74 research outputs found
Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry: Toward a Super-Resolved Separation Technique
No full textA data interpretation and processing approach for improved compound identification and data presentation in comprehensive two-dimensional gas chromatography (GC×GC) is described. A footprint peak of a compound in 2D space can be represented by a centroid or peak apex, similar to the data-reduced histogram spectra used in mass spectrometry. The workflow was demonstrated on data from GC×GC-TOFMS. Peaks in a modulated chromatogram were initially detected by conventional chromatographic integration, followed by a curve-fitting approach, which interpolated high-precision, absolute retention times for all modulated peaks. First dimension retention time (1tR) was obtained by using an exponentially modified Gaussian (EMG) fitting model for near-Gaussian distributed subpeaks, polynomial fitting for highly asymmetrical peaks, and parabolic fitting for under-sampled peaks, which allows determination of a precise 1tR, considering the dwell-time arising from modulation and 2tR. Area summation of the modulated peaks belonging to the same compound was then performed to yield the total peak area. Each compound in the GC×GC-MS result was then represented by its position at the intersecting coordinates, (1tR, 2tR), in the 2D separation plane, having a height of the same magnitude as the total component summed area. This results in a novel and uncluttered GC×GC output convention based on the scripted total ion chromatogram (TIC) data with precise 1tR, 2tR, and area. Comparison between the contour plots from the scripted and conventional TIC revealed improved data presentation, accompanied by an apparent enhanced resolution. The described approach was applied to the identification of 177 aroma compounds from peaches as indicators of fruit quality
Determination of 2-Methyisoborneol and Geosmin as Malodours in Catfish for Quality Control Using a Fully Automated Sample Prep Platform Coupled with Gas Chromatography and Mass Spectrometry
No full textAccumulation of off-flavours and odours in fish flesh are a major contributor towards a decrease in fish meat quality because of the dislike by consumers. This is typically caused by two compounds, geosmin (GM) and 2-methylisoborneol (2-MIB),
produced as secondary by-products of bacterial metabolism in water. These compounds have very low human sensory detection limits (or odour thresholds), which means that they can be present at trace-levels and still be detected with a
human nose. Due to the lipophilic properties of these compounds their extraction from the fish tissue and subsequent
analysis can be hindered due to simultaneous extraction of other volatile organic compounds (VOCs) which are present at
much higher concentration levels. Lengthy extraction techniques such as steam distillation are typically required to extract
the target compounds from the other VOCs present, producing cleaner chromatography. However, this is time consuming
and manually labour-intensive for the analyst.
Here we demonstrate a simple, solvent-free and fully-automated technique using high-capacity sorptive extraction (HiSorb)
coupled with Gas Chromatography and Mass Spectrometry for the identification of GM and 2-MIB at ppt-levels (pg/g) in
catfish samples. The ‘prep-ahead’ functionality of the extraction and enrichment platform, Centri, provided enhanced
sample management for increased sample throughput without compromising analytical sensitivity
Classification of olive oil and geographical origin by using a multi-cumulative trapping HS-SPME-GC-MS follow by a novel data handling software
No full textThe sensory attributes of extra virgin olive oil, and in particular specific aroma defects, are officially responsible for oil classification (or declassification) into extra virgin, virgin or lampante olive oil. Undoubtedly, volatile compounds play a crucial role in defining olive oil sensory quality and research efforts have been dedicated to unravel the composition of this informative fraction, to better understand correlations with quality attributes. The relative distribution of volatiles depends on several parameters (i.e., cultivar, geographical origin, fruit ripeness, processing practices, and storage) meaning the identification of an unequivocal fingerprint correlated to quality and authenticity is a difficult task. Most of these variables contribute towards the intensity and quality of the green and fruity perception, while the presence of defects is mainly due to inappropriate manufacturing practices. Multiple-cumulative trapping headspace-solid-phase microextraction (named MC-SPME) is a powerful technique proven to enhance the level of information on the volatile profile. Shorter cumulative extraction times, using a low volume of sample to avoid headspace saturation proved effective for discriminating between different qualities of olive oil (i.e. extra-virgin, virgin and lampante oil) as well as the different geographical origins among the extra virgin oils. The use of a novel data mining and chemometrics software enabled automatic alignment of chromatograms and extraction of useful information in a simple and straightforward way, supporting the routine application of this approach to corroborate sensory panel analysis
Volatile and semi-volatile compounds in flavoured hard seltzer beverages: comparison of high-capacity sorptive extraction (HiSorb) methods
No full textThe change in consumer behaviour towards healthier lifestyles since the Covid-19 pandemic has seen a steep rise in popularity of low-calorie, low-sugar food and beverage alternatives, like flavoured hard seltzers. In this study, a fully automated, high-capacity sorptive extraction (HiSorb) technique, coupled with gas chromatography–mass spectrometry (GC–MS), was developed to investigate volatile and semi-volatile organic compounds (VOCs and SVOCs) used for flavouring of hard seltzers. As part of methos optimisation we trialled various sample preparation protocols and compared extraction via direct immersion vs. extraction from the headspace. The best headspace and immersive techniques were then further analysed in a ‘stacked’ extraction, whereby extracts from both were collected onto a focusing trap and fired to the GC to produce a single chromatogram. HiSorb probes with 4 alternate phases were compared: Polydimethylsiloxane (PDMS), divinylbenzene/PDMS (DVB/PDMS), carbon wide range/ PDMS (CWR/PDMS) and a triple phase (DVB/CWR/PDMS), with the DVB/PDMS phase proving to extract the highest number of compounds. The DVB/PDMS probe was further applied to a study of four berry/cherry flavour hard seltzer drinks, produced by 4 different leading commercial brands, with 64 compounds extracted and identified. Chemometrics were able to distinguish each brand's flavour profile by detection of unique compounds, these having potential for use as quality and authenticity markers
