Laboratory and Field Evaluation of Host-Related Foraging Odor-Cue Combinations to Attract Drosophila suzukii (Diptera: Drosophilidae)
Bibliographic record
Abstract
The invasive spotted-wing drosophila, Drosophila suzukii (Matsumura), is a major pest of soft-skinned fruits. Since its introduction into North America and Europe, significant progress has been made in understanding the volatile cues used by this fly during food, oviposition site, and mate finding. Despite this progress, commercially available lures are non-selective. Here, we tested two Hanseniaspora uvarum (Niehaus) yeast compounds (isoamyl acetate and isobutyl acetate) and a leaf compound β-cyclocitral alone and in combination with a blend of four fermentation compounds ('Fermentation lure': acetic acid, ethanol, methionol, and acetoin) to improve D. suzukii attraction and selectivity. In laboratory assays, males and females were attracted to all seven individual compounds, although in electrophysiological assays, their antennae exhibited a dose-dependent response to only four of these compounds. In two-choice cage studies, the Fermentation lure was more attractive to D. suzukii than water controls, whereas β-cyclocitral and the mixture of isoamyl acetate and isobutyl acetate were not attractive in this larger-cage study. Moreover, adding the two-component H. uvarum compound blend to the Fermentation lure reduced D. suzukii attraction to the Fermentation blend. When these experiments were repeated in blueberry, raspberry, blackberry, and cherry orchards across several states in the United States over 2 yr, similar outcomes were observed: β-cyclocitral or the mixture of the H. uvarum blend did not improve the attractiveness of the Fermentation lure or its selectivity. This study demonstrates that cues from different sources may interfere with each other and reduce D. suzukii attraction to otherwise attractive odor combinations.
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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) | 0.001 | 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".