Emergence of Blueberry Maggot Flies (Diptera: Tephritidae) From Mulches and Soil at Various Depths
Bibliographic record
Abstract
Control of blueberry maggot, Rhagoletis mendax Curran, typically is achieved with insecticides targeting adult flies before females oviposit in ripening fruit. Management strategies targeting other life stages have received less attention. We tested effects of compost or pine needle mulches on emergence of blueberry maggot flies under laboratory and field conditions. Few flies emerged from pupae that were buried under 20 cm of pine needles in all experiments, but burial in 20 cm of compost did not always result in low fly emergence. Burial of pupae in 5 cm of compost or pine needles did not reduce fly emergence compared with 1 cm in soil. Low emergence with increased mulch depth appeared to be primarily because of failure of flies to ascend to the surface after they exited puparia. Low emergence also was associated with high moisture levels causing rotten, discolored pupae, particularly in the laboratory in compost. No flies emerged from pupae buried in 1 cm of pine needles in the field. In this case no flies exited puparia, likely because high temperatures (>30°C) at the surface killed pupae. Thus, mulch application under highbush blueberries (Vaccinium corymbosum L.) after maggots drop from berries can reduce emergence success of flies from buried pupae, but the level of control will depend on mulch depth and may vary with rainfall and temperature.
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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 | 0.000 | 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) | 0.001 | 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".