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.