The effects of LED daylength extensions on the fecundity of the pest aphid <i>Myzus persicae</i> and the daily activity patterns of its parasitoid, <i>Aphidius matricariae</i>
Bibliographic record
Abstract
Abstract Supplemental lighting, such as with LED lamps, allows greenhouse producers to maintain yields when natural light levels are low. Since both insect pests and their natural enemies are sensitive to light, both the duration and spectrum of LED daylength extensions could affect biological pest control in greenhouses. Longer days could allow for extended periods of reproduction for pests or foraging activity of biological control agents, possibly depending on the spectra used for these extensions. However, the effects of lengthening days with different LED spectra on the behaviour of biological control agents has mostly been studied in short-term experiments to date, and has not always included the context of the light’s effect on their hosts’ reproduction. In growth chambers, we examined the locomotor activity of the parasitoid biocontrol agent Aphidius matricariae (Hymenoptera : Braconidae) as a predictor for foraging activity and the fecundity of its aphid host Myzus persicae (Hemiptera : Aphididae) over multiple days under different daylength extension regimes representative of those used in greenhouse vegetable production. We compared the effects of 14, 16, 18, and 20 h photoperiods, and 12 h days extended by 6 h with three different spectral qualities. The parasitoids adjusted how their activity was distributed throughout the lit period of the day (i.e., its total duration and peak timing) without changing the total amount of daily activity, regardless of the photoperiod or the light spectrum used for daylength extension. The aphids’ peak fecundity was not affected by photoperiod or spectral quality. Our results suggest that at least some behavioral and reproductive traits of these insects can be resilient to even drastic changes in their light environment.
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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".