The characteristic secondary metabolites in tea (theanine, caffeine, and catechins) are important factors contributing to unique tea flavors. However, there has been relatively little research on molecular markers related to these metabolites. Thus, we conducted a genome-wide association analysis of the levels of these tea flavor-related metabolites in three seasons. The theanine, caffeine, and catechin levels in Population 1 comprising 191 tea plant germplasms were examined, which revealed that their heritability exceeded 0.5 in the analyzed seasons, with the following rank order (highest to lowest heritabilities): (+)-catechin > (−)-gallocatechin gallate > caffeine = (−)-epicatechin > (−)-epigallocatechin-3-gallate > theanine > (−)-epigallocatechin > (−)-epicatechin-3-gallate > catechin gallate > (+)-gallocatechin. The SNPs detected by amplified-fragment SNP and methylation sequencing divided Population 1 into three groups and seven subgroups. An association analysis yielded 307 SNP markers related to theanine, caffeine, and catechins that were common to all three seasons. Some of the markers were pleiotropic. The functional annotation of 180 key genes at the SNP loci revealed that FLS, UGT, MYB, and WD40 domain-containing proteins, as well as ATP-binding cassette transporters, may be important for catechin synthesis. KEGG and GO analyses indicated that these genes are associated with metabolic pathways and secondary metabolite biosynthesis. Moreover, in Population 2 (98 tea plant germplasm resources), 30 candidate SNPs were verified, including 17 SNPs that were significantly or extremely significantly associated with specific metabolite levels. These results will provide a foundation for future research on important flavor-related metabolites and may help accelerate the breeding of new tea varieties.

Volatile flavor compounds in 112 black teas from seven countries were analyzed by untargeted metabolomics using headspace solid-phase microextraction and gas chromatography-mass spectrometry (HS-SPME/GC-MS). Multivariate statistical analysis and odor activity values (OAVs) were used to classify these samples and identify key odorants. A total of 140 volatile flavor compounds (VFCs), including 12 different groups, were identified, and alcohols were prevalent in China and India samples, accounting for 40.83% and 34.96% of the total VFCs, respectively. Eight volatile compounds with OAVs > 1 were identified as key active differential odorants in Chinese, Indian, and Sri Lankan samples, including linalool, pentanoic acid, methyl salicylate, hexanoic acid, 1-methyl-naphthalene, phenylethyl alcohol, geraniol, and β-ionone. Linalool, pentanoic acid, and hexanoic acid in Indian black teas, phenylethyl alcohol in Chinese black teas, and 1-methyl-naphthalene, β-ionone in Sri Lankan black teas could be used to discriminate different black tea groups. A total of 12-14 VFCs with OAVs > 1 were identified as key active aromatics in Chinese black tea sample. Linalool and benzeneacetaldehyde in Yingde (Guangdong) black tea, methyl salicylate in Taiwanese samples, and benzeneacetic acid in Anhui black tea could be used as biomarkers to distinguish them from other Chinese samples. Sensory evaluation results showed that most black teas presented the common sweet, floral odors, which were consistent with GC-MS analysis. These results will contribute to characterize the odor metabolome of black teas and provide biochemical basis for identifying the authenticity of different black teas. K E Y W O R D Sblack tea, metabolomics, odor activity value, partial least-squares discriminant analysis, volatile flavor compound Practical Application: Linalool, pentanoic acid, and hexanoic acid in Indian black teas, phenylethyl alcohol in Chinese black teas, 1-methyl-naphthalene, β-ionone, and methyl salicylate in Sri Lankan black teas could be used to discriminate black teas from the three countries. Linalool and benzeneacetaldehyde in

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