Is Twelve Hours Really the Optimum Photoperiod for Promoting Flowering in Indoor-Grown Cultivars of Cannabis sativa?
Bibliographic record
Abstract
Cannabis sativa (“cannabis” hereafter) is a valuable recent addition to Canada’s economy with the legalization for recreational use in 2018. The vast majority of indoor cannabis cultivators use a 12-h light/12-h dark photoperiod to promote flowering. To test the hypothesis that robust flowering initiation responses can be promoted in indoor-grown cannabis cultivars under longer photoperiods, clones of ten drug-type cannabis cultivars were grown under six photoperiod treatments. All treatments were based on a standard 24-h day and included 12 h, 12.5 h, 13 h, 13.5 h, 14 h, and 15 h of light. The plants were grown in a growth chamber for 3 to 4 weeks, receiving an approximate light intensity of 360 µmol·m−2·s−1 from white LEDs. Flowering initiation, defined as the appearance of ≥3 pairs of stigmas at the apex of the primary shoot, occurred in all cultivars under all photoperiod treatments up to 14 h. Delays in flowering initiation time under 14 h vs. 12 h ranged from no delay to approximately 4 days, depending on the cultivar. Some cultivars also initiated flowering under 15 h, but floral tissues did not further develop beyond the initiation phase. Harvest metrics of some cultivars responded quadratically with increasing photoperiod, with ideal levels of key flowering parameters varying between 12 h and 13 h. These results suggest there is potential to increase yield in some indoor-grown cannabis cultivars by using longer than 12-h photoperiods during the flowering stage of production. This is attributed to the inherently higher daily light integrals. Indoor cannabis growers should investigate the photoperiod responses of their individual cultivars to determine the optimal photoperiod for producing floral biomass.
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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 | 0.001 | 0.001 |
| 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".