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Record W2235129858 · doi:10.1094/pdis-05-15-0605-re

A Quantitative PCR System for Measuring <i>Sclerotinia sclerotiorum</i> in Canola (<i>Brassica napus</i>)

2015· article· en· W2235129858 on OpenAlexafffund
Barbara R Ziesman, T. Kelly Turkington, Urmila Basu, Stephen E. Strelkov

Bibliographic record

VenuePlant Disease · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsAlberta Crop Industry Development FundAgriculture and Agri-Food CanadaUniversity of Alberta
FundersAlberta Canola Producers CommissionUniversity of AlbertaCanola Council of CanadaAgriculture and Agri-Food CanadaWestern Grains Research FoundationAlberta Crop Industry Development Fund
KeywordsSclerotinia sclerotiorumSclerotiniaCanolaStem rotBiologyBrassicaInfestationPetalRapeseedHorticultureAgronomy

Abstract

fetched live from OpenAlex

Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, is an economically important disease of canola (Brassica napus) commonly managed by routine application of fungicides. Petal infestation has been demonstrated to be an important stage of the disease cycle in canola and has been the focus of previously developed Sclerotinia stem rot risk assessment methods. Quantitative polymerase chain reaction (qPCR) analysis can provide a more rapid and accurate assessment of petal infestation levels. Primers and a hydrolysis probe were designed to amplify a 70-bp region of an S. sclerotiorum-specific gene, SS1G_00263. A hydrolysis probe-based qPCR assay was developed that had a detection limit of 8.0 × 10 −4 ng of S. sclerotiorum DNA and only amplified S. sclerotiorum DNA. Evaluation of petals collected at five sampling points in each of 10 commercial canola fields on each of two sampling dates (corresponding to 20 to 30% bloom and 40 to 50% bloom) revealed S. sclerotiorum DNA infestation levels of 0 to 3.3 × 10 −1 ng/petal. This qPCR assay can be used to reliably quantify petal infestation and, with further research, has the potential to serve as the basis for a Sclerotinia stem rot risk assessment tool or as a means to study Sclerotinia stem rot epidemiology.

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 score0.870
Threshold uncertainty score0.305

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 head0.073
GPT teacher head0.223
Teacher spread0.150 · 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

Citations20
Published2015
Admission routes2
Has abstractyes

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