Population Structure and Genetic Diversity of the Pepper Weevil (Coleoptera: Curculionidae) Using the COI Barcoding Region
Bibliographic record
Abstract
The pepper weevil Anthonomus eugenii Cano (Coleoptera: Curculionidae) is a pest of economic importance for Capsicum species pepper in North America that attacks the reproductive structures of the plant. The insect is distributed across Mexico, the United States, and the Caribbean, and is occasionally found during the pepper growing season in southern Ontario, Canada. Continuous spread of the insect to new areas is partially the result of global pepper trade. Here, we describe the genetic diversity of the pepper weevil using the mitochondrial COI barcoding region across most of its geographic range. In this study, 44 (H1-H44) highly similar haplotypes were identified, the greatest number of haplotypes and haplotype diversity were observed among specimens from its native Mexico, followed by specimens from the United States. Unlike Mexico, a low haplotype diversity was found among specimens from Canada, the Dominican Republic, Italy, and the Netherlands. Out of these 44 haplotypes, 29 are reported for the first time. Haplotype diversity in the Canadian population suggests either multiple and continuous introductions of the pepper weevil into this area or a single introduction of genetically diverse individuals. We discuss the importance of such population genetic data in tailoring pepper weevil management programs, using Canada as an example.
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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 | 0.001 |
| 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".