Effect of Soil Temperature and Moisture on Survival of Eggs and First-Instar Larvae of Delia radicum
Bibliographic record
Abstract
Edaphic factors such as soil temperature and moisture influence soil-dwelling insects, whose most vulnerable stages typically are eggs and young larvae. In this study, the survival of eggs and first-instar larvae of the cabbage maggot, Delia radicum L., was measured under laboratory conditions after exposure to a range of soil temperatures and moistures. When eggs were exposed to constant temperature (20-29°C) and humidity (5-200% [wt:wt]), temperature had no significant effect on survival, whereas humidity <25% [wt:wt] caused egg mortality. The gradual exposure of eggs to high temperatures resulted in low mortality below 33°C, but <5% of eggs survived at 40°C. When first-instar larvae were exposed to constant temperature (17-29°C) and humidity (5-100% [wt:wt]), both factors as well as their interaction had a significant effect on larval survival, which was nil at 5% (wt:wt) for all temperatures but increased from 21.9 to 42.8% at 17°C and from 34.1 to 55.0% at 29°C, for soil moisture contents of 15% and 100% (wt:wt), respectively. Eggs of D. radicum are resistant to low soil moisture and high temperature conditions. Larval survival tends to increase with an increase in soil temperature and moisture. It is suggested that soil temperature be integrated into insect development simulation models instead of air temperature, to build more effective models for cabbage maggot management.
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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".