Yield, herbage composition, and tillering of timothy cultivars under grazing
Bibliographic record
Abstract
Timothy is widely grown for silage and hay in eastern Canada. The relative performance of timothy cultivars under grazing is not, however, well documented. This research determined dry matter production, herbage composition, and tiller characteristics of 34 timothy cultivars under two grazing schedules over 3 yr on the same plots. Several cultivars outyielded the standard cultivar, Farol (7.96 t ha-1), by up to 10% for the 3-yr mean. Richmond and Comtal were the highest-yielding cultivars (8.75 t ha-1) while AC Regal had the best relative yield persistence over the experimental period. Crude protein concentrations of cultivars ranged from 172 to 208 g kg-1 for early and 150 to 179 g kg-1 for late grazing. Neutral detergent fibre (NDF) concentrations ranged from 460 to 495 g kg-1 and concentration of acid detergent fibre (ADF) ranged from 241 to 270 g kg-1 among the cultivars in early grazing. Differences in NDF and ADF concentrations between early and late grazing schedules varied among the cultivars indicating a variable rate of change in fibre concentration. Farol, Timora, Promesse, and Comtal had greater tiller densities than most other cultivars while AC Alliance, Colt, and Winmor had below average tiller densities throughout the grazing season. The ratio between reproductive and vegetative tillers was higher early in the season, than later, but depended on the grazing schedule. The reproductive to vegetative tiller ratios covered a wide range in the third (2–54) and fourth (3–115) grazing periods. We conclude that yield and relative yield persistence of timothy cultivars under grazing varied greatly among cultivars. Tillering density of cultivars also varied but was not significantly related to cultivar performance under grazing. Key words: Timothy, Phleum pratense, grazing, composition, tiller
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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 | 0.000 |
| 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 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".