Trap cropping for insect pests in the Canadian Prairies: a review and a case study
Bibliographic record
Abstract
Abstract The Canadian Prairies are one of the major agricultural regions of the world in terms of cereal, oilseed and pulse crop production. With few exceptions, major insect pests like grasshoppers, flea beetles, Lygus bugs, wireworms and pea leaf weevils are controlled with insecticides. Wheat stem sawfly is managed through host plant resistance and endemic natural enemies, whereas cereal leaf beetle is managed through classical biological control. Large farms and short growing seasons in the region present logistical challenges to adopt time intensive pest management systems such as trap crops. Therefore, there is no adoption of trap crops even though some research has demonstrated their potential. In this article we present a brief overview of the pest status and management, and we summarize research on trap crops in the Prairies Ecozone and adjacent ecoregions. We conclude the review with some innovative research ideas to make trap cropping a more appealing pest management system in our quest to reduce dependency on chemical insecticides and increase the environmental resilience of Canadian agroecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".