Comparing the Flavour Profiles of Soft Drink Brands Using Immersive Sorptive Extraction, GC×GC–TOF-MS, and Chemometrics


Immersion adsorption extraction combined with comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry (GC×GC–TOF-MS) was used to mimic the flavor profiles of popular brands of soft drinks. compared to

Immersion adsorption extraction combined with comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry (GC×GC–TOF-MS) was used to mimic the flavor profiles of popular brands of soft drinks. compared to

Unlike counterfeits, replicas and imitations are legal because they do not use the branded product’s trademark. In the food and beverage industry, counterfeiters attempt to mimic the taste experience of popular branded products.

However, flavor profiles are very complex and consist of a wide range of chemical classes, the combination of which ultimately determines consumer preference for a particular brand. It is important to be able to confidently identify these volatiles not only during product development, but also in quality and reliability studies.

Traditional sample preparation methods such as headspace and solid-phase microextraction (SPME) are widely used but often have limitations in terms of sensitivity. Furthermore, sampling is generally limited to headspace volatiles. In this article, we use high-capacity adsorptive extraction with novel trap-based focusing to increase sensitivity and improve chromatographic performance, and perform both headspace and immersion sampling to cover a wider range of polar and Shows how to achieve compatibility with semi-volatiles. Specimen. This improved performance, combined with improved separation by comprehensive two-dimensional gas chromatography (GC×GC) and detection by time-of-flight mass spectrometry (TOF-MS), provides greater insight into sample composition. can.

However, sampling, isolation, and detection are just the beginning. We need to reduce the resulting dataset to be able to discover significant differences and finally reach meaningful conclusions. This article also describes how chemometrics can be used to transform complex datasets into usable results. The approach used ensures that trace peaks are not ignored and automated workflows can be employed. This workflow is presented to compare branded and imitation cola-flavored soft drinks.

experimental

Five store-bought cola-flavored soft drinks were purchased from different suppliers. Sampling and analysis were performed in triplicate for each soft drink.

The following experimental conditions and equipment were used. For immersive sampling, a HiSorb large capacity adsorption extraction probe was used (PDMS/CWR/DVB, Markes International). Full automation was performed on the Centri extraction and enrichment platform (Markes International). GC×GC: Insight Flow Modulator (SepSolve Analytical); modulation period (PM) = 2.5 s. TOF-MS: BenchTOF2 mass spectrometer (SepSolve Analytical); mass range: m/z= 40 to 350; ionization energies: tandem ionization at 70 eV and 14 eV. Software: ChromSpace software (SepSolve Analytical) for full instrument control and processing, and chemometric comparisons with ChromCompare+ (SepSolve Analytical).

Results and discussion

The combination of high-capacity adsorptive extraction and GC×GC–TOF-MS enabled efficient separation and confident identification of a wide range of chemical classes.

Additional chemical details regarding the soft drink composition are clearly shown in Figure 1. Four co-eluting compounds are highlighted in the traditional one-dimensional (1D) analysis, but are separated in the second dimension and confidently identified using spectral analysis. TOF-MS quality and mass accuracy (Figure 2).

In this study, this workflow was used to analyze five “Cola” soft drinks from different manufacturers. To identify compositional differences between soft drink brands, an untargeted, tile-based workflow was applied to the software, comparing all raw data and automatically identifying the most significant differences between sample classes. it was done.

The resulting principal component analysis (PCA) score plot (Figure 3) shows clear clustering of the different brands. Interestingly, brands B and E are both ‘diet’ soft drinks from different manufacturers and are clustered separately from the ‘zero sugar’ brands.

Benzyl benzoate was found to be a key differentiator for Brand D (Figure 4, left) and may contribute to the fruity flavor of the balsamic. Additionally, trans-cinnamaldehyde (Figure 4, right) was found to distinguish between the ‘diet’ and ‘zero sugar’ classes.

The software’s volcano plot was also used to directly compare imitation cola to popular branded products. An example is shown in Figure 5.

Figure 5 also shows the reference quality spectrum of the MS analysis. This allowed us to reliably identify potential markers for branded and/or counterfeit cola products. Also note that the tandem ionization data were acquired at 70 eV and 14 eV in this study. Tandem data were used to confirm positive hits, improving the discovery of subtle trace differences by reducing the frequency of false positives (2).

Conclusion

In this study, an end-to-end non-targeted workflow for aroma profiling of food and beverages was demonstrated. This workflow consists of fully automated, immersive sampling of a wide range of aroma-active volatiles using high-capacity adsorption extraction. Enhanced separation by GC×GC using consumable-free flow modulation yielded a comprehensive aroma profile. Sensitive detection and reliable identification of analytes was achieved using TOF-MS. Chemometrics provided an automated workflow for alignment and comparison of complex chromatograms.

References

  1. The Good Scents Company Information System (search function)http://www.thegoodscentscompany.com/search2.html (accessed 20 June 2022).
  2. SepSolve, SepSolve Analytical White Paper 041: Improving Discovery Workflows Using Tandem Ionization Datahttps://www.sepsolve.com/white-papers/overview/technical-note-improving-discovery-workflows-using-tandem-ionisation-data.aspx (accessed 19 December 2022).

Laura McGregor I got M.Chem. After completing his PhD in Chemistry at the University of Andrews in St. England, he completed his Master of Science. He holds a PhD in Forensic Medicine from the University of Strathclyde, UK. She received her PhD in Environmental Forensics, also from the University of Strathclyde, with a focus on chemical fingerprinting of environmental contamination using advanced techniques such as GC×GC-TOF-MS. In her current role at SepSolve Analytical, she specializes in applying her GCxGC and her TOF-MS to challenging applications.

Eleanor Hughes got her bachelor’s degree. She has a degree in Chemistry and her Ph.D. She holds a PhD in Organic Chemistry from Bangor University, UK. In a chemical manufacturing company she worked for three years before she moved to the Royal Society of Chemistry, where she worked for six years in the publishing of magazines. chemical world magazine for four years. She then worked as a freelance copy editor and writer for Science Her for five years. Her current role is technical her copywriter for Markes International.

James Ogden He worked in environmental analysis labs for 9 years, responsible for method testing, development and implementation. In his current role at SepSolve Analytical, James supports customers through the development, demonstration and delivery of analytical methods across the company’s instrument and software portfolio.



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