MMSE-GC-MS volatile organic compound profiling of twelve defect categories in Robusta coffee beans: chemical markers
Februadi Bastian1, Trivena Patricia Bongga Pasilong1, Andi Dirpan2
1Department of Food Science and Technology, Faculty of Agricultural Technology, Hasanuddin University, Makassar 90245, Indonesia; Coffee Research Group, Hasanuddin University, Makassar 90245, Indonesia.
Abstract:
Defective coffee beans significantly compromise the flavor quality of Robusta coffee (Coffea canephora L.). This study presents a comprehensive volatile organic compound (VOC) profiling of twelve defect categories in Robusta green coffee beans from Bulukumba, Indonesia, using Monolithic Material Sorptive Extraction coupled with gas chromatography-mass spectrometry (MMSE-GC-MS). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) in independent triplicates were applied to discriminate volatile patterns across defect types, with validation on commercial-grade unsorted Robusta samples from three origins. A total of 42 volatile compounds were tentatively identified, spanning pyrazines, furans, aldehydes, alcohols, phenols, esters, acids, terpenes, and sulfur compounds. PCA explained 57.8% of total variance, with bean versus non-bean distinction as the primary axis of differentiation, HCA resolved three major clusters. Selected markers remained detectable in commercial-grade samples across origins. MMSE-GC-MS combined with multivariate analysis offers a sensitive, chemistry-informed framework for objective Robusta defect discrimination, complementing conventional visual inspection.
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