Blue versus Red Light Can Promote Elongation Growth Independent of Photoperiod: A Study in Four Brassica Microgreens Species
Bibliographic record
Abstract
An elongated stem has beneficial effects on microgreen production. Previous studies indicate that under 24-hour light-emitting diode (LED) lighting, monochromatic blue light, compared with red light, can promote plant elongation for some species. The objective of this study was to investigate whether shortened photoperiod can change blue vs. red light effects on elongation growth. The growth and morphology traits of arugula ( Brassica eruca , ‘Rocket’), cabbage ( Brassica oleracea , unknown variety name), mustard ( Brassica juncea , ‘Ruby Streaks’), and kale ( Brassica napus , ‘Red Russian’) seedlings were compared during the stage from seeding to cotyledon unfolding under two light quality × two photoperiod treatments: 1) R, monochromatic red light (665 nm) and 2) B, monochromatic blue light (440 nm) using continuous (24-hour light/0-hour dark) or periodic (16-hour light/8-hour dark) LED lighting. A photosynthetic photon flux density of ≈100 μmol·m −2 ·s −1 and an air temperature of ≈22 °C was used for the preceding treatments. After 7 to 8 days of lighting treatment, regardless of photoperiod, B promoted elongation growth compared with R, as demonstrated by a greater stem extension rate, hypocotyl length, or petiole length in the tested microgreen species, except for mustard. The promotion effects on elongation were greater under 24- vs. 16-hour lighting in many cases. Among the tested species, mustard showed the lowest sensitivity in elongation response to B vs. R, which was independent of photoperiod. This suggests that the blue-light-promoted elongation is not specifically from 24-hour lighting, despite the varying promotion degree under different photoperiods or for different species. The elongation growth promoted by blue LED light under a photoperiod of either 24 hours or 16 hours can potentially benefit indoor production of microgreens.
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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".