Bibliographic record
Abstract
A study was conducted in the Peace River region of north-western Canada with three cultivars (Boreal, Jasper, Jasper E) of creeping red fescue (Festuca rubra L. var. rubra) to identify cultivar-specific management practices for seed production. Experimental treatments included four methods of establishment [Broadcast; 30-cm rows; 15-cm rows; 15-cm rows with sulfur (56 kg ha -1 SulFer 0-0-0-95)], 10 nitrogen (N as 34-0-0) fertilizer treatments, and three methods of post-harvest management prior to winter (flail mowing and residue removal; disc mowing and residue removal; short-duration, intensive grazing with sheep) plus crop residue removal at seed harvest. Total seed yield over 2 consecutive production years was greatest with 30-cm rows although a higher first-year yield was realized with 15-cm rows. In the first production year, establishment in rows produced higher seed yield than broadcasting but, in the second, the converse was true. Within-row supplementation with sulfur decreased the total seed yield over 2 yr by 7%. In the first, second and combined production years, Boreal produced 655, 372 and 1027 kg ha -1 , respectively; for the corresponding production years, Jasper produced 56, 65 and 60% of Boreal, while Jasper E produced 58, 76 and 65% of Boreal. The endophyte (Neotyphodium spp. Glenn, Bacon, Price & Hanlin and Epichloe festucae Leuchtm., Schardl, & Siegel) infection of Jasper E had no consistent beneficial or detrimental effects on seed yield. For the year subsequent to the application of the post-harvest treatments, the effects of flail and disc mowing were similar (360 versus 347 kg ha -1 seed, respectively), whereas grazing reduced seed yield to 188 kg ha -1 . Splitting the application of N in fall and spring resulted in similar seed yields to fall-only N. The response to N fertilizer differed for consecutive years of production; in the first production year, seed yield increased linearly over the range 38–114 kg ha -1 N, whereas in the second production year, rates in excess of 76 kg ha -1 N markedly suppressed seed yield. A fall application of 55–80 kg ha -1 N in the establishment year, and again after the seed harvest of the first production year, was sufficient to maximize the total seed yield over 2 consecutive production years. Cultivar-specific responses in seed yield to treatment interactions were too small for agronomic exploitation. Key words: Creeping red fescue, Festuca rubra, grass seed production, cultivar-specific management, establishment method, nitrogen fertility, post-harvest management
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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 | 0.000 |
| 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 | 0.000 | 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".