Oviposition Preference of the American Hoverfly, Eupeodes americanus, between Banker Plants and Target Crops
Bibliographic record
Abstract
Assessing the oviposition preferences of predatory hoverflies is a key factor in the prediction of the success of these biological control agents against aphids in greenhouses, especially when using banker plant systems or in mixed-crop contexts. In this study, two aspects of the oviposition preferences of the American hoverfly, Eupeodes americanus (Wiedemann, 1830) (Diptera: Syrphidae), were evaluated. Firstly, the preference between the banker plant and the target crop was evaluated for three banker plant species (barley, finger millet, or corn) and two target crops (cucumber or pepper). Secondly, the preference between the same two target crops was assessed. Female oviposition preferences were evaluated via two-choice experiments using different plant/aphid systems. The results showed that, for the cucumber crops, the species of banker plant used drastically influenced the oviposition preference of the hoverfly, with a preference for barley over cucumber, cucumber over finger millet, and no preference between corn and cucumber. Unlike cucumber, when used with pepper, barley engendered a preference for the target crop. We conclude that the barley banker plant could be adequate for aphid control in pepper but not in cucumber crops. In a mixed-crop context, the American hoverfly had no preference between cucumber and pepper, which means it has the potential to protect both crops in a mixed-crop greenhouse context. This study shows that the banker plant system should be carefully chosen according to the crops/aphids present in the greenhouse to optimize the impact of the hoverfly as a biocontrol agent. Further work is required to confirm this choice of banker plant in semifield or field testing.
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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".