The Influence of Ultraviolet-A on Indicators of Plant Stress in Cannabis Sativa
Bibliographic record
Abstract
The economic value of Cannabis sativa is influenced by inflorescence quality. Exposure to ultraviolet light (UV) has been shown to increase concentrations of Δ9-tetrahydrocannabinolic acid in drug-type plants. High doses of UV-B are physiologically damaging and this damage is theorized to be repaired photo-enzymatically, through exposure to white light or UV-A light. I assessed chlorophyll content, stomatal conductance, sexual lability, vegetative biomass, floral biomass, Δ9-tetrahydrocannabinol and cannabidiol content in C. sativa using light emitting diodes (LED) receiving 4h of UV-B alone or with 6h UV-A daily for five weeks. Significant (or interactive) effects of UV-A were not detected for any trait measured. However, plants exposed to UV-A+B showed a negative correlation between stomatal size and density, not seen under UV-B, suggesting UV-A impacts stomatal physiology. Results suggest a limited impact of UV-A exposure when white light is sufficient. Alternatively, further environmental variables may have obscured any effects from UV-A exposure. Keywords:
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".