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Record W2036116522 · doi:10.1139/g03-015

Mapping quantitative trait loci for a common bean (<i>Phaseolus vulgaris</i>L.) ideotype

2003· article· en· W2036116522 on OpenAlexafffundvenue
Aaron D. Beattie, Jamie Larsen, K. Peter Pauls

Bibliographic record

VenueGenome · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Rural Affairs
KeywordsBiologyIdeotypePhaseolusQuantitative trait locusPopulationGeneticsGenetic linkageTraitMolecular markerSelection (genetic algorithm)BotanyCultivarGene

Abstract

fetched live from OpenAlex

Breeding a model plant that encompasses individual traits thought to enhance yield potential, known as ideotype breeding, has traditionally focused on phenotypic selection of plants with desirable morphological traits. Broadening this breeding method to the molecular level through the use of molecular markers would avoid the environmental interactions associated with phenotypic selection. A population of 110 F5 recombinant inbred lines (RILs), derived from the cross between WO3391 and 'OAC Speedvale', was used to develop a genetic linkage map consisting of 105 random amplified polymorphic DNA (RAPD), simple sequence repeat (SSR), and sequence-tagged site (STS) markers. The map has a total length of 641 cM distributed across 8 linkage groups (LGs). Five of them were aligned on the core linkage map of bean. Twenty-one quantitative trait loci (QTLs) were identified over three environments for eight agronomic and architectural traits previously defined for a bean (Phaseolus vulgaris L.) ideotype. The QTLs were mapped to seven LGs with several regions containing QTLs for multiple traits. At least one QTL was located for each trait and a maximum of four were associated with lodging. Total explained phenotypic variance ranged from 10.6% for hypocotyl diameter to 45.4% for maturity. Some of the QTLs identified will be useful for early generation selection of tall, upright, high-yielding lines in a breeding program.

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 score0.966
Threshold uncertainty score0.217

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 head0.034
GPT teacher head0.235
Teacher spread0.201 · 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

Citations40
Published2003
Admission routes3
Has abstractyes

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