Efficacy of New Insecticides Against Amrasca biguttula in Odienné Cotton Cultivation
Bibliographic record
Abstract
Amrasca biguttula (Hemiptera: Cicadellidae) is a major pest of cotton in Côte d’Ivoire. It reduces cotton yield despite pesticide spraying. This study carried out to evaluate the efficacy of new insecticides against A. biguttula in Odienné farms. Ten cotton hectares were established for field trials in 2021-2022 and 2022-2023. Each hectare was divided into two equal parts treated with one control insecticide and with one insecticide tested, respectively. A. biguttula adults and cotton yield of each treatment was evaluated. The results showed that JACOBIELLA 350 EC®Pyridine 200 g/L + Diamine 150 g/L, INDOXAN DUO 225 EC®Indoxacarb 125 g/L + Acetamiprid 100 g/L, Zidane 30 W®Flonicamide 30 g/kg, STINGER 500 WG®Flonicamide 500 g/kg, FLASHROLE PLUS 175 O®Flubendiamide 100g/L+ Spirotetramate 75 g/L, NICOMEDE 500 W®Flonicamide 500 g/kg, Tsunamide 280 OD®Flonicamide 200 g/L + Flubendiamide 80 g/L, FLOMID MAX®Flonicamide 250 g/kg + rzth 100 g/kg, CYCLODAN 42%®O,o-dimethyl s-phthalimidomethyl and GARANT 200 WG®Acetamiprid 100 g/L + Lambdacyhalothrin 100 g/L were effective against A. biguttula. Their reduction rate of A. biguttula on cotton plants were higher than 50%. CORONI 672EC®, Dangoro 112EC® and CYPALM P 336EC® reduction rate was lower than 50%. THIAN 175 O-TEQ®, THALIS 112EC®, ATTAKAN 344SC®, EMERIT 112EC® and Coxytrine 672EC® were not effective against A. biguttula. The highest yields were recorded with FLOMID MAX® (1805 kg/ha), CYCLODAN® 12% (1716 kg/ha) and ZIDANE 30W® (982 kg/ha). Flonicamid, pyridine and diamine, indoxacarb and acetamiprid can be used against A. biguttula in cotton crops.
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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".