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Record W4223589715 · doi:10.3390/plants11070996

Less Virulent Leptosphaeria biglobosa Immunizes the Canola Plant to Resist Highly Virulent L. maculans, the Blackleg Pathogen

2022· article· en· W4223589715 on OpenAlexafffund
Kaluhannadige Rasanie Eranka Padmathilake, W. G. Dilantha Fernando

Bibliographic record

VenuePlants · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Manitoba
FundersUniversity of HertfordshireUniversity of Manitoba
KeywordsLeptosphaeria maculansBlacklegCanolaVirulenceBiologyPathogenInoculationBrassicaMicrobiologyBotanyGeneHorticultureGenetics

Abstract

fetched live from OpenAlex

Leptosphaeria biglobosa is a less virulent Leptosphaeria spp. that causes blackleg disease in canola. Previous studies from our lab have shown that inoculation with the less virulent L. biglobosa can boost the resistance of canola plants against the highly virulent L. maculans. The objective of this study was to confirm the effectiveness of L. biglobosa as a biocontrol agent against L. maculans utilizing morphology, fluorescence microscopy, gene quantification, and transcriptomic analysis. The in planta development of two Leptosphaeria species inoculated at different time points was assessed using fluorescent protein-tagged isolates which are GFP-tagged L. maculans and DsRed-tagged L. biglobosa. The growth inhibition of L. maculans by pre-and co-inoculated L. biglobosa was supported by no lesion development on cotyledons and no or weak fluorescence protein-tagged mycelia under the confocal microscope. The host defense-related genes, WRKY33, PR1, APX6, and CHI, were upregulated in L. biglobosa inoculated Westar cotyledons compared to L. maculans inoculated cotyledons. The quantification of each pathogen through qPCR assay and gene expressions analysis on host defense-related genes by RT-qPCR confirmed the potential of L. biglobosa “brassicae’ in the management of the blackleg disease pathogen, L. maculans ‘brassicae’, in canola.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.999

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.025
GPT teacher head0.215
Teacher spread0.191 · 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.

Study designNot applicable
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

Citations8
Published2022
Admission routes2
Has abstractyes

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