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Record W2172410364 · doi:10.1094/phyto-08-14-0231-r

Maple Bark Biochar Affects <i>Rhizoctonia solani</i> Metabolism and Increases Damping-Off Severity

2015· article· en· W2172410364 on OpenAlexafffund
Tanya Copley, Konstantinos A. Aliferis, Suha Jabaji

Bibliographic record

VenuePhytopathology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsBiocharRhizoctonia solaniRhizoctoniaBiologyAmendmentDamping offBark (sound)MyceliumHorticultureBotanyAgronomyChemistrySeedlingEcology

Abstract

fetched live from OpenAlex

Many studies have investigated the effect of biochar on plant yield, nutrient uptake, and soil microbial populations; however, little work has been done on its effect on soilborne plant diseases. To determine the effect of maple bark biochar on Rhizoctonia damping-off, 11 plant species were grown in a soilless potting substrate amended with different concentrations of biochar and inoculated or not with Rhizoctonia solani anastomosis group 4. Additionally, the effect of biochar amendment on R. solani growth and metabolism in vitro was evaluated. Increasing concentrations of maple bark biochar increased Rhizoctonia damping-off of all 11 plant species. Using multivariate analyses, we observed positive correlations between biochar amendments, disease severity and incidence, abundance of culturable bacterial communities, and physicochemical parameters. Additionally, biochar amendment significantly increased R. solani growth and hyphal extension in vitro, and altered its primary metabolism, notably the mannitol and tricarboxylic acid cycles and the glycolysis pathway. One or several organic compounds present in the biochar, as identified by gas chromatography-mass spectrometry analysis, may be metabolized by R. solani. Taken together, these results indicate that future studies on biochar should focus on the effect of its use as an amendment on soilborne plant pathogens before applying it to soils.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.810
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.018
GPT teacher head0.220
Teacher spread0.202 · 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 teacher head, 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

Citations46
Published2015
Admission routes2
Has abstractyes

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