Effectiveness of Plant Extracts Against Podagrica decolorata and Amrasca biguttula in Abelmoschus esculentus (L.) Cultivation
Bibliographic record
Abstract
Okra cultivation is plagued by pests that affect productivity. Consequently, the use of chemical pesticides causes problems. The present study was conducted to assess the impact of plant extracts of Azadirachta indica, Hyptis suaveolens and Solanum lycopersicum on the abundance of insect pests of the Hiré and Clemson okra varieties. To do this, a factorial block design was set up and foliar applications of these extracts were made, after which the insects were quantified. The extracts significantly reduced the abundance of Podagrica decolorata (p = 0.0009), Amrasca biguttula (p = 0.01), Zonocerus variegatus (p = 0.02) and Jacobiasca lybica (p = 0.009). Chemical treatment was effective on Podagrica decolorata with an average abundance of 40±10.2, followed by hydroetanolic treatment of Hyptis suaveolens (43.3±15.4). On Amrasca biguttula, the hydro-anolic extract of the Azadirachta indica + Solanum lycopersicum combination was effective with an average abundance of 39.7±3.2. On Jacobiasca lybica, the chemical treatment was more effective (18±6.2), followed by the hydroethanolic treatments of Azadirachta indica (27±2.1) and Hyptis suaveolens (29±6.2). The aqueous extract of Hyptis suaveolens considerably reduced the abundance of Zonocerus variegatus (3.7±4.6) after the chemical treatment (3.5±5.7). However, no significant difference was observed between these extracts and the chemical control (p > 0.05). Yields showed a higher average number of fruits (131.83±45.6) in the chemically treated plot, followed by the plot treated with the hydroethanol extract of Hyptis suaveolens and Solanum lycopersicum (128.83±15.2).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".