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Record W2182422225 · doi:10.4141/cjps2011-101

A reproducible assay for measuring partial resistance to <i>Sclerotinia sclerotiorum</i> in soybean

2012· article· en· W2182422225 on OpenAlexafffundvenueabout
Maxime Bastien, Tung Thanh Huynh, Geneviève Giroux, Elmer Iquira, S. Rioux, François Belzile

Bibliographic record

VenueCanadian Journal of Plant Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsGrain Research CentreUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSclerotinia sclerotiorumSclerotiniaStem rotBiologyCultivarInoculationMyceliumHorticultureAgronomyQuantitative trait locusInbred strainGeneGenetics

Abstract

fetched live from OpenAlex

Bastien, M., Huynh, T. T., Giroux, G., Iquira, E., Rioux, S. and Belzile, F. 2012. A reproducible assay for measuring partial resistance to Sclerotinia sclerotiorum in soybean. Can. J. Plant Sci. 92: 279–288. In eastern Canada, Sclerotinia stem rot in soybean is an important disease, and resistance is systematically assessed in cultivar performance trials. The reference method used in these trials closely mimics the natural infection process, but is very demanding, and its success is highly subject to environmental conditions. Here we describe a simple, quick and reproducible inoculation method to measure resistance to pathogen progression on the main stem. Importantly, this method is the first to reproducibly identify quantitative trait loci (QTLs) conferring partial resistance to Sclerotinia stem rot in soybean. In this method, a cotton pad saturated with a mycelial suspension is applied to a floral bud and resistance is estimated by measuring lesion length on the main stem. The method was found to discriminate clearly between known resistant and susceptible checks in both the field and greenhouse. Clear discrimination between 26 recombinant inbred lines (RILs) contrasted for QTLs controlling resistance to Sclerotinia stem rot was also achieved in four independent trials, and lesion length was significantly correlated among all trials. When tested on 38, 42 and 40 lines in registration trials, the results of this method were significantly correlated with those of the reference method in 2 of 3 yr.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.718
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.216
Teacher spread0.170 · 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

Citations22
Published2012
Admission routes4
Has abstractyes

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