Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOF MS) is a technique that provides highly informative fingerprinting for food characterization. However, 2D fingerprints consistency might be affected by variables correlated to both the analytical platform and the experimental parameters adopted for the analysis making challenging cross-comparative studies extended over long-time range. This study focuses on the combined untargeted and targeted (UT) fingerprinting of volatiles from extra-virgin olive (EVO) oils and proposes an effective work-flow to correct fluctuations that may occur during long-term studies and that affect patterns alignment and response consistency. Volatiles from high-quality EVO oils (Picual cultivar, from Granada Altipiano, Spain) are sampled by headspace solid phase micro extraction (HS-SPME) with a DVB/CAR/PDMS df 50/30 μm 2 cm length fiber and analyzed by GC×GC-TOF MS featuring tandem ionization on a polar × medium polarity column set-up. 2D-pattern misalignments are simulated by changing chromatographic settings (modulation period MP and 2D column dimensions) while MS response fluctuations are induced by adopting different tuning and acquisition modes. Misalignments, caused by chromatographic setup changes, impact on 1D and 2D retention times (1tR, 2tR) and peak-width while MS tuning and acquisition mode impact on analytes absolute and relative response. A strategy is then proposed to define a) a minimal signal-to-noise ratio (SNR) threshold, for consistent extraction of MS features to be adopted for UT fingerprinting, b) a minimal direct match factor (DMF) similarity value to improve the specificity of the matching, and c) a minimal distance threshold to guide the matching transform toward a 100% of true-positive matches. Once designed, the work-flow is applied to a target template of known analytes with a full supervision of the analyst. On the other hand, a fully automated and unsupervised procedure is then applied to automated for the UT feature template by adopting previously optimized parameters. For both targeted and UT templates, the percentage of matching between misaligned patterns reaches 95%. Finally, to compensate for detector response fluctuations, different normalization approaches are examined: normalization on total or partial response and normalization on multiple Internal Standards ISs. Although the first two approaches result attractive, being simpler and less time-consuming, results are not satisfactory as those obtained by multiple ISs normalization. The latter performs better for those analytes showing higher response fluctuations due to the pressure-drop applied. In conclusion, this study shows that, thanks to a careful optimization of “smart templates” parameters, a full metadata transfer for targeted and untargeted features can be achieved even when dramatic misalignment occurs on complex 2D-patterns.

Extending over long-term studies the untargeted and targeted fingerprinting of extra-virgin olive oil volatiles by comprehensive two-dimensional gas chromatography with mass spectrometry

Federico Stilo;Erica Liberto;Carlo Bicchi;Chiara Cordero
2019

Abstract

Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOF MS) is a technique that provides highly informative fingerprinting for food characterization. However, 2D fingerprints consistency might be affected by variables correlated to both the analytical platform and the experimental parameters adopted for the analysis making challenging cross-comparative studies extended over long-time range. This study focuses on the combined untargeted and targeted (UT) fingerprinting of volatiles from extra-virgin olive (EVO) oils and proposes an effective work-flow to correct fluctuations that may occur during long-term studies and that affect patterns alignment and response consistency. Volatiles from high-quality EVO oils (Picual cultivar, from Granada Altipiano, Spain) are sampled by headspace solid phase micro extraction (HS-SPME) with a DVB/CAR/PDMS df 50/30 μm 2 cm length fiber and analyzed by GC×GC-TOF MS featuring tandem ionization on a polar × medium polarity column set-up. 2D-pattern misalignments are simulated by changing chromatographic settings (modulation period MP and 2D column dimensions) while MS response fluctuations are induced by adopting different tuning and acquisition modes. Misalignments, caused by chromatographic setup changes, impact on 1D and 2D retention times (1tR, 2tR) and peak-width while MS tuning and acquisition mode impact on analytes absolute and relative response. A strategy is then proposed to define a) a minimal signal-to-noise ratio (SNR) threshold, for consistent extraction of MS features to be adopted for UT fingerprinting, b) a minimal direct match factor (DMF) similarity value to improve the specificity of the matching, and c) a minimal distance threshold to guide the matching transform toward a 100% of true-positive matches. Once designed, the work-flow is applied to a target template of known analytes with a full supervision of the analyst. On the other hand, a fully automated and unsupervised procedure is then applied to automated for the UT feature template by adopting previously optimized parameters. For both targeted and UT templates, the percentage of matching between misaligned patterns reaches 95%. Finally, to compensate for detector response fluctuations, different normalization approaches are examined: normalization on total or partial response and normalization on multiple Internal Standards ISs. Although the first two approaches result attractive, being simpler and less time-consuming, results are not satisfactory as those obtained by multiple ISs normalization. The latter performs better for those analytes showing higher response fluctuations due to the pressure-drop applied. In conclusion, this study shows that, thanks to a careful optimization of “smart templates” parameters, a full metadata transfer for targeted and untargeted features can be achieved even when dramatic misalignment occurs on complex 2D-patterns.
Recent Advances in Food Analysis
Prague, Czech Republic
5-8 Novembre 2019
BOOK OF ABSTRACTS 9th International Symposium on RECENT ADVANCES IN FOOD ANALYSIS
Jana Pulkrabová, Monika Tomaniová, Michel Nielen and Jana Hajšlová
217
217
978-80-7592-055-3
http://www.rafa2019.eu/pdf/RAFA2019_BoA_web.pdf
Federico Stilo, Erica Liberto, Stephen E. Reichenbach, Qingping Tao, Carlo Bicchi, Chiara Cordero
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1743910
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