Effects of Potato Foliage Age and Temperature Regime on Prediapause Colorado Potato Beetle <I>Leptinotarsa decemlineata</I> (Coleoptera: Chrysomelidae)
Bibliographic record
Abstract
Feeding on mature potato foliage and low temperatures can influence diapause preparation and winter survival in insects adapted to northern regions such as the Colorado potato beetle (Leptinotarsa decemlineata Say). The effects of potato leaf maturity and temperature regimen, in a full factorial combination, on prediapause feeding, digging depth in the soil, and survival after a brief exposure to −2°C were studied in beetles induced to diapause under short day conditions in the laboratory. Newly emerged adults were fed either younger or older potato leaves (cultivar Norland) at temperatures cycling daily according to a sine wave averaging 17 or 11.5°C. As expected, time spent feeding before satiation was significantly longer at 11.5°C (25 ± 1.12 [SE] d) than at 17°C (17 ± 0.37 d); leaf age or its interaction with temperature had no significant effect. Beetles consumed older foliage at a faster rate, especially at the 17°C regime. Cumulative fresh weight of older leaves consumed before satiation was 45% higher (3.50 ± 0.07 g/beetle) than young leaves (2.25 ± 0.05 g/beetle); temperature regime and the interaction were nonsignificant. Despite variation in feeding rate and feeding time before satiation, weight gain during prediapause (25–30 mg/individual) remained nearly constant over all factor combinations. Thus, metabolic reserves for overwintering in terms of weight gain are more or less fixed, and any variations in food quality and temperature are compensated for by varying feeding behavior. Satiated prediapause beetles showed no significant variation of postfeeding delay before initiating digging; this delay averaged 8 d under all conditions. Mean depth reached in soil columns before final resting was 30 ± 2.1 cm at 11.5°C compared with 45 ± 2.4 cm at 17°C, with no significant effect of leaf age or interaction. Thus, feeding on older foliage did not affect overwintering depth. Survival after a 4-h cold shock at −2°C, after 6 mo at 4°C, was 59% for beetles under the 17°C regime during prediapause compared with 84% for those under the 11.5°C regime during prediapause. Our results show that a higher temperature regime during prediapause preparation reduces beetle resistance to frost in late dormancy, but beetles dig deeper at high temperatures, which could compensate for the higher risk of freezing.
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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".