The effect of plant density and photoperiod on flowering time, growth and yield of subtropical hemp (Cannabis sativa L.)
Bibliographic record
Abstract
Industrial hemp (Cannabis sativa L.) production is experiencing a significant increase in worldwide production since regaining popularity in many countries since the 1990's. Currently, production in Australia is very limited, and no major grain or fibre processing facilities yet exist, owing to the lack of suitable low THC (A9-tetrahydrocannibinol) varieties. Hemp production in subtropical regions of Australia is particularly limited as short day lengths (photoperiods) result in early plant maturity, and thus, poor yielding crops. The aim of this research is to determine the viability of a new variety of hemp, bred specifically for subtropical production whilst determining the effects of day length and plant density on yield and flowering time. Trials were conducted in Bundaberg, QLD in 2010-2012 in both field and controlled environment (plastic house) settings. Plant densities of 100, 200, 300 and 400 plants m-2 were compared for fibre production and densities of 50, 80, 100 and 150 plants m2 were compared for grain production to assist in the establishment of appropriate commercial sowing rates. Harvested fibre yields were greatest at 300 plants m2 whereas grain yields were greatest at 150 plants m2, with the potential of even higher yields at densities greater than 150 plants m2. Photoperiod experiments were conducted in a controlled plastic house evaluating plant responses to varying photoperiods. Treatments comparing ambient day length, 13 hour 40 minute fixed photoperiod and 14 hour 40 minute fixed photoperiod determined that a 13 hour 40 minute photoperiod did not significantly prolong vegetative growth compared to natural day lengths in the hemp variety BundyGem but at 14 hours 40 minutes maturity times were significantly delayed, thereby contributing to greater plant height and fibre yield. Previous research also suggests that a critical photoperiod of between 14 and 16 hours is required before flowering is delayed in hemp. This theory was supported by a field experiment whereby successive plantings of BundyGem throughout the spring/summer period of 2011/2012, flowered at the same age despite subtle changes in day length for the growing period (never exceeding 13 hours 40 minutes). This research confirms that subtropical fibre hemp is not yet suitable for subtropical production in Australia with existing varieties due to the limitation of photoperiod on yield. Grain production may still be viable despite early plant maturity with yields comparable with those produced in Europe and Canada.
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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 | 0.001 |
| 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) | 0.028 | 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".