Study of the beneficial effects of green light on lettuce grown under short‐term continuous red and blue light‐emitting diodes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Red and blue light are the most important light spectra for driving photosynthesis to produce adequate crop yield. It is also believed that green light may contribute to adaptations to growth. However, the effects of green light, which can trigger specific and necessary responses of plant growth, have been underestimated in the past. In this study, lettuce ( Lactuca sativa L.) was exposed to different continuous light (CL) conditions for 48 h by a combination of red and blue light‐emitting diodes (LEDs) supplemented with or without green LEDs, in an environmental‐controlled growth chamber. Green light supplementation enhanced photosynthetic capacity by increasing net photosynthetic rates, maximal photochemical efficiency, electron transport for carbon fixation (J PSII ) and chlorophyll content in plants under the CL treatment. Green light decreased malondialdehyde and H 2 O 2 accumulation by increasing the activities of superoxide dismutase (EC 1.15.1.1) and ascorbate peroxidase (EC 1.11.1.11) after 24 h of CL. Supplemental green light significantly increased the expression of photosynthetic genes LHCb and Psb A from 6 to 12 h, and these gene expressions were maintained at higher levels than those under other light conditions between 12 and 24 h. However, a notable downregulation of both LHCb and Psb A was observed during 24 to 48 h. These results indicate that the effects of green light on lettuce plant growth, via enhancing activity of particular components of antioxidative enzyme system and promoting of LHCb and Psb A expression to maintain higher photosynthetic capacity, alleviated a number of the negative effects caused by CL.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it