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. 2023 Jun 26:19:100774.
doi: 10.1016/j.fochx.2023.100774. eCollection 2023 Oct 30.

Metabolites profiling reveals the dynamic changes of non-volatiles in Pu-erh during Ganpu tea processing

Affiliations

Metabolites profiling reveals the dynamic changes of non-volatiles in Pu-erh during Ganpu tea processing

Xinyi Deng et al. Food Chem X. .

Abstract

Ganpu is an unique tea product made by Pu-erh tea and citrus peel. In this study, the non-volatiles changes of Pu-erh during Ganpu tea processing were fully analyzed by UPLC-ESI-MS/MS. Total 276 significantly differential metabolites in Pu-erh during Ganpu processing were detected (P < 0.05, VIP > 1), and their change trend were clustered into 8 subclasses by K-means analysis. Metabolites of Pu-erh present at various processes were revealed. 72 differential metabolites (P < 0.05, VIP > 1 and fold change ≥2 or ≤0.5) between any two stages were identified and fixation was the key step with 61 differential metabolites. 39 flavonoids and 2 lignans and coumarins were significantly decreased after fixation, while 5 terpenoids, 3 amino acids, 1 organic acids, 2 nucleotides and derivatives and newly detected jasminoside A (Log2FC = 9.90), picrocrocin (Log2FC = 9.90) and nomilinic acid (Log2FC = 7.56) were significantly increased. The results provided valuable information about the effect of Ganpu processing on dynamic changes of non-volatiles in Pu-erh.

Keywords: Citrus peel; Fixation process; Non-volatiles changes; Pu-erh tea.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
(A) The process of Ganpu tea. (B) Total ion flow (TIC) diagram of QC samples detected by mass spectrometry. (C) Three-dimensional PCA plot of non-volatiles in Pu-erh tea samples. (D) OPLS-DA of metabolic profiles. (E) The category of detected metabolites in Pu-erh tea samples.
Fig. 2
Fig. 2
(A) The class of differential metabolites in Pu-erh during Ganpu tea processes. (B) Eight classes of differential metabolites in flavonoids. (C) K-means clustering analysis showing differential metabolites. (D) Heatmap of the relative content of the 21 flavonoids in subclass 3 and 4.
Fig. 3
Fig. 3
Heatmap of the relative content of the differential non-volatiles in Pu-erh during Ganpu tea processing. (A) Amino acids and their derivatives. (B) Saccharides. (C) Phenolic acids. (D) Organic acids. (E) Tannins.
Fig. 4
Fig. 4
(A) Hierarchical cluster analysis of the similarity among tea samples. (B) Venn diagram showing the overlapping relationship of differential metabolites of PE0_vs_PESQ, PESQ_vs_PE1 and PE1_vs_GP-P.
Fig. 5
Fig. 5
(A) A volcano plot showing the differential non-volatiles between PE0 and PESQ. (B) Heatmap of the relative content of the differential non-volatile metabolites in PE0 and PESQ. (C) A bar chart showing the top 20 significantly differential metabolites. (D) KEGG analysis of the annotated differential metabolites in metabolic pathway.
Fig. 6
Fig. 6
(A) A volcano plot showing the differential non-volatile metabolites between PESQ and PE1. (B) Chord diagram showing the differential metabolites of PESQ_vs_PE1. (C) A volcano plot showing the differential non-volatile metabolites between PE1 and GP-P. (D) Chord diagram showing the differential metabolites of PE1_vs_GP-P. Different colors in the figure represent different classes of metabolites; the line represents the Pearson correlation coefficient between the corresponding differential metabolites, the red line represents positive correlation, and the blue line represents negative correlation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Supplementary Fig. S1
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