Potential of Stockpiled Annual and Perennial Forage Species for Fall and Winter Grazing in the Canadian Great Plains Region
Bibliographic record
Abstract
The practice of stockpiling forage for the fall and winter has become a popular feeding strategy used to extend the grazing season and maintain profitability of beef operation in the Canadian Great Plains Region. This thesis research was conducted in the field to determine the potential of perennial and annual species with the major focus on stockpiled forage dry matter yield and late fall forage quality. Five cultivars from four grass species and three cultivars from two legume species were seeded using grass-legume binary mixture or monocultures for the perennial forage trial, and managed under two different stockpile initiation treatments. Five cool-season and two warm-season species were selected for an annual forage stockpiling trial. Cool-season perennial stands yielded higher but had lower quality in a relatively dry and cool growing season compared with the stands that experienced a warm and wet summer. Early stockpile initiation resulted in longer accumulation period and significantly higher (P < 0.05) regrowth yield compared with late stockpile initiation. Stockpiled dry matter yield ranged from 1.5 to 3.6 Mg ha-1 with meadow brome [(Bromus riparius Rehm.) cv. Fleet], mixed with alfalfa [(Medicago sativa L.) cv. Algonquin] having the highest production. Meadow brome and tall fescue (Festuca arundinacea Schreb.) in mixed stands with legumes had significantly higher production than pure stands of cicer milkvetch (Astragalus Cicer L.) and orchardgrass (Dactylis glomerata L.) as well as mixed stands of hybrid brome [(Bromus inermis Leyss. x Bromus riparius Rehm.) cv. Success (S)] and cicer milkvetch (Astragalus Cicer L.). The latter three together with both pure alfalfa stands failed to meet the minimum stockpiled yield requirement for winter stockpiling of forage species. Tall fescue stands had the highest stockpiled yield among all pure stands. Late stockpile initiation provided more nutritious forage than the earlier initiation, however, the nutritive value of all species was adequate for a variety of grazing animals in different production stages regardless of the stockpile initiation date. Warm-season annuals generally exhibited higher stockpiled dry matter production than cool-season annuals. The overall results showed that many of the tested perennial and annual forage species provided adequate forage production and nutritive value for stockpiled grazing in the Great Plains region of western Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".