Effects of Different Light Spectra and Intensities on Stomatal Function in Lettuce and Basil
Bibliographic record
Abstract
Abstract Light quality and intensity markedly influence stomatal activity, a crucial physiological process regulating gas exchange and water loss in higher plants. Stomata dynamically open and close in response to environmental signals, facilitating carbon dioxide uptake for photosynthesis while modulating transpirational water loss. Although red and blue light are well-established regulators of stomatal function, the effect of green light on this process remains comparatively underexplored. In this study, the effects of multiple light wavelengths (430 nm, 530 nm, 560 nm, and 630 nm) and intensities (50, 75, 100, and 400 µmol·m −2 ·s −1 ) on stomatal responses in lettuce ( Lactuca sativa ) and basil ( Ocimum basilicum ) were systematically evaluated. The results showed that green light (530 nm and 560 nm) effectively maintained stomatal closure at lower intensities, thereby minimizing water loss and preserving tissue freshness during postharvest storage. These findings highlight the potential application of green light to optimize postharvest handling by reducing transpiration and improving shelf life of leafy crops. This evidence provides a foundation for targeted light management strategies aimed at improving the commercial quality and marketability of horticultural produce.
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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 | 0.001 |
| 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".