Evidence map›Paper›PMID 41742961›Full record

ArticleFrontiers in plant science2025

Wound-dependent infection by

Ahmad Yusuf Abubakar, Shujie Chen, Qianqi Lu, Sheidu Abdullaziz, Muhammed Mustapha Ibrahim, Hua Zhang, Pinghua Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in plant science, 2025. 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

7 authors.

Ahmad Yusuf Abubakar *Quality Inspection and Testing Center of Sugarcane and Derived Products, Ministry of Agriculture, National Engineering Research Center of Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China.
Shujie Chen *Quality Inspection and Testing Center of Sugarcane and Derived Products, Ministry of Agriculture, National Engineering Research Center of Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China.
Qianqi LuQuality Inspection and Testing Center of Sugarcane and Derived Products, Ministry of Agriculture, National Engineering Research Center of Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China.
Sheidu AbdullazizFujian Agriculture and Forestry University, Fuzhou, China.
Muhammed Mustapha IbrahimFujian Agriculture and Forestry University, Fuzhou, China.
Hua ZhangQuality Inspection and Testing Center of Sugarcane and Derived Products, Ministry of Agriculture, National Engineering Research Center of Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China.
Pinghua ChenQuality Inspection and Testing Center of Sugarcane and Derived Products, Ministry of Agriculture, National Engineering Research Center of Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Methods: We isolated the causal fungus from symptomatic sugarcane leaves and identified it using morphology and ITS phylogeny. Pathogenicity was tested on cultivar ROC22 using wounded and unwounded inoculations (mycelial plugs and spore suspensions). We assessed fungal growth across temperatures and pH, quantified host chlorophyll and defense-related responses (POD, SOD, PAL, and MDA), and evaluated sensitivity to commonly used fungicides using growth-inhibition assays. Results: The isolate (MF1) clustered with Discussion: These results indicate

Indexed as

bioenergy productioncrop cultivationfungal pathogenfungicide sensitivityNigrospora oryzaesugarcanewound infection

Identifiers

PMID41742961
PMCPMC12929479

What OpenQuestion holds

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LicenceCC BY
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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.