Colored Shade Nets and LED Lights at Different Wavelengths Increase the Production and Quality of Canada Goldenrod (Solidago canadensis L.) Flower Stems
Bibliographic record
Abstract
L.), a short-day plant commonly cultivated as a cut flower, depends on proper lighting management to obtain long stems and higher commercial value. Thus, this study aimed to determine the effect of modifying the light spectrum through the installation of light-emitting diodes (LEDs) and the use of colored shade nets on the production and quality of Canada goldenrod stems. The treatments used were colored shade nets and different LED lighting treatments. Production per plant and productivity per square meter were determined. Twenty stems were selected and evaluated for: stem length; inflorescence length and width; number of floral ramets per inflorescence; number of leaves; stem base diameter (mm); and fresh stem biomass (g). Canada goldenrod plants require an extension of the light period with artificial lighting to produce higher-quality stems, regardless of whether the bulbs emit red or white light. The use of nets with 50% red and white shading promoted higher production and elongation of Canada goldenrod stems, with a production that reached up to 4.2 floral stems per plant and 100.3 floral stems per square meter using the red shade net and white LED. These floral stems were of high commercial standard, with a length of up to 81.35 cm with the red shade net and red LED, and were 31 cm in diameter for the inflorescences, approximately, under black or white shade nets and white or red LEDs. More robust floral stems with greater biomass were observed using any shade net color and LED lamps.
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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".