The Buckwheat Effect: A Biopesticide for Wireworm?
Bibliographic record
Abstract
Growing buckwheat (Fagopyrum esculentum Moench. Caryophyllales: Polygonaceae) in rotation with potato and other vegetable crops has been reported to decrease the density of an invasive wireworm species (Agriotes sputator Linnaeus. Coleoptera: Elateridae) in Nova Scotia, Canada. It was predicted that the negative effects on wireworm populations result from phytochemicals by buckwheat that act as deterrents, anti-feedants, or toxins in the roots or when released into the soil. Choice assays were conducted to test the attractiveness of germinating, branching, and flowering buckwheat, red spring wheat (Triticum aestivum Linnaeus. Poales: Poaceae) and island barley (Hordeum vulgare Linnaeus. Poales: Poaceae) to the larvae. Twenty-one day, no choice feeding assays were conducted to determine change in mass and mortality of A. sputator larvae when fed buckwheat or barley. There was no evidence that the wireworms were deterred by buckwheat and the germinating stage of all three crops was the most attractive based on the 24-h choice assays. After the 21-d no choice feeding assays, no differences between hosts were observed; however, wireworm herbivory significantly reduced the growth of barley but not buckwheat. The findings from the no choice feeding assays suggest that buckwheat may produce anti-feedants, but longer term feeding assays and field trials are required to confirm this possibility.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".