Maximum elongation growth promoted as a shade-avoidance response by blue light is related to deactivated phytochrome: a comparison with red light in four microgreen species
Bibliographic record
Abstract
To clarify detailed patterns of responses to blue light associated with decreasing phytochrome activity, the growth and morphology traits of arugula, cabbage, mustard, and kale microgreens were compared under the treatments: (1) R, pure red light; (2) B, pure blue light; (3) BRF0, (4) BRF2, (5) BRF4, and (6) BRF6: unpure blue lights created by mixing B with low-level (6%) R, and further adding 0, 2, 4, and 6 μmol m −2 s −1 of far-red light, respectively. The calculated phytochrome photostationary state (PPS) value, indicating phytochrome activity, gradually decreased in the order of R (0.89), BRF0 (0.69), BRF2 (0.65), BRF4 (0.63), BRF6 (0.60), and B (0.50). Generally, the elongation growth (including stem extension rate, hypocotyl length, or petiole length) under blue lights increased with the decreasing PPS values, showing the highest and lowest sensitivity for arugula and mustard, respectively. However, the elongation promoted by blue lights gradually became saturated once the PPS values decreased below 0.60, a level which deactivates phytochrome. Other plant traits, such as biomass allocation and plant color, varied with increasing shade-avoidance responses to blue lights with decreasing PPS values relative to R, and these traits reached saturation at a similar PPS value as elongation. The response sensitivity was highest in elongation growth for arugula and cabbage, and highest in plant color for kale and mustard. This suggests that deactivated phytochrome contributes to the maximum elongation promotion as a shade-avoidance response induced by blue light, although the response sensitivity varies with plant traits and species.
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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".