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Record W4318831521 · doi:10.3389/fpls.2022.1101039

Effect of azoxystrobin on tobacco leaf microbial composition and diversity

2023· article· en· W4318831521 on OpenAlexaff
Meili Sun, Hancheng Wang, Caihua Shi, Jianjun Li, Liuti Cai, Ligang Xiang, Tingting Liu, Paul H. Goodwin, Xingjiang Chen, Ling Wang

Bibliographic record

VenueFrontiers in Plant Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Guelph
FundersChina National Tobacco CorporationNational Natural Science Foundation of China
KeywordsAzoxystrobinDiversity (politics)Composition (language)BiologyBotanyFungicide

Abstract

fetched live from OpenAlex

Azoxystrobin, a quinone outside inhibitor fungicide, reduced tobacco target spot caused by Rhizoctonia solani by 62%, but also affected the composition and diversity of other microbes on the surface and interior of treated tobacco leaves. High-throughput sequencing showed that the dominant bacteria prior to azoxystrobin treatment were Methylobacterium on healthy leaves and Pseudomonas on diseased leaves, and the dominant fungi were Thanatephorous (teleomorph of Rhizoctonia) and Symmetrospora on healthy leaves and Thanatephorous on diseased leaves. Both bacterial and fungal diversity significantly increased 1 to 18 days post treatment (dpt) with azoxystrobin for healthy and diseased leaves. For bacteria on healthy leaves, the relative abundance of Pseudomonas, Sphingomonas, Unidentified-Rhizobiaceae and Massilia declined, while Methylobacterium and Aureimonas increased. On diseased leaves, the relative abundance of Sphingomonas and Unidentified-Rhizobiaceae declined, while Methylobacterium, Pseudomonas and Pantoea increased. For fungi on healthy leaves, the relative abundance of Thanatephorous declined, while Symmetrospora, Sampaiozyma, Plectosphaerella, Cladosporium and Cercospora increased. On diseased leaves, the relative abundance of Thanatephorous declined, while Symmetrospora, Sampaiozyma, Plectosphaerella, Cladosporium, Phoma, Pantospora and Fusarium, increased. Compared to healthy leaves, azoxystrobin treatment of diseased leaves resulted in greater reductions in Thanatephorous, Sphingomonas and Unidentified-Rhizobiaceae, a greater increase in Methylobacterium, and similar changes in Phoma, Fusarium, Plectosphaerella and Cladosporium. Azoxystrobin had a semi-selective effect altering the microbial diversity of the tobacco leaf microbiome, which could be due to factors, such as differences among bacterial and fungal species in sensitivity to quinone outside inhibitors, ability to use nutrients and niches as certain microbes are affected, and metabolic responses to azoxystrobin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.207
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2023
Admission routes1
Has abstractyes

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