Development of a mechanical sexing system to improve the efficacy of an area‐wide sterile insect release programme to control American serpentine leafminer (Diptera: Agromyzidae) in Canadian ornamental greenhouses
Bibliographic record
Abstract
BACKGROUND: American serpentine leafminer (ASL), Liriomyza trifolii (Burgess), is a significant pest of greenhouse ornamental crops, and females damage leaf tissue with their ovipositor during feeding and oviposition. The sterile insect technique has been advocated as a non-chemical alternative to currently available control methods. In area-wide sterile insect release programmes, males act as true vectors of sterility. Females should be eliminated from a cohort of pupae prior to irradiation to maximise production economics and sterility spread. The aim of this research was to develop a mechanical sexing system based on pupal size to reduce the proportion of ASL females. RESULTS: Cumulative frequency distributions were used to examine significant differences in male and female pupal length and dorsal and lateral width distributions. Optimum size cut-off points based on the largest differences in distribution curves were used to determine the dimensions of three different sieve designs. Sieve pores measuring 1.543 mm by 0.765 mm excluded 76% of female pupae and doubled the proportion of males in the throughput sample. CONCLUSION: Pupal sexual dimorphisms identified in this research can be used to design a sieve to aid in reducing the proportion of females prior to irradiation, thus improving the efficacy of an area-wide sterile insect release programme. © 2016 Society of Chemical Industry.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".