Time-resolved volatile profiling and endpoint microbiome characterization in spontaneous Coffea arabica wet fermentation
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Abstract. Nova B, Wati L, Rizkyanto R, Wardi ES, Lubis P. 2026. Time-resolved volatile profiling and endpoint microbiome characterization in spontaneous Coffea arabica wet fermentation. Asian J Nat Prod Biochem 24 (1): f240105. https://doi.org/10.13057/biofar/f240105. Spontaneous fermentation during wet coffee processing involves complex microbial communities that influence Volatile Organic Compound (VOC) profiles and aroma characteristics. However, time-resolved descriptions of VOC dynamics alongside endpoint microbial community composition in spontaneous Coffea arabica wet fermentation remain limited. This study combined GC-MS volatilomics with amplicon-based community profiling to characterize chemical and microbial changes during a single 36-hour spontaneous fermentation batch. VOC profiles were measured by GC-MS at 0, 12, 24, and 36 h, while bacterial 16S rRNA and fungal ITS amplicon sequencing were performed only at 36 h to characterize the endpoint community. After contaminant curation, 32 unique volatile compounds were retained across timepoints. Temporal profiles indicated depletion of plant-derived compounds and appearance of fermentation-associated products. Eicosanoic acid decreased from 9.98% to 0.27% (Area%), and caryophyllene decreased from 6.24% to 1.07%. Linalool was detected only at 36 h (0.34%), whereas pentadecanal appeared at 12 h and persisted through 36 h. The 36-h bacterial community was dominated by Leuconostoc spp. (88.54% of reads; L. falkenbergense 47.3%, L. pseudomesenteroides 29.02%), while the fungal community was dominated by Hanseniaspora uvarum (73.0% of ITS reads). Microbiome characterization was performed only at the 36-h fermentation endpoint; no time-series microbiome sampling and no statistical association testing between microbial taxa and VOC data were conducted. Accordingly, all proposed microbe–metabolite relationships are derived solely from published literature and must be treated as hypothesis-generating rather than analytically validated findings. This work provides baseline data for future, time-series-replicated microbiome studies and controlled fermentation trials in coffee processing.
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