Identification of potential predators of western bean cutworm (<i>Striacosta albicosta</i>) in field corn through molecular gut‐content analysis
Bibliographic record
Abstract
Abstract Western bean cutworm, Striacosta albicosta (Smith; Lepidoptera: Noctuidae), is a major pest of corn and dry beans in its historic and expanded ranges in the North American western Great Plains and Great Lakes Region, respectively. In corn, S. albicosta ear feeding damage can significantly reduce yield and introduce avenues for secondary fungal infections. Management practices currently rely on transgenic crops expressing effective Bacillus thuringiensis (Bt) protein, of which only the VIP3A protein is effective against S. albicosta, and/or labor‐intensive scouting and chemical control. However, limited research on biological control options for this critical pest has been conducted. This study identifies key trophic interactions between S. albicosta and predatory arthropods in corn fields. Field surveys identified a community of 21 predator taxa present in Nebraska corn fields where S. albicosta eggs and larvae were present. The most common taxa were as follows: Hippodamia convergens (Guérin‐Méneville; Coleoptera: Coccinellidae), Coleomegilla maculata (De Geer; Coleoptera: Coccinellidae), Orius insidiosus (Say; Hemiptera: Anthocoridae), and green lacewings (Neuroptera: Chrysopidae). Additionally, molecular gut‐content analysis via PCR confirmed the predation of S. albicosta by several well‐known biological control agents, including H. convergens, O. insidiosus, C. maculata, and Chrysopidae larvae and adults. Coleomegilla maculata consumed more S. albicosta eggs and larvae than H. convergens in feeding trials, although egg consumption by C. maculata was unaffected by the presence of corn pollen, an important supplemental food for this species. Exploring the trophic interactions between S. albicosta and its predators will provide information necessary to improve conservation biological control for S. albicosta integrated pest 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 | 0.001 | 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".