Dose-Response Susceptibility of Pest Aphids (Homoptera: Aphididae) and their Control on Hydroponically Grown Lettuce with the Entomopathogenic Fungus<i>Verticillium lecanii,</i>Azadirachtin, and Insecticidal Soap
Bibliographic record
Abstract
The objective of our research was to identify alternatives to synthetic pesticide treatments to prevent aphid outbreaks in greenhouse lettuce crops. In the laboratory, we determined the susceptibility of three lettuce-infesting aphid species, Macrosiphum euphorbiae (Thomas), Myzus persicae (Sulzer), and Nasonovia ribisnigri (Mosley), to the hyphomycete Verticillium lecanii (Viegas) (strain Vertalec), the plant triterpenoid molecule azadirachtin (BioNeem), and an insecticidal soap (Safer’s). Estimated LC50 and LT50 obtained in the laboratory indicated that the three aphid species were susceptible to the entomopathogenic fungus, the plant extract, and the soap. Under greenhouse conditions, we assessed the potential of the three pesticides to reduce aphid populations and compared it with that of a synthetic insecticide, the organophosphate Malathion. Greenhouse experiments demonstrated that all three pesticides significantly reduced the population of each aphid species compared with the untreated plants. This study also revealed differences in aphid susceptibility between aphid species and between laboratory bioassays and greenhouse trials. The high initial aphid densities, difficulties to reach the aphids on the undersurface of leaves, stains left by Vertalec on the harvested lettuce, and high cosmetic standards for lettuce mitigated the performance of the insecticides. The potential of using Vertalec, BioNeem, and Safer’s soap for the control of lettuce aphids is discussed in relation to aphid species and crop management.
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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 | 0.001 |
| 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".