Effect of amber and low-pressure sodium lights supplemented with blue light on lettuce ( <i>Lactuca sativa</i> ) production
Bibliographic record
Abstract
As food security concerns and controlled environment agriculture continue to grow, a comprehensive understanding of the influence of light on vegetable cultivation is needed. This study compared the performance of broad amber (595 nm) lamps to low-pressure sodium lamps (589 nm) and evaluated whether the addition of blue (450 and 473 nm) light improved plant growth. The low-pressure sodium lamp performed similarly to amber in terms of vegetative growth. Results showed that lettuce grown under low-pressure sodium lamps exhibited yellowing of leaves, which was not observed under amber light. The addition of blue light significantly (p < .05) reduced the fresh mass and dry mass of plants treated with low-pressure sodium lamps by 21.5% and 16.6%, respectively. For plants treated with amber light, the addition of blue light at light intensities below 170 μmol m−2 s−1 significantly (p < .05) increased both fresh mass and dry mass, although decreased by 30.4% and 19.5%, respectively, above 170 μmol m−2 s−1. Data presented herein show that the addition of blue LEDs significantly increased the chlorophyll concentration by 24.4% and 33.1% for low-pressure sodium lamps and amber light, respectively (p < .05).
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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".