The use of Telenomus remus (Nixon, 1937) (Hymenoptera: Scelionidae) in the management of Spodoptera spp.: potential, challenges and major benefits
Bibliographic record
Abstract
Abstract Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae), also known as fall armyworm (FAW) is a polyphagous pest which can cause significant losses and is considered a global threat to different crops and a risk to food security. Currently, in maize, the pest is predominantly controlled by pesticides or transgenic events. However, the use of biological control agents is considered the most sustainable and preferred method of control, providing high effectiveness. Among the various natural enemies reported for FAW, the egg parasitoid Telenomus remus has gained most interest, and has been mass released against FAW in the Americas for many years. In addition to FAW, other armyworms of the genus Spodoptera often cause high crop damage and may be controlled using T. remus . Among other important aspects, this paper presents a review on T. remus mass rearing techniques, estimated costs of mass production, and release strategies. Due to the recent invasion of FAW in Africa, Asia, and Australia T. remus provides good opportunities for the establishment of an augmentative biological control program, reinforcing sustainable production of major crops such as maize in affected countries.
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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".