Floral Reversion based micropropagation of Day-Neutral <i>Cannabis sativa</i> L
Bibliographic record
Abstract
Abstract Micropropagation systems have been developed for photoperiod sensitive cultivars of cannabis, but there are currently no published methods for day-neutral genotypes. Most established cannabis micropropagation systems rely on shoot proliferation using modal explants that need them to be maintained in vegetative growth, which is not possible for day-neutral genotypes. Floral reversion, the process by which plants revert to vegetative growth from the generative stage, has been demonstrated as an alternative and potentially more efficient approach to the micropropagation of photoperiodic cannabis. The current study investigated if this process could be adapted to facilitate the micropropagation of day-neutral genotypes and overcome existing barriers. During the process, various factors such as photoperiod and light intensity may influence the efficiency of floral reversion. To evaluate this approach in day-neutral cultivars, various photoperiods were compared to assess the impact on reversion rate and subsequent growth. Excised florets obtained from in vitro day-neutral C. sativa cv. “Blue Auto Mazar x auto Blueberry” seedlings were subjected to five photoperiods including 12.0, 16.0, 18.0, 20.0, and 24.0 hours of light per day for four weeks. Reversion rates and time, shoot length, shoot number, and node number were measured. Statistical analyses revealed significant differences (p-values < 0.05) in terms of reversion time among photoperiod treatments. The highest reversion rate happened under the 16.0 hr photoperiod with 72% success. The highest shoot lengths were observed under 20.0 hr of photoperiods with a mean of 10.1 mm and the lowest shoot length belonged to 12.0 hr of photoperiods with a mean of 5.6 mm, respectively. Reverted shoots developed vegetatively for some time before initiating new flowers. However, during this period the shoots were successfully rooted in vitro and then acclimated to the growth chamber where they completed their life cycle, including seed production. This process was also successfully achieved from a 2-year old culture of C. sativa cv. “Blue Auto Mazar”, demonstrating that it is feasible to use this approach for long term culture maintenance and multiplication. This study demonstrates that floral reversion can successfully be used to clonally propagate day-neutral cannabis plants and serves as a basis for developing large-scale clonal propagation and breeding strategies.
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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) | 0.001 | 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".