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Record W2132879935 · doi:10.1094/phyto-100-1-0080

Mapping Net Form Net Blotch and Septoria Speckled Leaf Blotch Resistance Loci in Barley

2009· article· en· W2132879935 on OpenAlexaff
Summer St. Pierre, C. D. Gustus, Brian J. Steffenson, Ruth Dill‐Macky, Kevin P. Smith

Bibliographic record

VenuePhytopathology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsSmiths Detection (Canada)
FundersCenters for Disease Control and Prevention
KeywordsBiologySeptoriaQuantitative trait locusGermplasmHordeum vulgarePopulationLocus (genetics)Plant disease resistanceGeneticsAgronomyPoaceaeGene

Abstract

fetched live from OpenAlex

Septoria speckled leaf blotch (SSLB), caused by Septoria passerinii Sacc., and net form net blotch (NB), caused by Pyrenophora teres f. teres Drechsler, are fungal diseases that decrease the yields of barley in the Upper Midwest. An effective way to manage these diseases is to plant resistant cultivars. To characterize the genetics of resistance to both pathogens, two advanced barley breeding lines, one resistant to NB (M120) and another resistant to SSLB (Sep2-72), were crossed, creating a population of 115 recombinant inbred lines. The two parents and the population were evaluated in three greenhouse seedling assays for each pathogen and for simple-sequence repeat and diversity arrays technology markers. Composite interval mapping revealed two major quantitative trait loci (QTL) associated with NB on chromosome 6H, located in bins 2 and 6. The QTL located in bin 6 explained 19 to 48% of the phenotypic variation and the QTL located in bin 2 explained 25 to 44% of the phenotypic variation. A new locus for resistance to SSLB, Rsp4, was identified on chromosome 6H, located in bins 3 to 4. Mapping these genes in elite breeding germplasm will accelerate the development and utilization of marker-assisted selection to enhance resistance to these diseases.

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 score0.827
Threshold uncertainty score0.423

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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

Citations37
Published2009
Admission routes1
Has abstractyes

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