Growth and morphological responses of gerbera seedlings to narrow-band lights with different light spectral combinations as sole-source lighting in a controlled environment
Bibliographic record
Abstract
To optimize light-emitting diode (LED) spectral recipes for gerbera (Gerbera jamesonii) seedling propagation, seed germination and seedling morphology, biomass, flowering, and storage quality were observed in four cultivars, ‘Midi Dark Purple’, ‘Majorette Red Dark Eye’, ‘Maxi Pink’, and ‘Maxi White’, under six spectrum treatments: (1) FL, cool white fluorescent light; (2) RB, a photon flux ratio of 85% red and 15% blue (RB-LED); (3) RB + UVB, RB-LED combined with 0.5 μmol·m −2 ·s −1 of ultraviolet-B; (4) RB + UVA, RB-LED combined with 9.6 μmol·m −2 ·s −1 of ultraviolet-A; (5) RB + G, a photon flux ratio of 60% red, 15% blue, and 25% green; (6) RB + FR, RB-LED combined with 17.3 μmol·m −2 ·s −1 of far-red. For all treatments, the photosynthetic photon flux density was 165 μmol·m −2 ·s −1 under a 16-h photoperiod. Seedling growth and morphology were similar under FL and RB for all cultivars, except for a wider canopy of ‘Majorette Red Dark Eye’ under RB. Each of the tri-chromatic light treatments (i.e., RB + UVB, RB + UVA, RB + G or RB + FR) showed similar effects as RB, except for thicker ‘Maxi Pink’ stems under RB + FR. Furthermore, the quality index, an integrated evaluation of seedling quality, was similar under all the treatments for each cultivar. Given the similar seedling quality and the advantages of LEDs, RB-LED can potentially replace FL for controlled-environment gerbera seedling production, but the tri-chromatic lights tested in this study appear to be unnecessary.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".