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Screening, identification and evaluation of potential biocontrol fungal endophytes against Rhizoctonia solani AG3 on potato plants

2010· article· en· W1914742631 on OpenAlexafffund
Rachid Lahlali, Mohamed Hijri

Bibliographic record

VenueFEMS Microbiology Letters · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRhizoctonia solaniBiologyAlternaria solaniMyceliumBiological pest controlPathogenRhizoctoniaBotanyPhomopsisTrichodermaHorticultureBlightMicrobiology

Abstract

fetched live from OpenAlex

Rhizoctonia solani is an important soilborne pathogen of potato plants whose control typically depends on chemicals. Here, we screened six fungal endophytes for the suppression of R. solani growth both in vitro and in a greenhouse. These isolates were identified using morphology and internal transcribed spacer regions of rDNA as Alternaria longipes, Epicoccum nigrum, Phomopsis sp., and Trichoderma atroviride. Both T. atroviride and E. nigrum showed significant in vitro inhibition of mycelial growth of R. solani, with the greatest inhibition zone observed for E. nigrum species in dual cultures. The highest inhibition was observed for T. atroviride. The inhibition rate was also significantly correlated with the culture filtrates of these isolates. Confocal microscopy showed that T. atroviride acts as a mycoparasite and competitor. However, E. nigrum and A. longipes produce secondary metabolites, while Phomospsis sp. competes for nutrients and space. Greenhouse experiments confirmed that T. atroviride and E. nigrum improved potato yield significantly and decreased the stem disease severity index of sensitive potato.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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 designBench or experimental
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

Citations177
Published2010
Admission routes2
Has abstractyes

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