Coffee cherries contain a crucial flavor-precursor and chemical substances influencing roasted bean quality, yet limited knowledge exists on metabolite changes during cherry ripening. Our study identified 1078 metabolites, revealing 46 core differential metabolites using a KEGG pathway analysis. At the GF vs. ROF stage, amino acid synthesis dominated; ROF vs. BRF featured nucleotide catabolism; BRF vs. PRF exhibited glycoside and flavonoid synthesis; and PRF vs. PBF involved secondary metabolite synthesis and catabolism. The PRF stage emerged as the optimal cherry-harvesting period. A correlation analysis identified core differential metabolites strongly linked to taste indicators, suggesting their potential as taste markers. Notably, nucleotides and derivatives exhibited significant negative correlations with glycosides and flavonoids during ripening. This research systematically analyzed flavor and active substances in green coffee beans during cherry ripening, offering valuable insights into substance formation in Coffea arabica L.

Coffea arabica L. (C. arabica) is an economically important agricultural crop and the most popular beverage worldwide. To analyze genetic diversity and provide genetic resources for the selection and breeding of superior varieties of C. arabica, 61 cultivated Arabica coffee accessions were analyzed in the study, including 12 resequencing accessions from previous research and 49 accessions that were resequenced in this study. Single nucleotide polymorphisms (SNPs) and insertion–deletions (InDels) were statistically analyzed. Based on SNP variations, a genetic structure analysis, phylogenetic tree construction, and principal component analysis were performed for the 61 coffee accessions. The results showed that a total of 805.46 Gb of raw whole-genome resequencing data was obtained from the 61 coffee accessions, with 781.29 Gb of high-quality sequencing data after filtering. In total, 7,013,820 SNP sites and 1,074,329 InDel sites were detected. The average sequencing depth ranged from 6.69× to 19.35×, and the coverage ranged from 85.49% to 96.43%. The population genetic structure and phylogenetic analysis of the 61 coffee accessions revealed four lineages, suggesting that they had at least four ancestral genetic components. Catimor exhibited the highest genetic diversity, while Geisha had the lowest genetic diversity. The selective sweep analysis indicated that among the selected genes in Catimor, disease-resistance genes were significantly more numerous than in other coffee varieties. The genome resequencing data and genetic markers identified from the 61 cultivated Arabica coffee materials provided insights into the genetic variation in Arabica coffee germplasm and facilitated extensive genetic research.

This study combined HS-SPME-GC–MS and high-throughput sequencing to explore how honey-processing methods with varying mucilage retentions impact volatile compounds and microbial communities in green coffee beans. HS-SPME-GC–MS revealed that the RH group (75 % to 80 % mucilage retention) had the highest relative content of volatile compounds. According to rOAV >1, 13 key aroma compounds were identified, contributing to flavors like “mellow” and “fruity”. High-throughput sequencing identified seven dominant bacterial genera and four dominant fungal genera, with higher diversity of fungi than bacteria across treatments. Correlation analysis indicated that bacteria and fungi contribute to aroma formation, with bacteria more active in low-mucilage and fungi in high-mucilage treatments. Overall, the RH group was optimal for the aroma quality and bioactivity of green coffee beans. The findings of this research offers insights into aroma compound-microbe interactions in coffee mucilage fermentation, helping coffee producers optimize process parameters for better-quality coffee products.

To date, genomic and transcriptomic data on Coffea arabica L. in public databases are very limited, and there has been no comprehensive integrated investigation conducted on alternative splicing (AS). Previously, we have constructed and sequenced eighteen RNA-seq libraries of C. arabica at different ripening stages of fruit development. From this dataset, a total of 3824, 2445, 2564, 2990, and 3162 DSGs were identified in a comparison of different fruit ripening stages. The largest proportion of DSGs, approximately 65%, were of the skipped exon (SE) type. Biologically, 9 and 29 differentially expressed DSGs in the spliceosome pathway and carbon metabolism pathway, respectively, were identified. These DSGs exhibited significant variations, primarily in S1 vs. S2 and S5 vs. S6, and they involve many aspects of organ development, hormone transduction, and the synthesis of flavor components. Through the examination of research findings regarding the biological functions and biochemical pathways associated with DSGs and DEGs, it was observed that six DSGs significantly enriched in ABC transporters, namely, LOC113712394, LOC113726618, LOC113739972, LOC113725240, LOC113730214, and LOC113707447, were continually down-regulated at the fruit ripening stage. In contrast, a total of four genes, which were LOC113732777, LOC113727880, LOC113690566, and LOC113711936, including those enriched in the cysteine and methionine metabolism, were continually up-regulated. Collectively, our findings may contribute to the exploration of alternative splicing mechanisms for focused investigations of potential genes associated with the ripening of fruits in C. arabica.

To investigate the effects of different processing methods (WP, wet processing; DP, dry processing; AFWP, anaerobic fermentation wet processing; AFDP, anaerobic fermentation dry processing) on flavor precursors in green coffee beans and clarify the correlation with sensory flavor, this study employed a systematic analysis combining UPLC-ESI-MS/MS-based widely targeted metabolomics with sensory evaluation of brewed coffee. Multivariate statistical analysis indicates significant differences in the metabolic profiles of non-volatile compounds among different processing methods. Results showed that 843 differential metabolites, including amino acid derivatives, lipids, phenolic acids, and organic acids, were screened among 1,682 non-volatile compounds. Anaerobic fermentation has been shown to significantly increase the relative abundance of metabolites, particularly in AFDP, where they are primarily concentrated in pathways related to amino acid and nucleotide metabolism. KEGG analysis was employed to identify 125 characteristic metabolites across 45 differentially expressed pathways, which were then grouped into four clusters. Sensory analysis of brewed coffee revealed that anaerobically fermented coffee outperformed conventionally processed coffee in dry/wet aroma, flavor, aftertaste, acidity, body, and balance. Wet-processed coffee exhibited higher cleanliness and lower sweetness compared to dry-processed coffee. Through correlation analysis, 75 metabolites, including D-mannose, D-glucose, D-erythrose-4-phosphate, sinapic acid, L-lactic acid, γ-aminobutyric acid, caffeic acid, and esculetin, were identified as significantly correlated with sensory indicators and can be regarded as important flavor precursors in green coffee beans. The present results provide a valuable theoretical basis for understanding the flavor precursors and flavor characteristics of Arabica coffee processed using different processing methods.