Combined effects of canola plant density and insecticide management strategies on flea beetle abundance, canola defoliation, and yield across the <scp>Canadian</scp> prairies
Bibliographic record
Abstract
The crucifer flea beetle, Phyllotreta cruciferae (Goeze), and the striped flea beetle, Phyllotreta striolata (Fabricius) (Coleoptera: Chrysomelidae), are devastating pests of canola (Brassica napus (L.)) in North America. Currently, farmers rely on prophylactic, neonicotinoid insecticide-coated seed to control them. This results in most fields being treated with insecticides regardless of flea beetle levels. Moreover, if emergence of canola or seedling growth is delayed, or under very high flea beetle populations, seed treatments alone can fail to suppress damage and require foliar insecticides or reseeding. We conducted 15 replicated field trials in four regions of the Canadian prairies testing the effects of three canola planting densities combined with two flea beetle management treatments (seed treatment and foliar spray) and two controls ('flea beetle-free' treatment and untreated control) from 2018 to 2021. Although flea beetles increased as plant density increased, as predicted by the resource concentration hypothesis, this was offset by a dilution at the plant level and critically, defoliation levels did not increase at high plant densities. Using seed treatments as a management strategy generally produced similar results to using only foliar sprays at the 25% injury threshold when considering flea beetles per plant and yield. More importantly, yield increased with increased plant density regardless of flea beetle abundance, management treatment, and region. We conclude that increasing plant density is a sustainable technique that may be combined with other strategies to protect canola yield, but finding an economical plant density to protect yield from flea beetle damage will require further research. © 2025 His Majesty the King in Right of Canada and The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. Reproduced with the permission of the Minister of Agriculture and Agri-Food.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 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 teacher head, 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".