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Record W2171304719 · doi:10.2135/cropsci2011.01.0046

Genetic Characterization and Molecular Mapping <i>Pse‐2</i> Gene for Resistance to Halo Blight in Common Bean

2011· article· en· W2171304719 on OpenAlexaboutno aff
Phillip N. Miklas, Deidré Fourie, Jennifer J. Trapp, R. C. Larsen, Carolina Chavarro, Matthew W. Blair, Paul Gepts

Bibliographic record

VenueCrop Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPhaseolusPseudomonas syringaeGeneticsCultivarPopulationPlant disease resistanceGeneMicrosatelliteBlightBotanyAllele

Abstract

fetched live from OpenAlex

ABSTRACT Pseudomonas syringae pv. phaseolicola (Burkholder) Young et al. ( Psp ) causes halo blight, which is a serious bacterial disease of common bean ( Phaseolus vulgaris L.). Several resistance (R) genes have been discovered in host differential cultivar ZAA 12. Our objectives were to further characterize and enable marker‐assisted selection (MAS) of the Pse‐2 gene in ZAA 12 purported to have broad effect against multiple Psp races. A recombinant inbred population, ZAA 12 × ‘Canadian Wonder’, was challenged by the halo blight pathogen differential set consisting of nine Psp races. The resistance conferred by Pse‐2 to races 2, 3, 4, 5, 7, 8, and 9 expanded the effect known for this gene from three to seven races. Segregation in F 2 populations confirmed dominant inheritance for Pse‐2 against all races except Race 8. Resistance to Race 8 was recessively inherited and most closely fit a 7 resistant to 9 susceptible segregation ratio in the F 2 generation. Perhaps other genes are segregating that modify the effect of Pse‐2 against Race 8. A sequence characterized amplified region (SCAR) marker tightly linked with Pse‐2 was generated. The marker was used to integrate Pse‐2 to chromosome 10. A survey of lines and cultivars revealed the SCAR will have broad utility for MAS of Pse‐2 .

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.186

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 head0.022
GPT teacher head0.199
Teacher spread0.178 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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