Distinguishing Between Laboratory-Reared and Greenhouse- and Field-Collected <i>Trichoplusia Ni</i> (Lepidoptera: Noctuidae) Using the Amplified Fragment Length Polymorphism Method
Bibliographic record
Abstract
Abstract Frequent use of the microbial insecticide, Bacillus thuringiensis kurstaki (Berliner) (Bt), in commercial vegetable greenhouses has led to the evolution of resistance in cabbage looper, Trichoplusia ni (Hübner) (Lepidoptera: Noctuidae), populations. Spatial patterns of Bt resistance suggest that resistant moths disperse from greenhouses selected with Bt to neighboring untreated greenhouses. To quantify dispersal patterns in greenhouse and field populations, molecular markers are desired. We developed a DNA isolation procedure and evaluated the utility of the molecular fingerprinting technique, amplified fragment length polymorphism (AFLP), to analyze the possible population structure of T. ni by using laboratory-reared populations. We also assessed the ability of AFLP markers to distinguish between laboratory and wild T. ni populations collected from a greenhouse and field in the Fraser Valley of British Columbia, Canada. Due to the complexity of the T. ni genome, primer combinations of E+3 and M+4 were required to unambiguously score polymorphic loci. Three of the primer combinations that were examined produced >65 polymorphic bands in laboratory-reared populations, and >90 bands in greenhouse- and field-collected populations. Levels of heterozygosity were higher in wild populations compared with those reared in the laboratory, and AFLP markers reliably distinguished between laboratory and wild populations.
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 | 0.001 |
| 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".