persistence in the headspace were aromatic compounds and those with longer hydrocarbon chains. We present this study in a forensic science context and suggest that the interpretation of the results may be useful for forensic applications in establishing a time since deposition of a spray-painted surface.

Application of microextraction techniques in alternative biological matrices with focus on forensic toxicology: a review

The interest in alternative biological matrices (e.g., hair and saliva) for forensic toxicology analysis has increased, and recent developments in sample preparation have targeted rapid, cheap, efficient and eco-friendly methods, including microextraction techniques. For this review, we have gathered information about these two hot topics. We discuss the composition, incorporation of analytes and advantages and disadvantages of different biological matrices, and also present the operation principles of the most reported microextraction procedures and their application in forensic toxicology. The outcome of this review may encourage future forensic researches into alternative samples and microextraction techniques.

Thin layer chromatography based extraction approaches for improved analysis of volatile compounds with gas chromatography-mass spectrometry and direct analysis with gas analyzer

In this study, thin-layer chromatography was applied for selective extraction of volatile compounds in perfume prior to analysis with solid phase microextraction and gas chromatography-mass spectrometry. The standard compounds were desorbed from the thin-layer chromatography plate and extracted at 80°C for 15 min showing good linearity of the calibration curves (R²  > 0.98) and acceptable recovery range (65-81%). The plate after the separation was cut into four smaller parts followed by solid phase microextraction/gas chromatography-mass spectrometry analysis, which revealed different compound profile in each part with the correlation between log P of the standard compounds and their positions along the thin-layer chromatography plate (R²  = 0.65). This approach was applied to analyze perfume compounds in the sample with strong matrix interference from the synthetic agarwood. Terpene hydrocarbons (woody-based odors), ketones/esters, aldehydes, ethers, and alcohols were mostly observed at 8 ± 1, 6 ± 1, 5 ± 2, 4 ± 2, and 3 ± 2 cm, respectively, from the bottom of the thin-layer chromatography plate. While, the conventional solid phase microextraction/gas chromatography-mass spectrometry analysis of this sample solution revealed only 62 compounds (including 35 perfume compounds), the four-piece approach resulted in 109 compounds (62 perfume compounds). Furthermore, the capability of thin-layer chromatography-Gas Analyzer approach to analyze the isomers in this complex sample was demonstrated.

Formaldehyde and VOC emissions from plywood panels bonded with bio-oil phenolic resins

Pyrolysis bio-oil was used to partially substitute for phenol in reacting with formaldehyde for the production of bio-oil phenol formaldehyde plywood (BPFP) panels, with the phenol substitution ratio being 20%, 40%, or 60%. Emissions of formaldehyde and volatile organic compounds (VOCs) from the BPFP panels were studied using solid-phase micro-extraction (SPME) followed by headspace gas chromatography/mass spectrometry (GC/MS), and were compared to those from the phenol formaldehyde plywood (PFP) panels. The sources for VOCs were analyzed, and the health risks associated with the BPFP were examined. Results showed that at 80 °C: (1) Formaldehyde emissions from the BPFP panels were increased to about 4 times that of PFP; (2) VOCs emissions were significantly reduced by up to 84.9% mainly due to the greatly reduced phenol emissions, although the total number of VOCs was increased from 20 to 35; (3) BPFP presents greatly increased carcinogenic and non-carcinogenic health risks because of its much stronger emissions of formaldehyde, N,N-dimethylformamide, benzofuran, furfural, and many chemicals from the bio-oil. It is highly advisable that the health risks are properly taken care of before the wide application of BPFP, or similar bio-oil based engineered wood products.

Determination of 5-MeO-DIPT in Human Urine Using Gas Chromatography Coupled with High-Resolution Orbitrap Mass Spectrometry

