A global review of orange wheat blossom midge,<i>Sitodiplosis mosellana</i>(Géhin) (Diptera: Cecidomyiidae), and integrated pest management strategies for its management
Bibliographic record
Abstract
Abstract Orange wheat blossom midge,Sitodiplosis mosellana(Géhin) (Diptera: Cecidomyiidae), is a major economic pest of wheat (Triticum aestivumLinnaeus). Here, we review its general biology, history of global spread, economic impact, and methods available to manage its populations. Outbreaks have been reported across the Northern Hemisphere, including in China, Japan, the European Union, the United Kingdom, the United States of America, and Canada. Predators and parasitoids can help attenuate these outbreaks, but control has relied mainly on use of foliar insecticides. Wheat cultivars with resistance to midge conferred by theSm1gene became commercially available in 2010 and increasingly are grown to manage midge populations. Forecasting models have been developed in different countries to predict wheat midge populations in an effort to mitigate the degree of economic damage by supporting wheat cultivar selection and to optimise the timing of insecticide applications in conventional wheat production systems. Conservation of natural enemies, insecticides, resistant cultivars, and models combine to form effective integrated pest management programmes for midge, illustrated for Canada with a decision-making flowchart. Future work is needed to address the likely development of midge biotypes with resistance to theSm1gene and insecticides currently in use.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".