Recent Advances in Headspace Gas Chromatography

Simultaneous component analysis as an interesting preliminary data analysis method in GC-MS – An example of headspace screening of Polish grasses

70 species of grasses family (Poaceae), coming from genera: Agrostis, Alopecurus, Anthoxanthum, Apera, Arrhenatherum, Avena, Brachypodium, Briza, Bromus, Calamagrostis, Corynephorus, Cynosurus, Dactylis, Danthonia, Deschampsia, Digitaria, Echinochloa, Elymus, Eragrostis, Festuca, Glyceria, Helictotrichon, Hierochloe, Holcus, Hordeum, Koeleria, Leymus, Lolium, Milium, Molinia, Nardus, Panicum, Phalaris, Phleum, Phragmites, Poa, Saccharum and Setaria, collected mostly from natural stands in Poland during 2020 season, were subjected to GC-MS fingerprinting of headspace volatile fraction above dried material. Obtained mass spectrometry data were analyzed by means of principal component analysis (PCA) and hierarchical cluster analysis (HCA). Five species: Glyceria maxima (Hartm.) Holmb., Lolium multiflorum Lam., Hordeum jubatum L., Bromus tectorum L. and Bromus secalinus L. were identified as outliers, which is consistent with our earlier analysis by thin layer chromatography. These species deserve further look and their outliance is orthogonal to coumarin content, which was independently observed for odorant species of grasses.

[Determination of silanol group content on the surface of fumed silica by chemical reaction-headspace gas chromatography]

Fumed silica is prepared by flame pyrolysis, where silicon halide is combusted in an oxygen-hydrogen flame, resulting in finely dispersed and thermally stable silicon dioxide. Because of its unique physical and chemical properties, including high porosity, large pore volumes, large specific area, and high chemical activity, fumed silica is widely used in rubbers, plastics, adhesives, paints, and printing inks for reinforcement, as well as in thixotropy, anti-setting, and anti-sagging applications. These functional properties of fumed silica are related to the silanol group on its surface. However, there is no accurate and convenient test method to determine the silanol group content on the surface of fumed silica. This work explores a novel method to determine the silanol group content on the surface of fumed silica by chemical reaction-headspace gas chromatography (HS-GC). Theoretically, by this method, the silanol group can rapidly react with the Grignard reagent and generate methane, the amount of which can be determined accurately by GC analysis. GC analysis was conducted using a headspace flask as a closed reactor to transform the silanol group into a volatile component through a chemical reaction, so as to realize the accurate determination of silica hydroxyl. The amount of methane produced in the reaction was directly proportional to the content of silanol groups on the surface of fumed silica. Therefore, the silanol group content was calculated using the chemical reaction equation. Before the experiment, fumed silica was dried for 2 h in an oven at 105 ℃ to remove adsorbed moisture. The dried fumed silica sample was then reacted with the Grignard reagent dispersed in toluene in an airtight reaction bottle. Toluene was used as a dispersion agent to promote contact and reaction between the fumed silica sample and Grignard reagent. The methane produced by the reaction was injected into a gas chromatograph for separation and further detected using a flame ionization detector (FID). Methane was quantified from the peak areas of the GC signals using the external standard method, and the silanol content in the sample was obtained. Simultaneously, factors influencing the outcome of the method, such as the dosage of the Grignard reagent and reaction time with it, were optimized by a comparison test. Accordingly, 2.0 mL of 0.3 mol/L Grignard reagent and a reaction time of 15 min were found to be optimal for testing. The test results showed that there was good linear correlation between the content of the silanol group and the GC signals, with a correlation coefficient of 0.9990. The limit of detection was 0.30 mg/g, and the limit of quantification was 1.00 mg/g. The relative standard deviation of reproducibility was less than 3%. Based on an interlaboratory test conducted by four laboratories on five samples with different silanol group contents, the repeatability limit (r) was less than 2.5%, and the reproducibility limit (R) was less than 6.5%. Compared with the traditional chemical method, the method involving HS-GC presents distinct advantages in terms of lower reagent consumption, high sensitivity, good stability, and reliability. It is suitable for the rapid detection of the silanol group content on the surface of fumed silica, and can aid in the quality control of fumed silica during its production and application. This method has important theoretical and practical significance for developing accurate methods to determine silica hydroxyl in the silicon industry for standards and the optimization of industrial technology. This study serves as a foundation to standardize and promote the rapid development of silicon material-related industries.

