Bloat in cattle grazing alfalfa cultivars selected for a low initial rate of digestion: A review
Bibliographic record
Abstract
The occurrence of frothy bloat limits the practice of alfalfa grazing in spite of the availability of strains bred specifically for pasture. Bloat is a chronic condition, endemic to cattle. Prophylactics and management techniques are available to reduce its incidence but they are expensive, difficult to administer, conflict with traditional grazing management regimens and do not eliminate bloat in all circumstances. A program to breed and evaluate a bloat-reduced strain of alfalfa was initiated in 1980 to overcome some of these limitations. A review of the results of grazing and feeding trials using alfalfas with low initial rates of digestion (LIRD) shows that this new strain reduces the incidence and severity of frothy bloat on pasture. Their effectiveness in controlling bloat was related to feeding or grazing management practices, the maturity of the plants and the season of use. Graziers may reduce the risk of occasional livestock losses from bloat by using LIRD cultivars, like AC Grazeland, or managing species/cultivar mixtures in ways that reduce the initial rate of digestion. Other bloat preventive strategies, including co-seeding with bloat-free legumes and using bloat-controlling prophylactics in combination with a LIRD alfalfa, are being investigated. Key words: Bloat, alfalfa, lucerne, legume, low initial rates of digestion, cattle, grazing
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".