Ability of Muscidifurax raptorellus and Other Parasitoids and Predators to Control Drosophila suzukii Populations in Raspberries in the Laboratory
Bibliographic record
Abstract
Drosophila suzukii is an invasive pest and economic threat to berry crops in Europe and the Americas. Current methods of control of this pest rely primarily on frequent applications of insecticides; therefore, there is a need for alternative control methods to reduce insecticide reliance. In this study, we evaluated the biological control potential of three parasitoid wasps: Diglyphus isaea, Muscidifurax raptorellus and Pachycrepoideus vindemmiae, and four predators: Chrysoperla carnea, Dicyphus hesperus, Orius insidiosus and Podisus maculiventris. Experiments were conducted for 15 days under controlled conditions in experimental arenas with D. suzukii females and raspberries, allowing for all life stages of D. suzukii to be available to natural enemies. Results showed the first evidence of M. raptorellus’s ability to parasitize D. suzukii, resulting in a 40% reduction. Orius insidiosus, P. vindemmiae and C. carnea were also efficient, reducing D. suzukii numbers by 49%, 43% and 32%, respectively. Predator preferences for each D. suzukii life stage were assessed. The clutch size, sex ratio and adult size variability of D. suzukii pupal parasitoids were also evaluated. This study expands the list of species that can effectively parasitize D. suzukii and provides new insights into the biological responses of M. raptorellus to D. suzukii pupae.
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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".