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Record W2773939028 · doi:10.3954/jaue17-17.1

Laboratory Evaluation of Soybean Plant Introductions for Resistance to<i>Aphis glycines</i>(Hemiptera: Aphididae)<sup>1</sup>

2017· article· en· W2773939028 on OpenAlexaboutno aff
Louis S. Hesler, Brian M. Van De Stroet, Nicole R. Schultz, Eric A. Beckendorf, Kelley J. Tilmon

Bibliographic record

VenueJournal of Agricultural and Urban Entomology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
FundersAgricultural Research Service
KeywordsSoybean aphidAphididaeBiologyGermplasmPEST analysisCultivarHemipteraSoybean mosaic virusAgronomyHorticultureHomopteraBotanyGeneticsPlant virusPotyvirus

Abstract

fetched live from OpenAlex

The soybean aphid (SA), Aphis glycines Matsumura, is a major pest of soybean in the north-central United States and south-central Canada. It is controlled primarily with insecticides, but the development of aphid-resistant soybean cultivars may provide an alternative management tactic. The viability of this management tactic depends on a diverse set of resistance sources in order to counter various resistance-breaking biotypes of SA, and the identification of new sources of resistance necessitates additional testing of soybean germplasm. The current study used no-choice tests to identify SA resistance in seven early maturing (maturity group I) soybean plant introductions (PIs) that had been advanced from free-choice screening trials. The tests showed PI 437353 and PI 612759 C had an intermediate level of resistance against avirulent SA, whereas PI 437282, PI 437658, PI 437733, PI 548417, and PI 548530 exhibited no significant resistance. Additional research is needed to determine if the source of resistance in PI 437353 and PI 612759 C is due to novel resistant genes, which would help diversify resistance to SA in soybean. Screening and follow-up tests of additional soybean germplasm is warranted in order to ensure the development of durable, SA-resistant cultivars.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.241
Teacher spread0.224 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

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