Economic Threshold for Soybean Aphid (Hemiptera: Aphididae)
Bibliographic record
Abstract
Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), reached damaging levels in 2003 and 2005 in soybean, Glycine max (L.) Merrill, in most northern U.S. states and Canadian provinces, and it has become one of the most important pests of soybean throughout the North Central region. A common experimental protocol was adopted by participants in six states who provided data from 19 yield-loss experiments conducted over a 3-yr period. Population doubling times for field populations of soybean aphid averaged 6.8 d ± 0.8 d (mean ± SEM). The average economic threshold (ET) over all control costs, market values, and yield was 273 ± 38 (mean ± 95% confidence interval [CI], range 111–567) aphids per plant. This ET provides a 7-d lead time before aphid populations are expected to exceed the economic injury level (EIL) of 674 ± 95 (mean ± 95% CI, range 275–1,399) aphids per plant. Peak aphid density in 18 of the 19 location-years occurred during soybean growth stages R3 (beginning pod formation) to R5 (full size pod) with a single data set having aphid populations peaking at R6 (full size green seed). The ET developed here is strongly supported through soybean growth stage R5. Setting an ET at lower aphid densities increases the risk to producers by treating an aphid population that is growing too slowly to exceed the EIL in 7 d, eliminates generalist predators, and exposes a larger portion of the soybean aphid population to selection by insecticides, which could lead to development 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".