Enhanced odour profiling of strawberries using TD GC TOF MS

Transcription

1 Application Released: April 213 Application Note 515 Enhanced odour profiling of strawberries using TD GC TOF MS Summary This Application Note describes the application of a BenchTOF time-of-flight mass spectrometer to enhance the detection of trace-level components in the headspace gas above fresh strawberries. At the same time, the versatility of TargetView compound identification software is demonstrated by an all-component search against NIST and by a targeted search for various odour-active sulfur compounds. Introduction Food aroma profiles typically contain components at a wide range of concentrations, though very often some of the most odour-active components are only present at trace levels. In such situations a highly sensitive detector is essential to maximise the prospects for analyte detection and identification. Background to BenchTOF instruments Markes BenchTOF time-of-flight mass spectrometers are ideally suited for the analysis of such samples, the following three features being of particular importance: Sensitivity: Highly efficient direct-extraction technology allows BenchTOF instruments to acquire full-range spectra with SIM-like sensitivity, allowing them to reliably detect trace-level analytes in a single run, which would be difficult or impossible on a quadrupole system. Spectral quality: The reference-quality spectra produced by BenchTOF are a close match for those in commercial libraries such as NIST or Wiley. This enables quick and confident matching of both targets and unknowns. Speed: The ability to record full-range mass spectral information to extremely high densities (1, transient spectral accumulations per second) enables advanced spectral deconvolution and data-mining algorithms to extract maximum information from weak, matrix-masked signals. Background to TargetView The advantages of BenchTOF instruments are enhanced by TargetView, an innovative post-run data processing package that allows accurate and automated identification of trace compounds in complex GC MS profiles. TargetView uses sophisticated algorithms to eliminate background interference and deconvolve co-eluting components into individual analyte peaks. The mass spectra produced for each deconvolved component can then be rapidly matched against library spectra using advanced chemometric techniques, which allow both target and unknown compounds to be identified confidently, even at trace levels. Total ion chromatographic (TIC) profiles can either be searched against a target library (a target search ), or screened against the full NIST library (an all-component search ). TargetView is easy to learn, simple to operate, and compatible with GC MS file types from most major vendors. Experimental The extraction and analysis process is depicted schematically in Figure 1. Note that the microchamber system is able to accommodate whole strawberries, which would be not be possible with a standard 2 ml headspace vial. Sampling: Instrument: Chambers: Micro-Chamber/Thermal Extractor (Markes International) (six-chamber version) Inert-coated stainless-steel, 44 ml capacity Chamber temp.: 4 C Equilibration: 5 ml/min of dry nitrogen for 1 min Sampling flow: 2 min using 5 ml/min dry nitrogen Headspace volume: 1 ml sampled Sorbent tubes: Quartz wool Tenax TA SulfiCarb Formerly ALMSCO Application Note 15.

2 Page 2 Place strawberry in microchamber pot and weigh sample. Load pot into the Micro-Chamber/ Thermal Extractor. Attach sorbent tube, pass heated N 2 into the chamber, and collect released vapours. Load tube into the TD-1 automated thermal desorber and......analyse vapours by GC TOF MS. Identify compounds using TargetView software. Figure 1: Flow chart showing the process used to sample and identify the volatile compounds released from whole strawberries. TD: Instrument: TD-1 (Markes International) Flow path temp.: 16 C Focusing trap: Material Emissions Trap Dry-purge: 2 min, 2 ml/min flow Primary (tube) desorption: 12 C for 5 min, then 26 C for 5 min; 4 ml/min trap flow Pre-trap-fire purge: 2 min; 5 ml/min trap flow; 2 ml/min split flow Secondary (trap) desorption: TD split: Trap low: 25 C; trap high: 3 C; heating rate: 24 C/s; hold time: 5. min; split flow: 2 ml/min 21:1 outlet split GC MS System 1: GC: Column: Rtx-5MS 6 m.25 mm.5 µm Carrier: He, constant flow 1. ml/min Temp. programme: 4 C (5. min), 1 C/min to 3 C (5. min) Total run time: 36. min TOF MS: Instrument: BenchTOF (Markes International) Ion source: 28 C Transfer line: 2 C Mass range: m/z Data rate: 2 Hz (5 spectral accumulations per data point) Filament voltage: 1.6 V GC MS System 2: GC: Column: DB-5, 6 m.25 mm.5 µm Carrier: He, constant flow 1. ml/min Temp. programme: 4 C (5. min), 1 C/min to 3 C (5. min) Total run time: 36. min Quadrupole MS: Ion source: 23 C Quadrupole: 15 C Transfer line: 28 C Mass range: m/z Data rate: 5 Hz Gain factor: 1 Results and discussion Analysis of strawberry headspace An example emission profile of a whole strawberry is shown in Figure 2. This chromatogram has been processed by TargetView to remove unwanted background signals, and therefore improve both the identification of trace-level components and the quality of the mass spectra. Following this, the 1 most abundant peaks were searched against a commercial library (NIST 11) using a TargetView all-component search. A lower limit of 7 was placed on the match factor in order to ensure that only high-quality matches were reported. The outcome of this was a list of 76 major compounds identified in the sample, including key olfactory components such as esters and terpenoids (see Table A1 in the Appendix).

