Economic thresholds and economic injury level for pea aphid in tannin and low tannin faba bean
Bibliographic record
Abstract
Pea aphids , Acyrthosiphon pisum , are one of the major insect pests of faba bean ( Vicia faba ). Infestations of pea aphids on faba bean can occur at any plant growth stage and result in drastic yield losses (up to 100%). There was no established guideline to determine when to manage pea aphids on faba bean in Saskatchewan. We conducted a field study to develop an economic threshold for pea aphids on faba bean at six sites in the Saskatoon area in 2019 and 2020. No choice experiments were performed to determine pea aphid growth rate on tannin and low tannin faba bean. Under field conditions, the population of pea aphids on faba bean doubled in approximately 5.25 ± 0.19 days. The average economic threshold (ET) was 34–50 aphids per main stem of a plant. This ET provides a 7-day lead time before aphid populations are expected to exceed the economic injury level (EIL) of 680–984 cumulative aphid days or 96 to 142 aphids per faba bean main stem. All ETs were estimated based on the cost of registered insecticides and the average of three benchmark prices (high, medium and low) of faba bean from January 2018 to July 2021. Laboratory no-choice bioassays demonstrated no significant effect of faba bean tannins on pea aphid growth. Therefore, economic thresholds established in this study are applicable to both tannin and low tannin varieties of faba bean.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".