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Record W2796613209 · doi:10.1111/ppa.12868

A molecular marker for the specific detection of new pathotype 5‐like strains of <i>Plasmodiophora brassicae</i> in canola

2018· article· en· W2796613209 on OpenAlexafffundabout
Qixing Zhou, Sheau‐Fang Hwang, Stephen E. Strelkov, Rudolph Fredua‐Agyeman, Victor P. Manolii

Bibliographic record

VenuePlant Pathology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversity of AlbertaAlberta Ministry of Agriculture and ForestryAgriculture Food and Rural Development
FundersAgriculture and Agri-Food CanadaAlberta Crop Industry Development Fund
KeywordsClubrootBiologyCanolaBrassicaPrimer (cosmetics)TaqManPathogenInoculationHost (biology)Polymerase chain reactionCultivarSporeMicrobiologyBotanyGeneticsGeneHorticulture

Abstract

fetched live from OpenAlex

Clubroot of crucifers, caused by Plasmodiophora brassicae , is managed in canola ( Brassica napus ) by the deployment of resistant cultivars. Recently, however, new strains of P. brassicae have been detected in Alberta, Canada, that can overcome this resistance. Some of these strains are classified as pathotype 5 on the differential system of Williams, but are distinguished by their ability to overcome host resistance. In order to expedite the identification of these new pathotype 5‐like strains, three primer sets were developed based on the 18S‐ ITS region of the pathogen. With primers P5XF3 and P5XR3, a 127 bp product was amplified from all new pathotype 5‐like strains following optimized PCR analysis. A TaqMan probe‐based quantitative assay was also developed. These protocols could be used to detect as little as 0.5 pg P. brassicae DNA , and as few as 10 4 mL −1 pathogen resting spores; infection of host tissues could be detected as soon as 4 days after inoculation. The PCR and qPCR assays described in this study represent useful tools for the rapid and reliable diagnosis and quantification of new pathotype 5‐like strains of P. brassicae .

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.147

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 head0.212
Teacher spread0.194 · 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 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

Citations19
Published2018
Admission routes3
Has abstractyes

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