Aphid Infestation in Field Grown Lettuce and Biological Control with Entomopathogenic Fungi (<i>Deuteromycotina: Hyphomycetes</i>)
Bibliographic record
Abstract
The objective of this study was to identify the most common aphid species infesting field grown lettuce in Sweden and to evaluate the use of entomopathogenic fungi to suppress aphid infestations. Colonization of aphids to lettuce fields at two locations was monitored during two seasons. Aspects of the host specificity and pathogenicity of fungal isolates from different genera were tested under laboratory conditions on Macrosiphum euphorbiae (Thomas) and Nasonovia ribisnigri (Mosley) followed by field trials on the use of a bioinsecticide Vertalec® (Lecanicillium longisporum) against aphids. In the laboratory, a single exposure dose assay for each isolate was conducted, followed by a dose mortality assay on the most pathogenic isolates. Vertalec was included as a standard in all assays. The field trial had four treatments: untreated control, control treated with Confidor (Imidacloprid) and two Vertalec application treatments at different doses. In both seasons N. ribisnigri was the most commonly found aphid on lettuce. In bioassays, one Lecanicillum sp. isolate for M. euphorbiae and three Lecanicillium spp. isolates for N. ribisnigri were more pathogenic than the Vertalec isolate. Vertalec was pathogenic in the laboratory and caused a higher mortality than controls among the nymphs at one of the field sites, but neither Vertalec nor Confidor reduced total aphid population. This study identified pathogenic fungi that might be promising to use as bioinsecticides. However, in order to evaluate the usefulness of the identified pathogenic isolates as well as Vertalec as microbiological control agents in field grown crops, more studies in laboratory on abiotic factors as well as field studies over several seasons are necessary.
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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".