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Record W2152396680 · doi:10.1603/0046-225x-35.2.249

Sex Pheromone of the Soybean Aphid,<i>Aphis glycines</i>Matsumura, and Its Potential Use in Semiochemical-Based Control

2006· article· en· W2152396680 on OpenAlexaboutno aff
Junwei Zhu, Aijun Zhang, Kye-Chung Park, Tom Baker, Brian J. Lang, Russell A. Jurenka, John J. Obrycki, William R. Graves, John A. Pickett, D. W. M. Smiley, Kamlesh R. Chauhan, Jerome A. Klun

Bibliographic record

VenueEnvironmental Entomology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsSoybean aphidBiologySemiochemicalOverwinteringAlateAphidAphididaeSex pheromonePheromoneAgronomyPEST analysisBotanyHomoptera

Abstract

fetched live from OpenAlex

The newly invasive soybean aphid, Aphis glycines Matsumura, has seriously threatened soybean production in North America, after having spread to >20 states in the United States and several southern provinces of Canada. Control of A. glycines has focused on applications of insecticides, which are not a long-term solution to soybean aphid pest management. In autumn, soybean aphids start producing alate females (gynoparae) that search for their overwintering host plants, the common buckthorn, Rhamnus cathartica. The gynoparae then produce pheromone-emitting wingless female offspring (oviparae) that attract male aphids. In this study, we report the chemical identification of the soybean aphid sex pheromone using gas chromatography–electroantennogram, gas chromatography–mass spectrometry, and nuclear magnetic resonance spectroscopy. Behavioral activities of males and gynoparous females in the field were also characterized. The potential applications using formulations containing specific soybean aphid pheromone compositions for reducing overwintering populations are discussed.

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 score0.606
Threshold uncertainty score0.446

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 head0.005
GPT teacher head0.167
Teacher spread0.162 · 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

Citations23
Published2006
Admission routes1
Has abstractyes

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