Greenhouse Studies of Thiamethoxam Effects on Pea Leaf Weevil,<i>Sitona lineatus</i>
Bibliographic record
Abstract
The pea leaf weevil, Sitona lineatus L. (Coleoptera: Curculionidae), has recently emerged as an important pest of field peas in the Canadian prairies. Systemic seed-coated insecticides may provide a tool for the integrated pest management of this pest. Therefore, several controlled assays were performed in order to determine effects of a recently registered neonicotinoid, (thiamethoxam) on S. lineatus damage to foliage, weevil mortality, fertility, egg viability, larval mortality, and root nodule damage. Foliage damage was reduced by thiamethoxam relative to untreated controls during the seedling stage (2(nd)-5(th) nodes), but weevil adult mortality was only 15-30%. Fertility was reduced substantially through an extra seven-day delay in the preoviposition period and reduced egg-laying rate during the first 20 days of the study (92% lower than controls). Overall egg viability was lower in females fed foliage grown from thiamethoxamtreated seeds. Larval survivorship and nodule damage were also lower, but only when eggs were added to treated plants at the 2(nd) node stage. When eggs were added late, at the 5th node stage, thiamethoxam had no effect on larval survivorship or nodule damage. The results of this study led to the conclusion that seed treatments such as thiamethoxam have potential to be used as tools that will aid in the integrated pest management of S. lineatus, especially in combination with other methods such as biocontrol and trap crops.
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 | 0.000 | 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 | 0.001 |
| 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".