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Effects of pruning on mineral nutrients and untargeted metabolites in fresh leaves of Camellia sinensis cv. Shuixian
Pruning is an important strategy for increasing tea production. However, the effects of pruning on tea quality are not well understood. In this study, tea leaves were collected from Wuyi Mountain for both ionomic and metabolomic analyses. A total of 1962 and 1188 fresh tea leaves were respectively c...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606708/ https://www.ncbi.nlm.nih.gov/pubmed/36311102 http://dx.doi.org/10.3389/fpls.2022.1016511 |
Sumario: | Pruning is an important strategy for increasing tea production. However, the effects of pruning on tea quality are not well understood. In this study, tea leaves were collected from Wuyi Mountain for both ionomic and metabolomic analyses. A total of 1962 and 1188 fresh tea leaves were respectively collected from pruned and unpruned tea plants sampled across 350 tea plantations. Ionomic profiles of fresh tea leaves varied significantly between pruned and unpruned sources. For tea plants, pruning was tied to decreases in the concentrations of mobile elements, such as nitrogen (N), phosphorus (P), potassium (K) and magnesium (Mg), and dramatic increases in the concentrations of the immobile ions calcium (Ca), aluminum (Al), manganese (Mn), boron (B) and cobalt (Co). Clustering and heatmap analysis showed that pruning also affected tea leaf metabolism. Among 85 metabolites that were significantly impacted by pruning, 30 were identified through random forest analysis as characteristic differential metabolites with a prediction rate of 86.21%. Redundancy analysis showed that pruning effects on mineral nutrient concentrations accounted for 25.54% of the variation in characteristic metabolites between treatments, with the highest contributions of 6.64% and 3.69% coming from Ca and Mg, respectively. In correlation network analysis, Ca and Mg both exhibited close, though opposing correlations with six key metabolites, including key quality indicators 1,3-dicaffeoylquinic acid and 2-O-caffeoyl arbutin. In summary, large scale sampling over hundreds of tea plantations demonstrated that pruning affects tea quality, mainly through influences on leaf mineral composition, with Ca and Mg playing large roles. These results may provide a solid scientific basis for improved management of high-quality tea plantations. |
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