Monitoring of insecticide resistance in Bemisia tabaci populations collected from selected regions of the Punjab, Pakistan
Bibliographic record
Abstract
Whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), is a notorious sucking insect pest of cotton and many other crops worldwide. It acts as a vector of various diseases and responsible for causing destruction to economy by damaging major crops. In order to determine, the resistance ratio and efficacy of insecticides against whitefly, field populations of B. tabaci were collected from four districts (Multan, Bahawalpur, Jhang and Toba Tek Singh) of Punjab, Pakistan, during 2020 to 2022. After collection, leaf-dip bioassay method was used to measure resistance level in whitefly populations by insecticides (spirotetramat, buprofezin, pyriproxyfen, diafenthiuron, and bifenthrin). The results showed that B. tabaci developed high to very high resistance against buprofezin (97.26-108.41 fold), high resistance level against bifenthrin (70.65-95.30 fold), moderate to high resistance against pyriproxyfen (35.68-80.46 fold), moderate level of resistance against diafenthiuron (20.72- 30.77 fold), low level of resistance against spirotetramat (11.66-18.60 fold), while comparing with susceptible population. The results of present study i.e., spirotetramat and diafenthiuron may be used as wise choices regarding the selection of insecticides against B. tabaci and delay insecticide resistance
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".