Rye bread and synthetic bread odorants – effective trap bait and lure for German cockroaches
Bibliographic record
Abstract
Abstract Bread‐in‐beer and bread‐in‐water are prevalent home recipe trap baits for attracting German cockroaches (GCRs), Blattella germanica (L.) (Dictyoptera: Blattellidae), which are significant urban pests. Our objectives were to (1) test the attractiveness of these baits, (2) study the underlying factors of GCR attraction, and (3) determine whether a blend of synthetic bread odorants could replace bread in a trap lure. In large‐arena laboratory experiments with laboratory‐reared GCR males, traps baited with rye bread not only captured eightfold more males than unbaited control traps but also most males released into bioassay arenas. Neither beer nor water enhanced the attractiveness of bread. Bread crust as a bait was more effective than bread crumbs. As Porapak Q headspace volatile extracts of rye bread attracted GCRs, all rye bread odorants in extracts were identified by gas chromatography‐mass spectrometry. Synthetic rye bread odorants and other known bread odorants were then assembled into a master blend. This master blend, and even partial blends lacking certain groups of organic volatiles such as aldehydes and ketones, proved very attractive to GCRs. We conclude that rye bread could be used as an effective bait in retainer traps or, laced with insecticide, as a food source in bait stations. A lure of synthetic bread odorants may eventually replace bread as bait, but the minimum number of essential odorants for that lure has yet to be determined.
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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 | 0.000 | 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".