Managing Flea Beetles (<i>Phyllotreta</i> spp.) (Coleoptera: Chrysomelidae) in Canola with Seeding Date, Plant Density, and Seed Treatment
Bibliographic record
Abstract
Fall seeding of canola can increase equipment and manpower efficiencies for producers, hasten crop maturity, and improve seed quality, but no previous studies have examined effects of this practice on infestations of flea beetles ( Phyllotreta spp.) (Coleoptera: Chrysomelidae), the major pests of crop seedlings in North America. Field experiments were conducted at Vegreville, Fort Saskatchewan, and Lethbridge, AB, Canada from 1998 through 2000 to determine the effect of fall versus spring seeding of canola ( Brassica napus L. and Brassica rapa L.) on feeding damage by flea beetles. Interactions with seeding rate and seed treatment on flea beetle damage also were investigated. Flea beetle damage was greater on plants of B rapa than B napus , on spring‐seeded canola than on plants seeded in fall, and on plants that developed from seed treated with Vitavax Single (containing carboxin) than on plants treated with Vitavax rs (containing carboxin, thiram, and lindane). Mean flea beetle damage per plant declined with an increase in seeding rate. Canola seeded in fall reached 50% flowering about 10 d earlier than plants seeded in April and about 20 d before plants seeded in May. Fall‐seeded plants matured 5 to 21 d earlier than plants seeded in April and about 10 to 30 d before plants seeded in May. Seeding in fall enabled plants to progress beyond the vulnerable cotyledon stage by the time that most flea beetle injury occurred. Seeding canola in fall, at rates selected to achieve vigorous plant stands, is an important component of an integrated management strategy for flea beetles, with the potential for substantially reducing insecticide use in this crop.
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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 | 0.000 |
| 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 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".