Unraveling the impact of the capsule material on the aroma of brewed coffee by headspace analysis using a HiSorb probe followed by reverse fill/flush flow modulation GC×GC-MS
No full textThe present paper discusses the use of a high-concentration-capacity tool, HiSorb, to investigate the impact of capsule material on the aroma profile of espresso-brewed coffee. The specific high-concentration-capacity probe used is characterized by a sorbent volume (63 μL) intermediate between the solid-phase microextraction (SPME) fiber (0.6 μL) and the stir-bar sorptive extraction rod (126 μL). The extraction performance of the HiSorb was compared, in terms of both absolute signal and compound coverage, with both an equivalent sorbent (polydimethylsiloxane) and a divinylbenzene/carboxen/polydimethylsiloxane SPME fiber using both targeted and untargeted approaches. The HiSorb showed superior extraction compared with the SPME fibers. The HiSorb was then optimized in terms of extraction time and temperature and used to investigate the volatile profile of 23 espresso-brewed coffees prepared with capsules made of different materials-aluminum, compostable, and aluminum multilayer pack-prepared using a refillable capsule. Comprehensive two-dimensional gas chromatography equipped with a reverse fill/flush flow modulator and coupled to mass spectrometry was used to obtain a chromatographic fingerprint of the volatile profile of the brewed coffee. The data were aligned and compared using a tile-based approach, and the results were obtained by performing raw data mining within the same software platform. The data mining enabled the extraction of informative features responsible for the differentiation between the different capsule materials, showing a significant depletion in aroma intensity in the compostable capsule
Vacuum-assisted and multi-cumulative trapping in headspace solid-phase microextraction combined with comprehensive multidimensional chromatography-mass spectrometry for profiling virgin olive oil aroma
No full textIn the present work vacuum (Vac) and multiple cumulative trapping (MCT) headspace solid phase microextraction (HS-SPME) were evaluated as alternative or combined techniques for the volatile profiling. A higher extraction performance for semi-volatiles was shown by all three techniques. Synergic combination of Vac and MCT showed up to 5-times extraction power for less volatile compounds. The hyphenation of said techniques with comprehensive two-dimensional gas chromatography (GC × GC) enabled a comprehensive analysis of the volatilome. Firstly, 18 targeted quality markers, previously defined by means of classical HS-SPME, were explored for their ability to classify commercial categories. The applicability of such markers proved to be limited with the alternative sampling techniques. An untargeted approach enables the selection of specific features for each technique showing a better classification capacity of the commercial categories. No misclassifications were observed, except for one extra virgin olive oil classified as virgin olive oil in 3 × 10 min Vac-MCT-HS-SPME
Molecular Investigations of Peach Post-Harvest Ripening Processes and VOC Biosynthesis Pathways: A Review Focused on Integrated Genomic, Transcriptomic, and Metabolomic Approaches
No full textPeach (Prunus persica L.) represents a very important model plant given its small and publicly accessible genome, the availability of homozygous doubled haploids, and its taxonomic similarity to other popular stone fruits. Albeit it is an economically important crop with a great production potential, the consumption of peach is still considered low in comparison with that of other fresh fruits, such as apple and banana. A way to increase it could be to improve its quality and aroma, which tend to be affected during the often-prolonged storage and transport periods. Recently, substantial research efforts have been directed towards the characterisation of the regulatory mechanisms underlying the hormonal, transcriptomic, and metabolomic changes happening during peach fruit post-harvest ripening. Biosynthesis pathways of volatile organic compounds related to changes in aroma have also been investigated. Due to advances in next-generation sequencing, new insights into the molecular functions of peach genes have been gained. Studies have mapped out the molecular bases of peach fruit post-harvest ripening using a multi-omics approach, combining genomic, transcriptomic, and metabolomic methods. This review aims to discuss the most relevant recent research results in this area in order to provide a useful starting point for researchers in the field and future perspectives for improving peach quality
Aroma Discovery of Low-cost to Luxury Honey Using a High-Capacity Sorptive Extraction Technique (HiSorb) and Gas Chromatography Mass Spectrometry
No full textHoney is sold on a global scale and the market can be largely influenced by increasing concerns over product quality and
authenticity. Volatile organic compounds (VOCs) are responsible for the aroma of this natural product, providing
characteristic aromatic bouquets. The combined effect of several factors contributes to the distinct aromas, namely climate
conditions, geographical location of production, flower nectar composition and post-harvest processes. The VOCs
identified range both in compound class and molecular weight, with some key distinguishing compounds being present at
low levels, making the analytical process challenging and time spent data processing laborious.
Here we demonstrate a simple, solvent-free method for fingerprinting different honey qualities through fully-automated
sample extraction and enrichment by a high-capacity sorptive extraction technique (HiSorb), coupled to Gas
Chromatography Mass Spectrometry. Data mining and chemometrics are combined into one easy-to-use platform, for
rapid identification of key differences between the VOC profiles.
By identifying unique signatures amongst shared ubiquitous VOCs, we will show how this helps to distinguish between
commercial low-cost to luxury brands and locally produced honey
Multi-Cumulative Trapping HS-SPME-GC-MS in combination of with a novel data handling software for quality and geographical origin classification of virgin olive oil
No full textUnderstanding consumer preference of hard seltzer drinks using advanced analytical tools with sensory data correlation
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