Validating Differential Volatilome Profiles in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that does not currently have a robust clinical diagnostic test. Nonmotor symptoms such as skin disorders have long since been associated with the disease, and more recently a characteristic odor emanating from the skin of people with Parkinson's has been identified. Here, dynamic head space (DHS) thermal desorption (TD) gas chromatography-mass spectrometry (GC-MS) is implemented to directly measure the volatile components of sebum on swabs sampled from people with Parkinson's-both drug naïve and those on PD medications (n = 100) and control subjects (n = 29). Supervised multivariate analyses of data showed 84.4% correct classification of PD cases using all detected volatile compounds. Variable importance in projection (VIP) scores were generated from these data, which revealed eight features with VIP > 1 and p < 0.05 which all presented a downregulation within the control cohorts. Purified standards based on previously annotated analytes of interest eicosane and octadecanal did not match to patient sample data, although multiple metabolite features are annotated with these compounds all with high spectral matches indicating the presence of a series of similar structured species. DHS-TD-GC-MS analysis of a range of lipid standards has revealed the presence of common hydrocarbon species rather than differentiated intact compounds which are hypothesized to be breakdown products of lipids. This replication study validates that a differential volatile profile between control and PD cohorts can be measured using an analytical method that measures volatile compounds directly from skin swabs.

Effect of Different Drying Methods on Nutrient Quality of the Yellow Mealworm (Tenebrio molitor L.)

Yellow mealworm (Tenebrio molitor L.) represents a sustainable source of proteins and fatty acids for feed and food. Industrial production of mealworms necessitates optimized processing techniques, where drying as the first postharvest procedure is of utmost importance for the quality of the final product. This study examines the nutritional quality of mealworm larvae processed by rack oven drying, vacuum drying or freeze drying, respectively. Proximate composition and fatty acid profile were comparable between the dried larvae. In contrast, larvae color impressions and volatile compound profiles were very much dependent on processing procedure. High-temperature rack oven drying caused pronounced darkening with rather low content of volatiles, pointing toward the progress of Maillard reaction. On the other hand, vacuum drying or freeze drying led to enrichment of volatile Maillard reaction and lipid oxidation intermediates, whose actual sensory relevance needs to be clarified in the future. Beyond sensory and visual importance drying intermediates have to be considered with regard to their metal ion chelating ability; in particular for essential trace elements such as Zn²⁺. This study found comparable total zinc contents for the differently dried mealworm samples. However, dried larvae, in particular after rack oven drying, had only low zinc accessibility, which was between 20% and 40%. Therefore, bioaccessibility rather than total zinc has to be considered when their contribution to meeting the nutritional requirements for zinc in humans and animals is evaluated.

Quantitative Detection of Ethanol/Acetone in Complex Solutions Using Raman Spectroscopy Based on Headspace Gas Analysis

This paper demonstrated the quantitative detection of ethanol and acetone mixtures in complex solutions with Raman spectroscopy based on headspace gas analysis. By analyzing the volatile components in the headspace, their concentrations in liquid solutions were determined. We constructed our own Raman spectroscopy system to detect the headspace gas quantitatively over a solution in a sealed vial. The Raman spectra of the headspace gases over standard solutions were standardized for finding the concentrations of ethanol, acetone, and ethanol-acetone in mixture solutions. The results showed that the concentration of a gaseous component in the headspace gas was proportional to its ratio in the liquid solution. We obtained a linear relationship between the spectral intensity of volatile components in headspace and the concentration of the liquid solutions. Then, we analyzed the alcohol concentration in a white wine and a Chinese liquor called Fen Chiew by measuring the Raman spectra of the headspace gas over their liquids. For the river water sample, we also implemented our headspace gas detection with Raman spectra to obtain the concentration of acetone in the river sample. This work demonstrated the facilitation of headspace gas analysis by the qualitative and quantitative determination of volatile substances from liquid samples using Raman spectroscopy.

