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Record W1967686498 · doi:10.1094/phyto-10-12-0271-r

Association Mapping of Septoria Speckled Leaf Blotch Resistance in U.S. Barley Breeding Germplasm

2013· article· en· W1967686498 on OpenAlexaboutno aff
Hao Zhou, Brian J. Steffenson

Bibliographic record

VenuePhytopathology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyQuantitative trait locusGermplasmSeptoriaHordeum vulgarePlant disease resistanceCultivarGenetic markerGeneticsMarker-assisted selectionSingle-nucleotide polymorphismIntrogressionAgronomyPoaceaeGenotypeGene

Abstract

fetched live from OpenAlex

Septoria speckled leaf blotch (SSLB) is a sporadic but important disease of barley (Hordeum vulgare) in the Upper Midwest region of the United States and Prairie Provinces of Canada that is caused primarily by Septoria passerinii. Most of the widely grown cultivars in the region are susceptible to the disease. To identify and map SSLB resistance loci in U.S. barley breeding germplasm, we employed an association mapping approach using 3,840 breeding lines and cultivars and nearly 3,000 single-nucleotide polymorphism markers previously mapped to the seven barley chromosomes. SSLB infection responses (IRs) were assayed on seedling plants in the greenhouse using a 0-to-5 scale. From the analysis of four yearly panels consisting of 960 lines each, four quantitative trait loci (QTL) for SSLB resistance were identified: one on chromosome 1H (Rsp-qtl-H_12_31144), one on chromosome 3H (Rsp-qtl-3H_12_31488), and two on chromosome 6H (Rsp-qtl-6H_11_21032 and Rsp-qtl-6H_11_10064). Individual resistance QTL reduced the mean IR from 9 to 38% compared with lines lacking any resistance alleles. However, the combination of all four resistance QTL together reduced the mean IR by 83%. The markers found associated with these QTL will be valuable for programs utilizing marker-assisted selection for SSLB resistance.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.469

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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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 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

Citations14
Published2013
Admission routes1
Has abstractyes

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