Enhancing pasture productivity with alfalfa: A review
Bibliographic record
Abstract
Alfalfa has been recognized for its superior yield and quality in seeded pastures. However, when grazing immature alfalfa there is a risk of animal losses due to frothy bloat in some ruminant livestock. Inclusion of at least 50% grass in the pasture mixture is commonly recommended to reduce the risk of bloat. Two decades of plant breeding have resulted in the release of AC Grazeland, an alfalfa cultivar that reduces the incidence of bloat. Other bloat control agents such as pluronic detergents and ionophores can also be of value. Development of grazing-tolerant alfalfa varieties is solving some of the problems associated with lack of persistence of alfalfa in mixed stands; however, they are not bloat-safe. Animal productivity commonly increases when alfalfa is included in pasture mixtures. Improvements in cattle rate of gain are observed when alfalfa contributes as little as 35% to the sward. Grazing management is the principal method for controlling pasture yield and quality as well as animal performance and bloat incidence. When grazing management is used to optimize pasture production and nutrient intake, yearling steers can gain as much as 1.5 kg head −1 d −1 and liveweight production ranging from 107 kg ha −1 (on dryland) to 1946 kg ha −1 (under irrigation) can be expected. Limiting utilization of alfalfa-based pasture to ≤70% may be more important for maximizing gain per head than managing herbage quality. Key words: Alfalfa, beef production, forage, grazing
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".