Evidence map›Paper›PMID 36311102›Full record

ArticleFrontiers in plant science2022

Effects of pruning on mineral nutrients and untargeted metabolites in fresh leaves of

Yang Liu, Jing Tian, Bei Liu, Zuopin Zhuo, Chen Shi, Ruineng Xu, Maoxing Xu, Baoshun Liu, Jianghua Ye, Lili Sun and 1 more

Abstract read
In one paragraph

Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yang LiuRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Jing TianRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Bei LiuRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Zuopin ZhuoRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Chen ShiRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Ruineng XuRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Maoxing XuWuyi Mountain Tea Industry Research Institute, Wuyishan, China.
Baoshun LiuWuyi Mountain Tea Industry Research Institute, Wuyishan, China.
Jianghua YeWuyi Mountain Tea Industry Research Institute, Wuyishan, China.
Lili SunRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.
Hong LiaoRoot Biology Center, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

calciumfresh tea leafmagnesiummetabolitemineral nutrientpruning

Identifiers

PMID36311102
PMCPMC9606708

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.