Effectiveness of an oil-based <i>Beauveria bassiana</i> formulation for controlling the neotropical brown stink bug, <i>Euschistus heros</i> (Heteroptera: Pentatomidae) on soybean crops
Bibliographic record
Abstract
Abstract The fungus Beauveria bassiana (Unioeste 76) was tested against the soybean pest Euschistus heros in laboratory, greenhouse, and field. In the laboratory, insects were sprayed with pure conidia (TC) suspended in distilled water or in an oil dispersion formulation (OD; vegetable oil) at a concentration of 10 9 conidia/mL. The UV-B radiation and heat tolerance of the conidia were also assessed. After 12 days, the mortality rates in the laboratory were 70% for the TC treatment and 80% for the OD treatment. In the greenhouse pre-infestation bioassay, which used soybean plants in cages, the fungal treatments resulted in 52% and 47% mortality for the TC and OD formulations, respectively. In the post-infestation bioassay, both fungal treatments caused 83% mortality. In the field trial conducted on soybean plots (14 × 18 m), the treatments included: (i) biological: OD (10 9 conidia/mL); (ii) chemical insecticide; (iii) biological + chemical, all applied at 150 L/ha. Insect numbers were evaluated using beating-sheet sampling. In the final population sample, the biological treatment showed a population density similar to the chemical treatment (0.94 and 0.83 insects/m, respectively), both below the economic threshold. Conidia tolerance to UV-B radiation was similar across both treatments, but conidia in oil were less tolerant to heat. These results suggest that strategically combining both approaches ( B. bassiana with chemical insecticides), with careful consideration of application intervals, could provide a sustainable and effective method for managing natural populations of E. heros .
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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".