Seeding rate and row spacing effect on weed competition, yield and quality of hemp in the Parkland region of Saskatchewan
Bibliographic record
Abstract
Field experiments were conducted on a Black Chernozem silty loam soil at Melfort, Saskatchewan, Canada, from 2000 to 2002, to determine the effect of seeding rate and row spacing on weed competition, as well as on seed, shoot biomass production and seed q uality attributes of industrial hemp ( Cannabis sativa L. ‘Fasamo’ and ‘Finola’). Increasing seeding rate from 20 to 60 or 80 kg ha -1 decreased weed density in all years (average of 33%) and reduced weed size (34%) in 2000. It also increased hemp plant density, biomass and seed yield (average of 174, 23 and 34%, respectively). Seed weight and protein were not affected by seeding rates, but seed oil content increased 1% in one year, when seeding rate increased from 20 to 60 kg ha -1 . Row spacing (18 and 36 cm) had little or no definite effect on most of the parameters studied. Key words: Biomass, cultivar, hemp, protein content, oil content, organic farming, row spacing, seeding rate, weed competition
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".