Implementation of a Diagnostic-Concentration Bioassay for Detection of Susceptibility to Pyrethroids in Soybean Aphid (Hemiptera: Aphididae)
Bibliographic record
Abstract
Soybean aphid, Aphis glycines Matsumura, remains the most economically damaging arthropod pest of soybean in the midwestern United States and southern Canada. Foliar applications of a limited number of insecticide modes of action have been the primary management tactic, and pyrethroid resistance was documented recently with full concentration-response leaf-dip and glass-vial bioassays. Full concentration-response bioassays can be cumbersome, and a more efficient assessment tool was needed. In this study, we implemented a diagnostic-concentration glass-vial bioassay using bifenthrin and λ-cyhalothrin. Bioassays were conducted with field-collected soybean aphid populations to assess the geographic extent and severity of resistance to pyrethroids. In 2017, 10 of 18 and 11 of 21 field populations tested with bifenthrin and λ-cyhalothrin, respectively, had mean proportion mortalities less than the susceptible laboratory population. In 2018, 17 of 23 and 13 of 23 field populations tested with bifenthrin and λ-cyhalothrin, respectively, had mean proportion mortalities less than the susceptible laboratory population. Populations collected after reported field failures of a pyrethroid insecticide generally had mean proportion mortalities less than the susceptible laboratory population. In both years, there was a strong correlation between chemistries, which suggests cross-resistance between these insecticides. The diagnostic-concentration glass-vial bioassays reported here will provide the foundation for an insecticide resistance monitoring program with the ability to determine practical levels and geographic extent of insecticide resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".