Attract and kill, an effective technique to manage apple maggot, Rhagoletis pomonella [Diptera : Tephritidae] in high density Quebec apple orchards
Bibliographic record
Abstract
"Attract and kill" is an effective technique to control apple maggot (Rhagoletis pomonella) in apple orchards. It provided 98.5 to 100% clean fruit at harvest in McIntosh, Liberty, Royal Gala and Jonagold cvs. The traps consisted of yellow boards (28 cm x 21.5 cm) sandwiched between the two halves of red spheres (9 cm diam). They were sprayed with 12.5 and 6.3% cypermethrin or 1.3 and 1.7% deltamethrin in de-odorized kerosene, loaded with butyl hexanoate in semi-permeable sachets. The traps were hung on branches 1.20-1.70 m above the ground. They were placed on the periphery of the plot and positioned so as to be visible from outside the tree canopy. The number of traps per plot was a function of the length of the plot opposite a possible entry site of apple maggot. In columns opposite a forest, entry site of apple maggot into the plot, the traps in a column were at 2-3 m intervals (0.3-0.5 traps m-1). A trap was also placed on every tree of the first and last row of a column. The columns were 4-5.5 m apart (0.18-0.25 traps m-1). Opposite to prairie grass or a chemically treated plot the traps were at 2-6 m intervals (0.17-0.5 traps m-1) in a column. On the row, the distance between adjacent traps was 4 to 12 m (0.08-0.25 traps m-1). To achieve commercially acceptable apple maggot control in cvs. McIntosh, Liberty, Gala and Jonagold apples with "attract and kill" technique, the activity of the pest should not exceed 13 flies per four traps placed on the periphery of the plot, in other words, 1.6 times the action threshold for the apple maggot in Quebec apple orchards.
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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) | 0.002 | 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".