Evidence map›Paper›PMID 38088968›Full record

ArticleFrontiers in microbiology2023

Bacterial dynamic of flue-cured tobacco leaf surface caused by change of environmental conditions.

Jie Ding, Kesu Wei, Xianchao Shang, Yuxue Sha, Liting Qin, Haozhen Li, Di Wang, Xiaohua Zhang, Shengjiang Wu, Delun Li and 2 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Complete genome sequence ofMicrobiology resource announcements · 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

12 authors.

Jie Ding *Agricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Kesu Wei *Guizhou Academy of Tobacco Science, Guiyang, China.
Xianchao ShangAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Yuxue ShaAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Liting QinAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Haozhen LiAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Di WangAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Xiaohua ZhangAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.
Shengjiang WuGuizhou Academy of Tobacco Science, Guiyang, China.
Delun LiGuizhou Academy of Tobacco Science, Guiyang, China.
Feng WangGuizhou Academy of Tobacco Science, Guiyang, China.
Long YangAgricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Taian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microorganisms present on the surface of tobacco leaves play a significant role in shaping the composition of the tobacco microbial ecosystem, which undergoes continuous changes throughout the curing process. In the present study, a total of four distinct tobacco curing periods were selected for sampling, namely the fresh, yellowing, leaf-drying, and stem-drying stages. The bacterial 16S rRNA gene sequences of the collected samples were subsequently analyzed to identify operational taxonomic units (OTUs). The findings indicated that the complete dataset of leaf microbial samples was clustered, resulting in the identification of 1,783 operational taxonomic units (OTUs). Furthermore, the analysis of diversity revealed a pattern of initially increasing and subsequently decreasing community diversity. Redundancy Analysis (RDA) and weighted gene correlation networks for analysis (WGCNA) were employed in conjunction with environmental factors to assign OTUs to 22 modules for functional analysis. Additionally, a classification model utilizing the random forest algorithm was utilized to identify seven marker microorganisms (

Indexed as

dynamic changeenvironmental conditionsflue-cured tobaccoleaf surfacemicrobiological

Identifiers

PMID38088968
PMCPMC10713716

What OpenQuestion holds

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Registered trials

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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.