Evidence map›Paper›PMID 42708595›Full record

ArticleMicrobiology spectrum2026

Biocontrol of tobacco leaf mold using

Daiyuan Zhang, Mo Zhang, Ge Zhang, Dian Zou, Dong Li, Huijing Gu, Xuetuan Wei, Kuo Huang, Changwen Ye

Abstract read
In one paragraph

Article in Microbiology spectrum, 2026. 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
–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

0 citing papers in PubMed.

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

9 authors.

Daiyuan ZhangZhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, China.ORCID 0009-0002-6005-8944
Mo ZhangNational Key Laboratory of Agricultural Microbiology, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, China.
Ge ZhangZhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, China.
Dian ZouNational Key Laboratory of Agricultural Microbiology, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, China.
Dong LiZhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, China.
Huijing GuNational Key Laboratory of Agricultural Microbiology, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, China.
Xuetuan WeiNational Key Laboratory of Agricultural Microbiology, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, China.
Kuo HuangZhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, China.ORCID 0009-0003-9277-4694
Changwen YeZhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, China.ORCID 0009-0009-2328-0766

Funding

National Key Research and Development Program of China No. 2022YFF1000700The chief scientist innovation project of state tobacco monopoly administration/china national tobacco corporation No. 702024CK0380The major science and technology projects of china national tobacco corporation 110202201034(XJ-05)
6 · The paper itself

Abstract

Mold contamination causes economic losses and poses risks to human and animal health. Tobacco leaves, as a high-value agricultural product, are particularly susceptible to mold contamination during post-harvest handling. In this study, the antifungal performance of

Indexed as

BacillusFungiNicotianaPlant DiseasesPlant LeavesVolatile Organic CompoundsMicrobiotaPenicilliumPest Control, BiologicalVolatile Organic Compoundsantifungal effectBacillus velezensismicrobial diversitytobacco leavesvolatile compounds

Identifiers

PMID42708595
PMCPMC13689419

What OpenQuestion holds

Textmetadata
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.