Management of insecticide resistance in Oriental fruit moth (<i>Grapholita molesta</i>; Lepidoptera: Tortricidae) populations from Ontario
Bibliographic record
Abstract
The development of resistance in the Oriental fruit moth, Grapholita molesta (Busck) to organophosphorus (OP) insecticides (azinphos-methyl and phosmet) is a serious threat to the tender fruit industry in Ontario (50% crop losses in 1994). Resistance to carbamate insecticides and increased survival of field-collected moths at diagnostic concentrations of pyrethroids were widespread. As a result, four different treatment regimes were tested to manage resistance in G molesta, and the changes in resistance frequencies under each treatment regime were monitored from 1996 to 1999. The data indicated that the levels of resistance were significantly influenced by the various treatment regimes. The seasonal pattern of resistance was similar for all treatment regimes, in that resistance peaked in mid-season and declined in the late season. Levels of resistance in G molesta to OPs decreased from 55% to 14% and that to pyrethroids declined from 30% to 10% from 1996 to 1999 under a treatment regime consisting of endosulfan-organophosphate-pyrethroid rotation. Similarly, under a treatment regime implemented in commercial orchards (organophosphate-pyrethroid rotation), resistance to OP insecticides declined from 50% to 12% and resistance to pyrethroids evolved to around 16%. The overall data indicated that resistance was unstable; a strategy based on rotation of insecticides by class for each generation of G molesta was successful in managing resistance to both OP and pyrethroid insecticides. The rotational strategy has been widely adopted by growers and is applied to ca 85% of the acreage.
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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 | 0.000 | 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 | 0.001 | 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 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".