Filtering Light-Emitting Diodes to Investigate Amber and Red Spectral Effects on Lettuce Growth
Bibliographic record
Abstract
Red and blue light are the principal wavelengths responsible for driving photosynthetic activity, yet amber light (595 nm) has the highest quantum efficiency and amber-rich high pressure sodium lamps result in superior or comparable plant performance. On this basis, we investigated how lettuce plant growth and photosynthetic activity were influenced by broad and narrow light spectra in the 590–630 nm range, by creating amber and red light-emitting diode (LED) spectra that are not commercially available. Four different light spectra were outfitted from existing LEDs using shortpass and notch filters: a double peak spectrum (595 and 655 nm; referred to as 595 + 655-nm light) that excluded 630-nm light, 595-nm, 613-nm, and 633-nm light emitting at an irradiance level of 50 W·m−2 (243–267 µmol·m−2·s−1). Shifting LED wavelengths from 595 nm to 633 nm and from 595 nm to 613 nm resulted in a biomass yield decrease of ~50% and ~80%, respectively. When 630-nm light is blocked, lettuce displayed expanded plant structures and the absence of purple pigmentation. This report presents a new and feasible approach to plant photobiology studies, by removing certain wavelengths to assess and investigate wavelength effect on plant growth and photosynthesis. Findings indicate that amber light is superior to red light for promoting photosynthetic activity and plant productivity, and this could set precedence for future work aimed at maximizing plant productivity in controlled environment agriculture.
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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 | 0.000 | 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) | 0.000 | 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".