Mineral nutrition for Cannabis sativa in the vegetative stage using response surface analysis
Bibliographic record
Abstract
Cannabis cultivated for medical and adult use is a high-value horticultural crop in North America; however, we lack information on its optimal mineral nutrition due to previous legal restrictions. This study evaluated the mineral requirements of nitrogen (N), phosphorus (P), and potassium (K) for cannabis in the vegetative stage using response surface analysis. Plants were cultivated in a hydroponic system with various nutrient solution treatments (mg L -1 ) of N (132.7, 160, 200, 240, and 267.3), P (9.6, 30, 60, 90, and 110.5), and K (20.8, 60, 117.5, 175, and 214.2) according to a central composite design. Nutrient interactions (N × K, K × P, and N × P × K) had a significant effect on the vegetative growth of the cannabis plants. N × K interaction had a significant effect on leaf mass and stem mass. K × P interaction had a significant effect on dry root mass, leaf mass, stem mass, leaf area, specific leaf area, and chlorophyll a and b contents. N × P × K interaction had a significant effect on root mass, leaf mass, stem mass, stem diameter, leaf area, and chlorophyll a and b contents. The optimum concentrations of total nitrogen, P, K, calcium, and sulfur in the cannabis leaves were 0.54, 0.073, 0.27, 0.56, and 0.38 mg g -1 , respectively. An increase in P and K concentrations decreased the magnesium concentration in the leaves, but it was unaffected by the increase in N concentration. The recommended primary macronutrients for cannabis plants in the vegetative stage based on the maximum desirability and nutrient use efficiencies were 160–200 mg L -1 N, 30 mg L -1 P, and 60 mg L -1 K. These findings can offer valuable insight and guidance to growers regarding the mineral requirements for cannabis during the vegetative stage.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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".