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Assessment of the impact of resistant and susceptible canola on <i>Plasmodiophora brassicae</i> inoculum potential

2012· article· en· W1962897542 on OpenAlexafffund
Sheau‐Fang Hwang, Hammad Ahmed, Qixing Zhou, Stephen E. Strelkov, B. D. Gossen, Gary Peng, G. D. Turnbull

Bibliographic record

VenuePlant Pathology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversity of AlbertaAgriculture and Agri-Food CanadaAgriculture Food and Rural Development
FundersCanola Council of CanadaSaskatchewan Canola Development CommissionAlberta Crop Industry Development Fund
KeywordsClubrootCanolaBiologyCultivarAgronomyCropHorticultureBotanyBrassica

Abstract

fetched live from OpenAlex

The impact on clubroot severity of growing susceptible canola or mixtures of resistant and susceptible canola genotypes was examined. Bioassays revealed greater clubroot severity and incidence, and reduced plant height, where 100% of a susceptible cultivar had been grown. A higher proportion of susceptible plants within a resistant canola crop increased root hair and secondary infections. Regression analysis of root hair infection and the amount of Plasmodiophora brassicae DNA (as determined by quantitative PCR) revealed strong linear relationships between the two parameters. The linear relationships between root hair infection and P. brassicae DNA were stronger for the resistant cultivar than for the susceptible cultivar when regression analysis was conducted by cultivar over the sampling dates. In conclusion, the cropping of a resistant cultivar reduced clubroot severity, while the presence of susceptible volunteer canola increased inoculum potential. Quantitative PCR was a reliable tool for the quantification of root hair infection.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.241
Teacher spread0.230 · 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

Citations53
Published2012
Admission routes2
Has abstractyes

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