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Record W2012790648 · doi:10.2135/cropsci2014.07.0473

Evaluation and Reselection of Wheat Resistance to Russian Wheat Aphid Biotype 2

2014· article· en· W2012790648 on OpenAlexaboutno aff
Xiangyang Xu, Guihua Bai, Brett F. Carver, Kehui Zhan, Yinghua Huang, D. W. Mornhinweg

Bibliographic record

VenueCrop Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
Fundersnot available
KeywordsRussian wheat aphidBiologySecaleCultivarAgronomyResistance (ecology)HomogeneousBotanyAphididaePEST analysisHomoptera

Abstract

fetched live from OpenAlex

ABSTRACT Russian wheat aphid (RWA, Diuraphis noxia , Mordvilko) biotype 2 (RWA2) is virulent to most known RWA resistance genes and severely threatens wheat ( Triticum aestivum L.) production in the hard winter wheat area of the U.S. western Great Plains. We determined RWA2 reactions of 386 cultivars from China, 227 advanced breeding lines and recently released cultivars from the United States, 505 landraces from countries where RWA is endemic, and 31 genetic stocks developed in the United States, Australia, Canada, and Russia. The majority of wheat accessions from China and the United States were highly susceptible to RWA2. Only nine landrace accessions produced a homogeneous resistant reaction. In addition, highly resistant plants were identified in 28 heterogeneous landraces. Thus, reselection was conducted to purify some potential resistance sources, and the single‐plant progenies of 220 selected plants were evaluated. Homogeneous resistant or highly resistant lines were identified from seven previously heterogeneous landraces. Reselection line PI 626759‐20‐32 offered a high level of resistance similar to lines carrying Dn7 , the rye ( Secale cereale L.)‐derived resistance gene associated with undesirable bread‐making quality. PI 626759‐20‐32 has the potential to supplement or replace Dn7 as a new RWA2 resistance source in wheat breeding.

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)0.001
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 score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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