N, P, and S fertilization effects on industrial hemp in Saskatchewan
Bibliographic record
Abstract
Industrial hemp (Cannabis sativa L.) has become a well-known crop in western Canada in recent years, but insufficient information is available on its nutrient requirements for optimum yield. Our objective was to confirm the response of two hemp cultivars to increasing levels of nitrogen (N), phosphorus (P) and sulphur (S) in various sites in the province of Saskatchewan, during 2006-2008. Increasing N rates significantly increased plant height, biomass, and seed yield, when data were averaged across all sites (location-years), reaching maximum values at about 150 kg N ha-1 of applied N fertilizer. The cultivar Crag was taller and produced greater biomass than the cultivar Finola over all levels of N fertilizer rate. The minimum rate of N fertilizer to achieve maximum height/biomass for Crag, relative to Finola, was 5 kg N ha-1 lower for height (Finola: 163 kg N ha-1) but 9 kg N ha-1 higher for biomass (Finola: 180 kg N ha-1). Finola seed yield was more responsive to progressively greater rates of N fertilizer. Consequently, maximum seed yield (plateau) was 27% greater for Finola than for Crag, but 198 kg N ha-1 of fertilizer was required to achieve this maximum yield vs. 175 kg N ha-1 for Crag. There was generally little or no response to P fertilizer, on soils with adequate available P, or to S fertilizer on an S-deficient soil. Results from this study indicate that N fertilizer rate and cultivar choice are important management parameters to consider for industrial hemp production.Key words: Fertilizer, hemp cultivars, nitrogen, phosphorus, sulphur, soil extractable P, soil nitrate-N
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".