3 Page Ethanol 3 Acetone 4 Methyl acetate 5 Acetic acid 9 Butan-1-ol 15 Methyl butanoate 19 Ethyl butanoate 22 1-Methylethyl butanoate 35 Methyl hexanoate 39 Butyl butanoate 4 Ethyl hexanoate 41 Hex-3-en-1-ol acetate 42 Hexyl acetate 43 Hex-2-en-1-ol acetate 5 3,7-Dimethylocta-1,6-dien-3-ol 59 Octyl acetate 62 Octyl butanoate 66 Decalactone 71 Nerolidol 76 1,2,3,6,7,8,9,1,11,12- Decahydrobenzo[e]pyrene Time (min) Figure 2: Analysis of the headspace profile of a whole strawberry, sampled onto a sorbent tube using the Micro-Chamber/Thermal Extractor, and analysed by GC and BenchTOF. The 2 most abundant compounds are labelled (the numbers correlate to those in Table A1 in the Appendix). Detection of sulfur compounds Low-level sulfur compounds in the aroma profile of strawberries and other foods are known or suspected to be strongly linked to customer perception of the quality and flavour of the foodstuff 1. However, previous studies into their sensory role have been hampered by difficulties in detecting and identifying these compounds at very low levels, particularly in complex data sets, where they can be hidden under baseline features or more abundant components. To see if any sulfur compounds were present in these samples, a search of the chromatogram in Figure 2 was conducted using a target library containing 26 sulfurcontaining compounds. To ensure only the most confident matches were reported, a stricter match coefficient of.8 was applied (corresponding to a match factor of 8 in the NIST search). The results of this search are shown in Table 1. This search demonstrated the presence of seven sulfur species from the library, including dimethyl disulfide and ethyl (methylthio)acetate, as shown in Figure 3. Cross-checking the spectra of these two trace-level components against those in NIST using TargetView s Search NIST option confirmed their identity, with very good forward match coefficients of 92 and 812 respectively. This also demonstrated the quality of the spectra produced by BenchTOF instruments. Target compound Retention time (min) Match coefficient Peak sum (TIC) Sulfur dioxide Carbon disulfide Methyl thioacetate Dimethyl disulfide Dimethyl sulfone S-Methyl butanethioate Ethyl (methylthio)acetate Table 1: Results obtained using TargetView for a sample processed against a library containing sulfur compounds. Note also the difference in peak sum for methyl thioacetate and dimethyl sulfone, indicating a dynamic range of over three orders of magnitude. Adoption of GC TOF MS technology, with its inherent advantages of sensitivity and speed, was hampered historically by the fact that many early systems produced distorted spectra that could not be used to search standard libraries. The fact that BenchTOF instruments produce reference-quality spectra allows users to take full advantage of commercial libraries such as NIST and Wiley.

4 Page 4 A Retention time (min) B Dimethyl disulfide Ethyl (methylthio)acetate Retention time (min) Retention time (min) C Dimethyl disulfide Forward match Reverse match Probability % Ethyl (methylthio)acetate Forward match Reverse match Probability % S S S O O Figure 3: (A, B) Detection of the deconvolved peaks for dimethyl disulfide and ethyl (methylthio)acetate (red traces) alongside co-eluting peaks (grey traces). (C) The corresponding mass spectra (top, red) compared to those in the NIST library (bottom, blue). Optimising system sensitivity It is well-established that dynamic headspace enrichment followed by TD pre-concentration offers considerable sensitivity advantages for the analysis of VOC profiles from bulk samples 2. With this confirmed for the case of strawberry headspace, attention turned to the issue of detector sensitivity. Quadrupole mass spectrometers offer a robust MS option for GC detection, and are widely used in many routine and research laboratory environments. However, they collect full spectral data by repeatedly scanning across the mass range, thus limiting system sensitivity. Detection limits can be greatly enhanced by moving to SIM mode, but the lack of spectra then compromises qualitative analysis, particularly of unknowns. In-depth analysis of trace compounds in complex samples may therefore be impossible (or at least require multiple runs) in order to obtain sufficient information about the analytes of interest. TOF MS technology monitors all ions without scanning, and thus generates full spectral information at lower mass/concentration levels. This is particularly true for BenchTOF instruments, which employ direct ion extraction in the source, rather than the less efficient orthogonal extraction used in most conventional TOF instruments for GC. Parallel analyses of the strawberry headspace samples were run using a TD GC quadrupole MS system and a TD GC BenchTOF system to compare the differences. Figure 4 shows the two chromatograms at the same scale, illustrating the sensitivity difference between the two systems, while Figure 5 shows the quadrupole results scaled by a factor

