• Seven primary processing methods of coffee beans were investigated. • Traditional dry processing gave the strongest aftertaste, astringency, and umami. • A total of 1395 metabolites were identified by metabolomic analysis. • Anaerobic fermentation produced extracellular enzymes that convert phenolic acids. • Thirty-seven biomarker metabolites significantly correlated with taste quality.

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.

Background: Farmers harvest two batches fruits of Lemons (Citrus limon L. Burm. f.) i.e., spring flowering fruit and autumn flowering fruit in dry-hot valley in Yunnan, China. Regular lemons harvested in autumn have smooth skin. However, lemons harvested in spring have rough skin, which makes them less attractive to customers. Furthermore, the rough skin causes a reduction in commodity value and economical losses to farmers. This is a preliminary study that investigates the key transcriptomic and metabolomic differences in peels of lemon fruits (variety Yuning no. 1) harvested 30, 60, 90, 120, and 150 days after flowering from the same trees in different seasons.Results: We identified 5,792, 4,001, 3,148, and 5,287 differentially expressed genes (DEGs) between smooth peel (C) and rough peel (D) 60, 90, 120, and 150 days after flowering, respectively. A total of 1,193 metabolites differentially accumulated (DAM) between D and C. The DEGs and DAMs were enriched in the mitogen-activated protein kinase (MAPK) and plant hormone signaling, terpenoid biosynthesis, flavonoid, and phenylalanine biosynthesis, and ribosome pathways. Predominantly, in the early stages, phytohormonal regulation and signaling were the main driving force for changes in peel surface. Changes in the expression of genes associated with asymmetric cell division were also an important observation. The biosynthesis of terpenoids was possibly reduced in rough peels, while the exclusive expression of cell wall synthesis-related genes could be a possible reason for the thick peel of the rough-skinned lemons. Additionally, cell division, cell number, hypocotyl growth, accumulation of fatty acids, lignans and coumarins- related gene expression, and metabolite accumulation changes were major observations.Conclusion: The rough peels fruit (autumn flowering fruit) and smooth peels fruit (spring flowering fruit) matured on the same trees are possibly due to the differential regulation of asymmetric cell division, cell number regulation, and randomization of hypocotyl growth related genes and the accumulation of terpenoids, flavonoids, fatty acids, lignans, and coumarins. The preliminary results of this study are important for increasing the understanding of peel roughness in lemon and other citrus species.

Macadamia ternifolia is a dynamic oil-producing nut crop in the world. However, the nutshell is frequently considered as a low-quality material. Further, its metabolic profile is still uncharacterized. In order to explore the industrial significance of the nutshell, this study performed metabolic and transcriptomic analyses at various developmental stages of the nutshell. The qualitative and quantitative metabolic data analysis identified 596 metabolic substances including several species of phenolic acids, flavonoids, lipids, organic acids, amino acids and derivatives, nucleotides and derivatives, alkaloids, lignans, coumarins, terpenoids, tannins, and others. However, phenolic acids and flavonoids were predominant, and their abundance levels were significantly altered across various developmental stages of the nutshell. Comparative transcriptome analysis revealed that the expression patterns of phenolic acid and flavonoid pathway related genes were significantly changed during the nutshell growth. In particular, the expression of phenylalanine ammonia-lyase, C4H, 4CL, CHS, CHI, F3H, and FLS had dynamic differences at the various developmental stages of the nutshell. Our integrative metabolomic and transcriptomic analyses identified the key metabolic substances and their abundance levels. We further discussed the regulatory mechanism of phenolic and flavonoid biosynthesis in the nutshell of M. ternifolia. Our results provide new insights into the biological profiles of the nutshell of M. ternifolia and help to elucidate the molecular mechanisms of phenolic and flavonoid biosynthesis in the nutshell of M. ternifolia.

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.

Background: Codon usage bias has been analyzed in the Coffea arabica L. nuclear genome, yet comprehensive genomic resources for this species remain limited. The chloroplast genome, characterized by its maternal inheritance and high conservation, represents a valuable resource for investigating plant phylogeny, crop domestication, and maternal lineage evolution. Results: We assembled complete chloroplast genomes for 52 C. arabica accessions, encompassing four cultivars (Geisha, Catimor, Bourbon, and Caturra), four improved breeding lines within the Geisha group (Yunka No. 3, Yunka No. 4, G02, and G13), two Catimor breeding lines (CCCA25 and T5175), and four accessions of unknown cultivar origin. Comparative genomics, unrooted phylogenetic reconstruction (neighbor-joining and maximum likelihood), haplotype inference, and exploratory principal component analysis (PCA) were integrated to characterize the genetic architecture of these chloroplast genomes. These genomes ranged from 155,133 bp to 155,192 bp in length, displayed the typical quadripartite architecture, and exhibited GC contents of 37.43–37.44%. Gene annotation identified 131 genes, comprising 86 protein-coding genes, 37 tRNAs, and 8 rRNAs. Codon usage analysis revealed a pronounced bias toward A or U at the third codon position. We detected 194 SSR loci per plastome, among which mononucleotide A/T repeats predominated. Neighbor-joining and maximum-likelihood phylogenies, PCA, and haplotype network reconstruction consistently resolved the 52 accessions into three genetic clusters (C1–C3; C1 represented by a single divergent accession) and five distinct haplotypes. SNP and InDel profiling further showed that intergenic spacer (IGS) regions harbored the highest density of genetic variation. Conclusions: These genomes provide resources for germplasm characterization, phylogenetic studies, and marker-assisted breeding in coffee. They also establish a chloroplast-genome framework that, when integrated with nuclear genomics and expanded sampling, will help fully resolve the maternal history, domestication, and allopolyploid origin of Coffea arabica.