Yield, persistence, and nutritive value of autumn harvested tall fescue
Bibliographic record
Abstract
Tall fescue, harvested or grazed in autumn, may be a potential source of forage but little is known of the effect of a fall harvest or grazing on yield and nutritive value of tall fescue in the mid-north of eastern Canada (˜ 1400 growing degree-days). Three tall fescue cultivars (Courtenay, Kokanee, and Montebello) were submitted to 10 harvest management treatments (two dates of second harvest and five dates of third harvest) over 3 production years in the Saguenay-Lac-St-Jean region (QC). The cultivars Courtenay and Kokanee were more productive and persistent than Montebello. The annual DM yield decreased by an average of 15% between the first and the second production year and by an average of 35% between the first and the third production year; these decreases were greater (22 and 41%, respectively) when the third harvest was taken in early October. Increasing from 28 to 35 d the interval between the first and second harvests increased DM yield of the second harvest by more than 0.5 Mg ha-1, but caused a greater reduction in DM yield of the third harvest, primarily during the first 2 production years. Third-harvest DM yields of more than 4.0 Mg ha-1 were obtained in the first and second production years, while third-harvest DM yields varied from 2.5 to 3.0 Mg ha-1 in the third production year. With the delay of the third harvest in autumn, the concentration of crude protein decreased to 120 g kg-1 DM, the concentration of water-soluble carbohydrates increased to 150 g kg-1 DM, while that of acid detergent fibre changed very little. Tall fescue has a significant yield potential in late summer and early autumn in the mid-north of eastern Canada, primarily in the first 2 production years. However, harvesting or grazing tall fescue in the week preceding or following the first killing frost will reduce persistence and spring regrowth the following year. Key words: Lolium arundinaceum (Schreb.) S. J. Darbyshire, cutting management, cultivars, water-soluble carbohydrates
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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 | 0.000 |
| 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) | 0.001 | 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".