Effect of Biopesticides Against Sucking Insect Pests of Brinjal Crop Under Field Conditions
Bibliographic record
Abstract
A field study was carried out during 2013 at the experimental area of Entomology Section, Agriculture Research Institute, (ARI) Tando Jam to examine the effect of bio-pesticides against sucking insect pests of brinjal crop under field conditions. Five treatments with three replications were applied. The treatments were: T1=chemical control (confidor/Diamond), T2=Neem (Azadirachta indica), T3= Tobacco (Nicotiana tabacum), T4= Eucalyptus (Eucalyptus globus), T5= Untreated (Control). Three insect pests were found infesting brinjal including white flies, jassid and mites. Pre treatment- and post-treatment observations were recorded. The results revealed that against white fly, the first spray of chemical control(confidor) showed highest reduction percent (96.62%) followed by Neem extract (82.60%), Tobacco extract (75.95%), Eucalyptus extract (73.93%) and lowest for untreated control (11.07%); while in the second spray also, chemical control(Diamond) showed highest effect against white fly (78.32%); followed by Neem extract (67.53%), Tobacco extract (56.43%), Eucalyptus extract (42.25%) and least by untreated plot (5.49%). Against jassid, chemical control (confidor) showed highest effect (77.90%) as observed during 1st spray, followed by Neem extract (55.95%), Tobacco extract (53.38%), Eucalyptus extract (53.99%) and untreated control (8.00%), while after second spray also chemical control (Diamond) showed highest reduction percent (81.70%) followed by Neem extract (68.73%), Tobacco extract (55.72%), Eucalyptus extract (50.66%) and the lowest was resulted by untreated control (13.91%). Against mites population on brinjal the first spray results showed that chemical control (confidor) showed highest effect (98.19%) followed by Neem extract (96.19%), Tobacco extract (95.75%), Eucalyptus extract (86.86%) and least population was recorded in untreated control (9.96%). After second spray, chemical control (Diamond) showed highest reduction percent (99.65%), followed by Neem extract (98.33%), Tobacco extract (92.85%), Eucalyptus extract (88.93%) and the lowest reduction percent was resulted by untreated control (9.14%) respectively. Chemical control (confidor/Diamond) showed its superiority in effect to combat sucking insect pests studied in brinjal, followed by Neem extract, Tobacco extract, Eucalyptus extract and untreated control remained the least.
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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) | 0.001 | 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 | 0.001 |
| 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".