Flight Take-Off Performance of Colorado Potato Beetle in Relation to Potato Phenology
Bibliographic record
Abstract
The flight take-off frequency of adult Colorado potato beetles, Leptinotarsa decemlineata (Say), from potato plants, Solanum tuberosum L. 'Red Pontiac' at the bloom stage of development was 2.2-2.5-fold that of Colorado potato beetle from plants at the vegetative stage. Tests were conducted in a flight chamber over a period of 3 h. Prefeeding Colorado potato beetles for 48 h on potato plants at the bloom or at the vegetative stage before placing them into the flight chamber resulted in the same significantly higher flight take-off frequency from potato plants at the bloom stage than from plants at the vegetative stage. These results demonstrate that the factor in potato plants in bloom that stimulates the flight take-off of the Colorado potato beetle is independent of the feeding history of the beetles and begins acting only when the beetles are in the presence of the plant. According to these results, the dispersal of adult Colorado potato beetles from potato fields in bloom to younger potato fields with plants at the vegetative stage, previously reported in the literature, is at least partly explained by the effect of plant phenology on the frequency of flight take-off. Results confirm the value of planting potato fields of similar phenology over as wide an area as possible to reduce Colorado potato beetle dispersal between fields. Results also imply that staggering the planting dates of conventional potato refuge areas near Colorado potato beetle transgenic or conventionally resistant potato fields is a sound management practice, because it promotes the movement of wild beetles over to the adjacent younger resistant crops.
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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".