Evidence map›Paper›PMID 37750694›Full record

ArticleMicrobiology spectrum2023

Effects of pruning on tea tree growth, tea quality, and rhizosphere soil microbial community.

Qi Zhang, Ying Zhang, Yuhua Wang, Shaoxiong Lin, Meihui Chen, Pengyuan Cheng, Jianghua Ye, Pengyao Miao, Xiaoli Jia, Haibin Wang

Open access · goldAbstract read
In one paragraph

Article in Microbiology spectrum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
5.9field-weighted citation impact, top 3% of its field
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

14 citing papers in PubMed, 23 citations in OpenAlex.

  1. Three new species (MycoKeys · 2026
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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

10 authors at 3 institutions in 1 country.

Qi Zhang *College of Tea and Food, Wuyi University , Wuyishan, China.ORCID 0000-0001-9047-4899
Ying Zhang *College of Tea and Food, Wuyi University , Wuyishan, China.
Yuhua WangCollege of Life Science, Fujian Agriculture and Forestry University , Fuzhou, China.
Shaoxiong LinCollege of Life Science, Longyan University , Longyan, China.
Meihui ChenCollege of Tea and Food, Wuyi University , Wuyishan, China.
Pengyuan ChengCollege of Life Science, Longyan University , Longyan, China.
Jianghua YeCollege of Tea and Food, Wuyi University , Wuyishan, China.
Pengyao MiaoCollege of Tea and Food, Wuyi University , Wuyishan, China.
Xiaoli JiaCollege of Tea and Food, Wuyi University , Wuyishan, China.ORCID 0000-0001-5076-0604
Haibin WangCollege of Tea and Food, Wuyi University , Wuyishan, China.ORCID 0000-0002-2792-0216
Wuyi University · CNLongyan University · CNFujian Agriculture and Forestry University · CN

Funding

Natural Science Foundation of Fujian Province (Fujian Provincial Natural Science Foundation) 2020J01369Natural Science Foundation of Fujian Province (Fujian Provincial Natural Science Foundation) 2020J01408Natural Science Foundation of Fujian Province (Fujian Provincial Natural Science Foundation) 2021J011137
6 · The paper itself

Abstract

importancePruning is an important agronomic measure in tea cultivation and management. We found that pruning was beneficial to increase tea yield, but it would reduce tea quality, especially the content of polyphenols, theanine, flavonoids, and free amino acids in tea leaves was reduced. The reason for this phenomenon was that pruning promotes the enrichment of special functional microorganisms and the enhancement of special metabolic pathways in the soil, leading to changes in the nutrient cycle in the soil.

Indexed as

metabolic pathwaymicroorganismqualitysoil enzymesoil physicochemical indextea treeyield

Identifiers

PMID37750694
PMCPMC10655597
OpenAlexW4387033403

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.