Effect of Amber (595 nm) Light Supplemented with Narrow Blue (430 nm) Light on Tomato Biomass
Bibliographic record
Abstract
Full-spectrum light-emitting diodes (LEDs) mainly comprising 460-nm + 595-nm light are becoming a mainstay in the horticulture industry, and recent studies indicate that plant productivity under white LEDs is higher than combined blue and red LED lighting. Different light properties (wavelength and bandwidth) in full-spectrum light, particularly for the blue and amber light regions, have only partly been explored. This research aimed to characterize the effects of amber + blue light wavelengths and bandwidths on tomato (Solanum lycopersicum cv. Beefsteak) growth, morphology, and production efficiency. Tomato seedlings were subjected to four different light treatments for 60 days: narrow amber light (595 nm), narrow blue + narrow amber light (430 nm + 595 nm) with a 1:10 ratio, white LED (455 nm + 595 nm), and a high-pressure sodium (HPS) lamp (control). The highest mean fresh mass yield occurred with the narrow blue + narrow amber light (479 g), followed by white LED at 20% less, HPS at 34% less, and narrow amber at 40% less. Dry mass and plant height were similar among light treatments. Supplementing narrow amber light with 430-nm blue light led to a 20% increase in chlorophyll content. Findings indicate that narrow amber light is more efficient in biomass accumulation than broad amber light and that precise selection of different blue and amber wavelengths can greatly impact the growth and development of tomato seedlings. This energy-efficient narrow-wavelength combination shows improvement over white LED lighting for maximizing tomato growth.
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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 | 0.000 |
| 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".