5-Methoxy-N,N-Diisopropyltryptamine (5-MeO-DIPT) is a designer hallucinogen derived from tryptamine and its use has been banned by many countries. In this study, a qualitative and quantitative method was developed for determining 5-MeO-DIPT in urine by gas chromatography high-resolution mass spectrometry. 5-hydroxy-N,N-diisopropyltryptamine (5-OH-DIPT) and 5-methoxy-N-isopropyltryptamine (5-MeO-IPT) were identified as 5-MeO-DIPT metabolites in abusers’ urine. 5-MeO-DIPT was extracted from urine by liquid–liquid extraction with ethyl acetate under alkaline conditions. The extract was analyzed by GC-Orbitrap-MS in full scan mode with a resolution of 60,000 full width at half maxima (FWHM). The linear range of this method was 2–300 ng/mL with r > 0.99, and the limit of detection was 1 ng/mL. The accuracy and precision were 93–108.7% and 3.1–10.3%, respectively. This method is simple and sensitive. It has been successfully used to detect 5-MeO-DIPT in drug abusers’ urine, which showed that the concentrations of 5-MeO-DIPT were between 1 and 2.8 ng/mL. 5-OH-DIPT and 5-MeO-IPT, two urinary major metabolites of 5-MeO-DIPT, were identified in urine samples from 5-MeO-DIPT users. Furthermore, the stability of 5-MeO-DIPT in human urine was investigated. It was discovered that the concentration of 5-MeO-DIPT in urine decreased by 22.8, 33.2 and 38.2% after samples were stored for 24 h at 25°C, 5 days at 4°C and 7 days at 4°C, respectively. And 5-MeO-DIPT in urine were stable after they were stored for 30 days at −20°C. Therefore, it is recommended that urine should be stored under freezing conditions before performing 5-MeO-DIPT analysis.

Release of Fragrances from Cotton Functionalized with Carbohydrate-Binding Module Proteins

Perspiration as a response to daily activity and physical exercise results in unpleasant odors that cause social unrest and embarrassment. To tackle it, functional textiles incorporating fragrances could be an effective clothing deodorizing product. This work presents two strategies for the release of β-citronellol from functionalized cotton with carbohydrate-binding module (CBM)-based complexes (OBP::GQ₂₀::CBM/β-citronellol-approach 1 and CBM::GQ₂₀::SP-DS3-liposome/β-citronellol-approach 2). CBM from Cellulomonas fimi was fused with the odorant-binding protein (OBP::GQ₂₀::CBM) and with an anchor peptide with affinity to the liposome membrane (CBM::GQ₂₀::SP-DS3). In approach 1, OBP fusion protein served as a fragrance container, whereas in approach 2, the fragrance was loaded into liposomes with a higher cargo capacity. The two strategies showed a differentiated β-citronellol release profile triggered by an acidic sweat solution. OBP::GQ₂₀::CBM complex revealed a fast release (31.9% and 25.8% of the initial amount, after 1.5 and 24 h of exposure with acidic sweat solution, respectively), while the CBM::GQ₂₀::SP-DS3-liposome complex demonstrated a slower and controlled release (5.9% and 10.5% of the initial amount, after 1.5 and 24 h of exposure with acidic sweat solution, respectively). Both strategies revealed high potential for textile functionalization aimed at controlled release of fragrances. The OBP::GQ₂₀::CBM/β-citronellol complex is ideal for applications requiring fast release of a high amount of fragrance, whereas the CBM::GQ₂₀::SP-DS3-liposome/β-citronellol complex is more suitable for prolonged and controlled release of a lower amount of β-citronellol.

Fragrance transfer between fabrics for forensic reconstruction applications

Sexual assault is a serious crime that often has low conviction rates. Recent literature has demonstrated that there is potential for fragrances to be valuable in forensic reconstructions where there has been contact between individuals. However, developing appropriate evidence bases for understanding the nature of fragrance transfer in these contexts is needed. This article presents three experiments that address the transfer process of fragrances that have been transferred from a primary piece of fabric onto a secondary piece of fabric, in a manner that could occur during an assault. The three variables studied were the ageing time of the fragrances on the first fabric prior to transfer, the contact time between the two fabrics, and lastly the fabric type (of the primary material and the recipient material). The transfer was evaluated using a validated solid phase micro-extraction gas chromatography-mass spectrometry (SPME GC-MS) method. The findings demonstrated that all three variables had an impact on the transfer of fragrances between clothing fabrics. Generally, lower volatility compounds were transferred and recovered in larger amounts than higher volatility compounds. All fragrance compounds were successfully recovered from a secondary piece of fabric even when the contact time was as short as 10 s, and even when the perfume was aged on the primary fabric for as long as 48 h. The nature of the fragrance transfer also depended on the fabric type, so that a clear discrimination was observed between the fragrance transfer that occurred onto a natural fabric (cotton) and onto a synthetic fabric (polyester).