Effect of Food Attractants and Insecticide Toxicity for the Control of Spodoptera frugiperda (Lepidoptera: Noctuidae) Adults
Bibliographic record
Abstract
An alternative for the population suppression of Spodoptera frugiperda is the use of toxic baits. The objective of this study was to evaluate the dietary preference and toxic effect of insecticides associated with the attractiveness of S. frugiperda adults as a pest management method. The following attractions were tested: 1) 5% sucrose solution, 2) 10% sugarcane syrup, 3) 10% honey, 4) 5% hydrolyzed protein, 5) Noctovi® 43sb, 6) Noctovi® OVI PLU 1-3, 7) Noctovi® OVI PHE/PAL 50-50 in the study with choice. Attractions: 1) sugarcane syrup 10%, 2) Noctovi® 43sb, 3) Noctovi® 43sb + sugarcane syrup 10%, 4) Noctovi® OVI PLU 1-3 in the study with no chance of choice. For the toxicity study, the food attraction associated with insecticides was used: methomyl 2%, lambda-cyhalothrin 1%, chlorpyriphos 2%, spinosad 1%, chlorantraniliprole 2% and chlorfenapyr 2%. The experimental design was the completely randomized design (CRD) with chance of choice, without chance of choice and toxicity. The following parameters were evaluated: number of insects that fed; time in minutes that remained in the attractive food and mortality. The molasses (10%) and Noctovi® 43sb food attractiveness were significantly more efficient in relation to feeding time and the highest number of landings was observed in the Noctovi® 43sb treatment, both in females and total adults. Methomyl, lambda-cyhalothrin and spinosad insecticides associated with food attractiveness are promising toxic baits for the management of S. frugiperda.
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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".