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Record W2068256857 · doi:10.2135/cropsci2009.06.0311

Identification of QTLs Associated with Partial Resistance to White Mold in Soybean Using Field‐Based Inoculation

2010· article· en· W2068256857 on OpenAlexafffund
Tra Huynh, M. Bastien, Elmer Iquira, Pierre Turcotte, François Belzile

Bibliographic record

VenueCrop Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsGrain Research CentreMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsBiologySclerotinia sclerotiorumQuantitative trait locusInoculationGenotypeGeneticsCultivarAlleleHybridHorticultureWhite (mutation)ChromosomeBotanyGene

Abstract

fetched live from OpenAlex

White mold caused by Sclerotinia sclerotiorum (Lib.) de Bary can be an important cause of yield loss in soybean. Only partial resistance to this disease has been found to date, and little is known about the loci contributing to this resistance. The objectives of this study were to identify quantitative trait loci (QTL) associated with partial resistance to white mold progression on the main stem. One hundred eighty F 4 –derived lines from a cross between a partially resistant cultivar, Maple Donovan, and a susceptible cultivar, OAC Bayfield, were tested for resistance to white mold under field conditions with (2003 and 2004) or without irrigation (2005 and 2006). The resistance of the lines was assessed by measuring the length of lesions 7 d after inoculation with a mycelial suspension. These lines were genotyped with 128 simple sequence repeat markers, and three QTLs associated with lesion length were detected consistently (in at least three of the four trials). Two of the QTLs were located on LG C2 (chromosome 6) and the third was on LGI (chromosome 20). In these genomic regions, the favorable alleles came from Maple Donovan and contributed to a decrease in lesion length. Together, they accounted for 30.7 to 50.9% of lesion length variation across year trials. Selective phenotyping of 26 lines carrying contrasting alleles at these QTLs in four additional environments resulted in significant phenotypic contrasts between the two genotypic classes.

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 score0.571
Threshold uncertainty score0.104

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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

Citations48
Published2010
Admission routes2
Has abstractyes

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