Evidence map›Paper›PMID 38202371›Full record

ArticlePlants (Basel, Switzerland)2023

Effect of Shading on Physiological Attributes and Proteomic Analysis of Tea during Low Temperatures.

Shah Zaman, Jiazhi Shen, Shuangshuang Wang, Dapeng Song, Hui Wang, Shibo Ding, Xu Pang, Mengqi Wang, Yu Wang, Zhaotang Ding

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Shah ZamanTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan 250100, China.ORCID 0000-0002-7698-040X
Jiazhi ShenTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan 250100, China.
Shuangshuang WangTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan 250100, China.ORCID 0000-0001-9726-6742
Dapeng SongRizhao Tea Research Institute, Rizhao 276800, China.
Hui WangRizhao Tea Research Institute, Rizhao 276800, China.
Shibo DingRizhao Tea Research Institute, Rizhao 276800, China.
Xu PangRizhao Tea Research Institute, Rizhao 276800, China.
Mengqi WangRizhao Tea Research Institute, Rizhao 276800, China.
Yu WangTea Research Institute, Qingdao Agricultural University, Qingdao 266109, China.
Zhaotang DingTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan 250100, China.
Tea Research Institute · CNShandong Academy of Agricultural Sciences · CNQingdao Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shading is an important technique to protect tea plantations under abiotic stresses. In this study, we analyzed the effect of shading (SD60% shade vs. SD0% no-shade) on the physiological attributes and proteomic analysis of tea leaves in November and December during low temperatures. The results revealed that shading protected the tea plants, including their soil plant analysis development (SPAD), photochemical efficiency (Fv/Fm), and nitrogen content (N), in November and December. The proteomics analysis of tea leaves was determined using tandem mass tags (TMT) technology and a total of 7263 proteins were accumulated. Further, statistical analysis and the fold change of significant proteins (FC < 0.67 and FC > 1.5

Indexed as

low temperaturephysiological attributesproteomicsshadetea

Identifiers

PMID38202371
PMCPMC10780538
OpenAlexW4390176426

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.