Alternatives to incandescent bulbs in Berlese funnels for detecting stored-product beetles in grain
Bibliographic record
Abstract
We conducted a study to find alternative bulbs to use with Berlese funnels as a replacement for incandescent bulbs following widespread bans on their production and use. To do this, we measured the mean percent-recovery of adults and larvae of common stored-product beetles from 1-kg samples of wheat (12.5–14.5% moisture content) after 6 h using A19-style halogen bulbs and ceramic heat lamps, and compared them to recoveries using incandescent bulbs. We found that the 72W halogen bulb performed similarly to the incandescent bulb for all four species tested. Using this bulb, we recovered, on average, >85% of adult Cryptolestes ferrugineus, Rhyzopertha dominica, and adult and larval Tribolium castaneum, as well as >70% of adult Sitophilus oryzae. Recovery of adult beetles using the heat lamp was similar to the incandescent bulb, but recovery of larval T. castaneum was significantly lower. The 43W and 53W halogens had significantly lower recovery rates compared to the incandescent bulb for adult C. ferrugineus (both bulbs) and adult and larval T. castaneum (43W halogen). Average recovery of larval C. ferrugineus was low for all bulbs (<70%). Grain moisture content did not influence average recovery across species or life stages. We also investigated whether an operating time shorter than 6 h could be used with an alternative bulb, but found that 6 h was still the minimum time required to maximize adult and larval recovery. We recommend using 72W A19 style halogen bulbs in place of incandescent bulbs because they have similar recovery rates as the incandescent bulb, and are cost-effective compared to ceramic heat lamps. However, some systems may not be able to handle the increase in power consumption and so we suggest assessing the system before running a full bank of lights.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".