Volatile Metabolites Emission by In Vivo Microalgae-An Overlooked Opportunity?

Fragrances and malodors are ubiquitous in the environment, arising from natural and artificial processes, by the generation of volatile organic compounds (VOCs). Although VOCs constitute only a fraction of the metabolites produced by an organism, the detection of VOCs has a broad range of civilian, industrial, military, medical, and national security applications. The VOC metabolic profile of an organism has been referred to as its 'volatilome' (or 'volatome') and the study of volatilome/volatome is characterized as 'volatilomics', a relatively new category in the 'omics' arena. There is considerable literature on VOCs extracted destructively from microalgae for applications such as food, natural products chemistry, and biofuels. VOC emissions from living (in vivo) microalgae too are being increasingly appreciated as potential real-time indicators of the organism's state of health (SoH) along with their contributions to the environment and ecology. This review summarizes VOC emissions from in vivo microalgae; tools and techniques for the collection, storage, transport, detection, and pattern analysis of VOC emissions; linking certain VOCs to biosynthetic/metabolic pathways; and the role of VOCs in microalgae growth, infochemical activities, predator-prey interactions, and general SoH.

Chemometric analysis of volatiles of propolis from different regions using static headspace GC-MS

Six samples of propolis were analyzed in the paper: a sample from Brazil, Estonia, China and three samples from different locations of Uruguay. Static headspace technique coupled with gas chromatography-mass spectrometry analysis has been applied for the determination of the characteristic volatile profile with the aim to differentiate the propolis from different regions. Monoterpenes (α- and β-pinenes) were predominant in all samples, except the sample from China. This sample separated itself by the alcohols 3-methyl-3-buten-1-ol and 3-methyl-2-buten-1-ol, (40.33% and 11.57%, respectively) and ester 4-penten-1-yl acetate (9.04%). α-Pinene and β-pinene composed 64.59–77.56% of volatiles in Brazilian and Uruguayan propolis, and 29.43% in Estonian propolis. Brazilian propolis was distinguished by a high amount of β-methyl crotonaldehyde (10.11%), one of Uruguayan samples 3- by limonene (15.58%), and the Estonian sample — by eucalyptol (25.95%). Statistical investigation of the samples was made applying principal component, hierarchical cluster and K-Means cluster analyses. Various data pre-processing techniques were proposed and used to study and obtain the important volatile compounds contributed to the differentiation of the propolis samples from different regions to separate clusters.

Establishment and application of a metabolomics workflow for identification and profiling of volatiles from leaves of Vitis vinifera by HS-SPME-GC-MS

INTRODUCTION

Volatile organic compounds (VOCs) occurring in leaves of plants carry information about the physiological state of the plant. Monitoring of VOCs assists in detecting plant stress before visible signs are present.

OBJECTIVE

To establish and apply a simple workflow for the automated extraction, measurement and annotation/identification of Vitis vinifera cv. Pinot Noir leaf metabolites.

METHODOLOGY

Leaf samples were harvested, cooled with liquid nitrogen and homogenised under cooled conditions. VOCs were extracted and enriched by solid phase microextraction (SPME) and analysed by GC-MS. Samples were measured on two columns with different polarity of stationary phases. Mass spectral deconvolution and identification was done by AMDIS software. Strict identification criteria were applied: match factor ≥ 90; relative retention index deviation ≤ 2% from reference value on both columns. Data of two sampling dates were analysed with multivariate statistics.

RESULTS

We found ~600 components in a single chromatogram. Applying the mentioned criteria resulted in annotation of 63 metabolites of which 47 were confirmed with authentic standards. For the majority of the compounds technical variability was < < 40% (RSD), biological variability among plants was 7-119%. Principal component analysis (PCA) scores plot of leaf samples from two different sampling dates showed two clearly separated clusters. The presented workflow enabled for the first time the detection and identification of 19 metabolites that have so far not been described for Vitis spp.

CONCLUSION

The developed workflow enabled the identification of grapevine leaf metabolites, which allowed the separation of leaves from two sampling dates by PCA.