Photoperiodic Response of in vitro <em>Cannabis sativa </em>Plants
Bibliographic record
Abstract
Most commercial Cannabis sativa L. (cannabis) genotypes are short-day plants and cultivators typically use a 12.0 h uninterrupted dark period to induce flowering; however, scientific information is lacking to prove this is the optimal dark period for all genotypes, and cultivar specific photoperiods may increase productivity. Tissue culture can be used for research requiring multiple treatments, proper replication, and in a controlled environment on a smaller scale compared to greenhouse and indoor facilities. To determine whether cannabis explants can flower under varied photoperiods in vitro, explants were grown under one of six photoperiod treatments: 12.0, 13.2, 13.8, 14.4, 15.0, and 16.0 h for four weeks. The percentage of flowering explants was highest under 12.0 and 13.2 h treatments. There were no treatment effects on the fresh weight, final height, or growth index of the explants. The results suggest an uninterrupted dark period of at least 10.8 h (i.e. 13.2 h photoperiod) is needed to induce the flowering of this genotype. In vitro flowering could provide a unique and high throughput approach to study floral/seed development and secondary metabolism in cannabis under highly controlled conditions. Further research should determine if this response is the same on a whole plant level.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".