Light emitting diode effect of red, blue, and amber light on photosynthesis and plant growth parameters
Bibliographic record
Abstract
The visible light spectrum (400-700 nm) powers plant photosynthesis and innumerable other biological processes. Photosynthesis curves plotted by pioneering photobiologists show that amber light (590-620 nm) induces the highest photosynthetic rates in this spectrum. Yet, both red and blue light are viewed superior in their influence over plant growth. Here we report two approaches for quantifying how light wavelength photosynthesis and plant growth using light emitting diodes (LEDs). Resolved quantum yield spectra of tomato and lettuce plants resemble those acquired earlier, showing high quantum utilization efficiencies in the 420-430 nm and 590-620 nm regions. Tomato plants grown under blue (445 nm), amber (595 nm), red (635 nm), and combined red-blue-amber light for 14 days show that amber light yields higher fresh and dry mass, by at least 20%. Principle component analysis shows that amber light has a more pronounced and direct effect on fresh mass, whereas red light has a major effect on dry mass. These data clarify amber light's primary role in photosynthesis and suggest that bandwidth determines plant growth and productivity under sole amber lighting. Findings set precedence for future work aimed at maximizing plant productivity, with widespread implications for controlled environment agriculture.
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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) | 0.002 | 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".