Delineating the extra-virgin olive oil aroma blueprint by multiple headspace solid phase microextraction and differential-flow modulated comprehensive two-dimensional gas chromatography

Autor: Maria del Pilar Segura Borrego, M.L. Morales, Raquel Maria Callejón Fernadez, Federico Stilo, Daniela Peroni, James D. McCurry, Sonia Battaglino, Stephen E. Reichenbach, Chiara Cordero, Carlo Bicchi
Rok vydání: 2021
Předmět:
Analyte
Resolution (mass spectrometry)
010402 general chemistry
Mass spectrometry
Solid-phase microextraction
01 natural sciences
Biochemistry
Chemistry Techniques
Analytical

Gas Chromatography-Mass Spectrometry
Analytical Chemistry
law.invention
law
Artificial Intelligence
Flame ionization detector
Sample preparation
Extra-virgin olive oil volatiles
Olive Oil
Solid Phase Microextraction
predicted relative response factors
Flame Ionization
Aldehydes
Volatile Organic Compounds
comprehensive two-dimensional gas chromatography
Chromatography
quantitative analysis
Chemistry
010401 analytical chemistry
Organic Chemistry
Reproducibility of Results
General Medicine
Reference Standards
0104 chemical sciences
Linear range
Odorants
Gas chromatography
Extra-virgin olive oil volatiles
comprehensive two-dimensional gas chromatography
parallel detection MS/FID
predicted relative response factors
reverse-inject differential-flow modulation
quantitative analysis

reverse-inject differential-flow modulation
Food Analysis
parallel detection MS/FID
Zdroj: Journal of chromatography. A. 1650
ISSN: 1873-3778
Popis: Comprehensive two-dimensional gas chromatography with parallel mass spectrometry and flame ionization detection (GC × GC-MS/FID) enables effective chromatographic fingerprinting of complex samples by comprehensively mapping untargeted and targeted components. Moreover, the complementary characteristics of MS and FID open the possibility of performing multi-target quantitative profiling with great accuracy. If this synergy is applied to the complex volatile fraction of food, sample preparation is crucial and requires appropriate methodologies capable of providing true quantitative results. In this study, untargeted/targeted (UT) fingerprinting of extra-virgin olive oil volatile fractions is combined with accurate quantitative profiling by multiple headspace solid phase microextraction (MHS-SPME). External calibration on fifteen pre-selected analytes and FID predicted relative response factors (RRFs) enable the accurate quantification of forty-two analytes in total, including key-aroma compounds, potent odorants, and olive oil geographical markers. Results confirm good performances of comprehensive UT fingerprinting in developing classification models for geographical origin discrimination, while quantification by MHS-SPME provides accurate results and guarantees data referability and results transferability over years. Moreover, by this approach the extent of internal standardization procedure inaccuracy, largely adopted in food volatiles profiling, is measured. Internal standardization yielded an average relative error of 208 % for the fifteen calibrated compounds, with an overestimation of + 538% for (E)-2-hexenal, the most abundant yet informative volatile of olive oil, and a -89% and -80% for (E)-2-octenal and (E)-2-nonenal respectively, analytes with a lower HS distribution constant. Compared to existing methods based on 1D-GC, the current procedure offers better separation power and chromatographic resolution that greatly improve method specificity and selectivity and results in lower LODs and LOQs, high calibration performances (i.e., R2 and residual distribution), and wider linear range of responses. As an artificial intelligence smelling machine, the MHS-SPME-GC × GC-MS/FID method is here adopted to delineate extra-virgin olive oil aroma blueprints; an objective tool with great flexibility and reliability that can improve the quality and information power of each analytical run.
Databáze: OpenAIRE