Identification of morphologically challenging <i>Delia</i> (Diptera: Anthomyiidae) species from field vegetable crops using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP)
Bibliographic record
Abstract
Abstract Root feeding by the larvae of multiple Delia species can lead to economic loss in many agricultural crops. Field vegetables are subject to infestations by a species complex composed of Delia radicum (Linnaeus) (Diptera: Anthomyiidae), a pest in brassica crops (Brassicaceae), Delia antiqua (Meigen), believed to cause the majority of crop damage in onions, and the generalists Delia florilega (Zetterstedt), Delia platura (Meigen), and Botanophila fugax (Meigen) (Diptera: Anthomyiidae). Correct species identification is necessary to implement field management strategies, but these species are challenging to identify morphologically. We propose a polymerase chain reaction–restriction fragment length polymorphism method as a molecular tool to distinguish between five species of Delia and between two genetic lines of D. platura. The mitochondrial DNA cytochrome c oxidase subunit 1 barcode fragment is targeted, then the polymerase chain reaction product digested with four different restriction enzymes (AccI, BsrI, MlyI, and StyI). The BsrI enzyme distinguishes the two genetic lines of D. platura and D. florilega. The MlyI enzyme identifies B. fugax from the Delia species. Combining BsrI, StyI, AccI, and MlyI into double digestion reactions allows for rapid diagnostics among the species tested. Our method was validated using DNA from specimens collected in eastern Canada. This method provides tools in ecological and environmental studies where these species are of interest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".