Efficacy of Synthetic Pesticides Against Thrips, Thrips tabaci Lindeman (Thysanoptera: Thripidae) on Okra Abelmoschus esculentus (L.) Moench
Bibliographic record
Abstract
Okra (Abelmoschus esculentus L.) is an essential vegetable crop with good nutritional significance. Insect pests are the major threat for poor production of the okra crop. Thrips of vegetable crops are known to be serious pests on a wide range of fruit, vegetable, flower, and agronomic crops. The present field study was carried out to know the efficacy of different insecticides (acetamiprid 19% weightable water (ww), lambda 25% ww, colarphipare 32% ww, lambda 2.5% ww and abamectin 1.3% ww) against Thrips, Thrips tabaci (Lindeman) on okra crop during the year 2019, and observations against T. tabaci (Lindeman) were recorded after 24 hrs, 48 hrs, 72 hrs and 07 days of each spray in all the treatments. The pre-treatment count of thrips on okra was non-significant (P > 0.05); while the evaluated efficacy of different insecticides against thrips was significant (P < 0.01). It was noted that all the insecticides showed their highest efficacy after 7 days of spray and acetamiprid 19% weightable water (ww) was more efficient to combat the T. tabaci as compared to other pesticides that produced field efficacy of 73.92 and 74.91% against thrips after 7 days of 1st and 2nd spray respectively. Abamectin, 1.3% ww, was reasonably successful, yielding 53.81 and 56.66% field efficacy against T. tabaci (Lindeman) after 7 days of first and second spray. Also, moderately effective was colarphipare 32% ww, which developed field effectiveness of 56.41 and 61.49% against T. tabaci (Lindeman) after 7 days of first and second spray, respectively.
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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".