In the light of new greenhouse technologies: 2. Direct effects of artificial lighting on arthropods and integrated pest management in greenhouse crops
Bibliographic record
Abstract
Novel lighting technology offers the possibility of improved arthropod integrated pest management (IPM) in artificially lighted crops. This review compiles the current knowledge on how greenhouse pest and beneficial arthropods are directly affected by light, with the focus on whiteflies. The effect of ultraviolet depletion on orientation and colour-coded phototaxis are to some extent studied and utilised for control of the flying adult stage of some pest species, but far less is known about the visual ecology of commercially used biological control agents and pollinators, and about how light affects arthropod biology in different life stages. Four approaches for utilisation of artificial light in IPM of whiteflies are suggested: (a) use of attractive visual stimuli incorporated into traps for monitoring and direct control, (b) use of visual stimuli that disrupt the host-detection process, (c) radiation with harmful or inhibitory wavelengths to kill or suppress pest populations and (d) use of time cues to manipulate daily rhythms and photoperiodic responses. Knowledge gaps are identified to design a road map for research on IPM in crops lighted with high-pressure sodium lamps, light-emitting diodes (LEDs) and photoselective films. LEDs are concluded to offer possibilities for behavioural manipulation of arthropods, but the extent of such possibilities depends in practice on which wavelength combinations are determined to be optimal for plant production. Furthermore, the direct effects of artificial lighting on IPM must be studied in the context of plant-mediated effects of artificial light on arthropods, as both types of manipulations are possible, particularly with LEDs.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".