5 Page 5 of 1 for ease of comparison. Although different strawberries were used for the two analyses, the VOC profiles show a high degree of similarity. Clearly, these results demonstrate the sensitivity enhancement that can be achieved using a BenchTOF instrument rather than a single-quadrupole MS for the collection of full spectral information. This makes BenchTOF instruments suitable for the identification of trace compounds, both targets and unknowns, even in the complex chromatographic data generated by foodstuffs such as strawberries. The collection of full spectral information at these low detection levels would also enable users to re-examine stored data for new target species (such as allergens, toxins and olfactory components) should the need arise Quadrupole TOF Time (min) Figure 4: Comparison of the TIC chromatograms obtained using quadrupole and TOF MS detection for the TD GC analysis of large volumes of headspace from whole strawberries collected on sorbent tubes. Analytical conditions were the same in both cases, and the two data sets are displayed on the same scale Quadrupole ( 1) TOF Time (min) Figure 5: TD GC MS (quadrupole and TOF) data for dynamic strawberry headspace samples as shown in Figure 4, but with the quadrupole data scaled by a factor of 1.

6 Page 6 Conclusions In this Application Note, we have shown the ease with which flavour compounds can be profiled and trace-level components can be detected when dynamic headspace extraction and thermal desorption pre-concentration are combined with the inherent sensitivity of BenchTOF instruments. Moreover, we have demonstrated that the 1, spectra per second acquired by BenchTOF, and the reference-quality spectra produced, provide TargetView with the data needed to reliably deconvolve target peaks from baseline interferences and other compounds, and thus enable confident identification. The whole system, therefore, provides high sensitivity (and wide dynamic range) at the same time as allowing both target and unknown compounds to be detected in this complex matrix a task that would otherwise be time-consuming and require considerable skill and experience on the part of the analyst. It is also worth pointing out that the superior sensitivity delivered by BenchTOF instruments would also allow the gas flow from the GC to be split without compromising compound identification. This capability is valuable in food aroma analysis, because it allows the sample to be re-collected for repeat analysis using different GC parameters (e.g. for quantitative analysis of the major constituents), or analysed in parallel using a different technique such as olfactometry, for identification of aroma contributions from individual chemicals. References 1. X. Du, V. Whitaker and R. Rouseff, Changes in strawberry volatile sulfur compounds due to genotype, fruit maturity and sample preparation, Flavour and Fragrance Journal, 212, 27: ; X. Du, M. Song and R. Rouseff, Identification of new strawberry sulfur volatiles and changes during maturation, Journal of Agricultural and Food Chemistry, 211, 59: For examples, see Application Notes 88 (fruit juices and wine), 96 (tobacco) and 11 (cheese). Trademarks BenchTOF, Micro-Chamber/Thermal Extractor, SulfiCarb, TargetView and TD-1 are trademarks of Markes International. Tenax is a registered trademark of Buchem B.V., The Netherlands. Applications were performed under the stated analytical conditions. Operation under different conditions, or with incompatible sample matrices, may impact the performance shown.

7 Page 7 Appendix No. Compound name Retention time (min) Match factor Peak sum (TIC) 1 Isobutene Ethanol Acetone Methyl acetate Acetic acid Hexane Ethyl acetate Methyl propanoate Butan-1-ol Benzene Pentan-2-one Methyl thioacetate Ethyl propanoate n-propyl acetate Methyl butanoate Methylbutan-1-ol Dimethyl disulfide Benzyl methyl ketone Ethyl butanoate Methyl pentanoate Methyl 2-hydroxybutanoate Isopropyl butanoate Ethyl 2-methylbutanoic acid 24 Ethyl 3-methylbutanoate Hex-3-en-1-ol Hex-2-en-1-ol Hexan-1-ol Methylbutyl acetate Methylbutyl acetate Methylhexan-2-one Propyl butanoate Ethyl pentanoate Styrene Pentyl acetate Methyl hexanoate Methylpropyl butanoate Benzaldehyde Phenol Butyl butanoate No. Compound name Retention time (min) Match factor Peak sum (TIC) 4 Ethyl hexanoate Hex-3-enyl acetate Hexyl acetate Hex-2-enyl acetate Ethylhexan-1-ol Isopropyl hexanoate Methylbutyl butanoate Furaneol Dihydromyrcenol Acetophenone Linalool Nonanal Methyl octanoate Ethylhexyl acetate Benzyl acetate Hex-3-enyl butanoate Butyl hexanoate Ethyl octanoate Dodecane Octyl acetate Tridecane Nonyl acetate Octyl butanoate Tetradecane Biphenyl β-farnesene Decalactone α-farnesene β-bisabolene Butylated hydroxy toluene α-muurolene Nerolidol Octyl hexanoate Hexadecane Dodecalactone Isobutyl 2,2,4-trimethyl-3- carboxyisopropylpentanoate 1,2,3,6,7,8,9,1,11,12- Decahydrobenzo[e]pyrene Table A1: Major component list of whole strawberry emission profile. a Concentrations determined in terms of toluene equivalents by comparison with the peak area of a toluene standard analysed under the same conditions. AN515_3_18714