Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS

Matteo Bordiga, Vincenzo Disca, Marcello Manfredi, Elettra Barberis, Francesca Carrà, Luciano Navarini, Valentina Lonzarich, Marco Arlorio

Risultato della ricerca: Contributo su rivistaArticolo in rivistapeer review

Abstract

This study compared two nontargeted analytical techniques—headspace gas chromatography–ion mobility spectrometry (HS-GC-IMS) and comprehensive two-dimensional gas chromatography–mass spectrometry (GC × GC-MS)—to fingerprint the volatile organic compounds (VOCs) of green Coffea arabica beans from Ethiopia, Brazil, Nicaragua, and Guatemala. HS-GC-IMS enabled rapid differentiation of samples, detecting VOC signal regions that effectively clustered samples by origin with minimal preparation. GC × GC-MS offered higher chemical resolution, identifying 98 compounds, including methoxypyrazines, aldehydes, and alcohols, which significantly contributed to interorigin variability. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) confirmed the capacity of both methods to distinguish geographical origins, with hierarchical clustering highlighting region-specific VOC patterns. HS-GC-IMS proved efficient for high-throughput screening, while GC × GC-MS provided molecular insights into potential aroma precursors. Together, these platforms offer a complementary approach to green coffee authentication and quality control.

Lingua originaleInglese
Numero di articolo1302823
RivistaInternational Journal of Food Science
Volume2025
Numero di pubblicazione1
DOI
Stato di pubblicazionePubblicato - 2025

Fingerprint

Entra nei temi di ricerca di 'Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS'. Insieme formano una fingerprint unica.

Cita questo