Amber LEDs outperform red, blue, and red-blue-amber LEDs for lettuce
Bibliographic record
Abstract
Debate persists on light in controlled environment agriculture.To dissect the effects of conventionally used wavelengths on a crop and provide new information to this expanding food production sector, this study investigated the effects of monochromatic and combined red, blue, and amber light on lettuce growth with increasing light intensities (up to 1300 molm -2 sec -1 ) for 18 days with a 16 hd -1 .Under amber light at PPFDs ranging from 500 to 700 molm -2 sec -1 , fresh mass displayed a 33.3% greater yield when compared to red light at the same PPFD.Suppressed growth was observed with either red or amber alone at high PPFD (>800 molm -2 sec -1 ).Blue light was the least productive of the four treatments, yet lettuce plant growth was not suppressed at high intensities.No growth suppression was observed for lettuce plants grown under combined red-blue-amber light at high intensities, and these plants exhibited greater biomass yield than blue light alone.Varied degrees of pigmentation occurred under each light treatment, yet bleaching was only observed in plants grown under amber light alone at PPFD above 1000 molm -2 sec -1 .Findings present novel plant responses to high intensity light, setting precedence for future experiments aimed at expanding the use of LEDs in horticulture.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".