DNA Barcoding of Bemisia tabaci Complex (Hemiptera: Aleyrodidae) Reveals Southerly Expansion of the Dominant Whitefly Species on Cotton in Pakistan
Bibliographic record
Abstract
BACKGROUND: Although whiteflies (Bemisia tabaci complex) are an important pest of cotton in Pakistan, its taxonomic diversity is poorly understood. As DNA barcoding is an effective tool for resolving species complexes and analyzing species distributions, we used this approach to analyze genetic diversity in the B. tabaci complex and map the distribution of B. tabaci lineages in cotton growing areas of Pakistan. METHODS/PRINCIPAL FINDINGS: Sequence diversity in the DNA barcode region (mtCOI-5') was examined in 593 whiteflies from Pakistan to determine the number of whitefly species and their distributions in the cotton-growing areas of Punjab and Sindh provinces. These new records were integrated with another 173 barcode sequences for B. tabaci, most from India, to better understand regional whitefly diversity. The Barcode Index Number (BIN) System assigned the 766 sequences to 15 BINs, including nine from Pakistan. Representative specimens of each Pakistan BIN were analyzed for mtCOI-3' to allow their assignment to one of the putative species in the B. tabaci complex recognized on the basis of sequence variation in this gene region. This analysis revealed the presence of Asia II 1, Middle East-Asia Minor 1, Asia 1, Asia II 5, Asia II 7, and a new lineage "Pakistan". The first two taxa were found in both Punjab and Sindh, but Asia 1 was only detected in Sindh, while Asia II 5, Asia II 7 and "Pakistan" were only present in Punjab. The haplotype networks showed that most haplotypes of Asia II 1, a species implicated in transmission of the cotton leaf curl virus, occurred in both India and Pakistan. CONCLUSIONS: DNA barcodes successfully discriminated cryptic species in B. tabaci complex. The dominant haplotypes in the B. tabaci complex were shared by India and Pakistan. Asia II 1 was previously restricted to Punjab, but is now the dominant lineage in southern Sindh; its southward spread may have serious implications for cotton plantations in this region.
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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 | 0.000 | 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".