Widely Targeted Metabolomics Analysis Reveals the Differences of Nonvolatile Compounds in Oolong Tea in Different Production Areas

Abstract

The flavor differences in Oolong tea from different producing areas are caused by its complex differential compounds. In this study, representative samples of Oolong tea from four countries were collected, and their differential nonvolatile compounds were analyzed by a combination of widely targeted metabolomics, chemometrics, and quantitative taste evaluation. A total of 801 nonvolatile compounds were detected, which could be divided into 16 categories. We found that the difference in these compounds’ content among Oolong teas from three producing areas in China was the largest. There were 370 differential compounds related to the producing areas of Oolong tea, which were mainly distributed in 67 Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways. In total, 81 differential nonvolatile compounds made important contributions to the taste differences in Oolong tea from different producing areas, among which the number of flavonoids was the largest. Finally, the characteristic compounds of Oolong tea in six producing areas were screened. This study comprehensively identifies the nonvolatile compounds of Oolong tea in different producing areas for the first time, which provides a basis for the analysis of flavor characteristics, quality directional control, and the identification and protection of geographical landmark agricultural products of Oolong tea from different producing areas.

Untargeted Metabolomics and Transcriptomics Reveal the Mechanism of Metabolite Differences in Spring Tender Shoots of Tea Plants of Different Ages

“…Here, we employed OPLS-DA, as it is an effective method for screening DEMs [ 10 ]. In order to screen the DEMs of tea plants of different ages from the two cultivars, OPLS-DA analysis was performed with all of the relevant metabolites as variables.…”

“…Cross-validation indicated that the interpretation degree of the two models was high, and there was no fitting phenomenon ( Figure S2 ). Their DEMs were screened according to the principles of VIP > 1.00 and p < 0.05 [ 10 ] ( Table S3 ). There were 92 DEMs shared between WL-7 and WL-40, among which 50 metabolites were upregulated and 42 metabolites were downregulated in WL-40 ( Figure 3 C).…”

“…According to the results of the DEMs of plants of different ages from the two cultivars, in contrast to the 7-year-old tea plants, the upregulated metabolites in the 40-year-old tea plants were more numerous than the downregulated metabolites, among which flavonoids and amino acids and their derivatives were predominant. These two kinds of metabolites are also considered to have a greater impact on the quality of tea [ 10 ]. Wang.…”

“…The XCMS package of R (v3.3.2) was used for peak identification, peak filtration, and peak alignment, and the data matrix including the mass-to-charge ratio ( m / z ), retention time, and peak area (intensity) was obtained. The metabolites were identified according to the accurate molecular weight, the MS/MS secondary fragment information, and information from the relevant literature regarding tea [ 10 , 35 ]. One-way analysis of variance (ANOVA) with the least significant difference (LSD) was performed using SPSS19.0.…”

“…Tea is made from the tender shoots of the tea plant [ 8 ]. Using different processing techniques, the same fresh leaves can be processed into six different types of tea, including green tea, black tea, Oolong tea, white tea, dark tea, and yellow tea [ 9 , 10 ]. As an important raw material for tea processing, the content and composition of the metabolites in the tender shoots are the decisive factors of tea quality [ 11 ].…”