Intake, liveweight gain and feed preference by steers fed combinations of lucerne and Westerwolds ryegrass silages
Bibliographic record
Abstract
Nutritive value and voluntary intake of legumes are generally considered to be higher than those of grasses when ensiled at similar digestibility, although high levels of soluble protein can result in low N utilization by animals and high losses to the environment. The objectives of this experiment were to describe the optimum combination of Westerwolds ryegrass (Lolium multiflorum Lam. cv. Aubade) and lucerne (Medicago sativa L. cv. AC Caribou) silages to maximize liveweight gain of steers fed silage, determine chemical components that are important and ascertain whether steers selected the optimum mixture when given a choice. Both silages contained similar concentrations of dry matter (DM), acid‐detergent fibre (ADF) and organic acids, but lucerne silage had higher concentrations of N, soluble‐N and ammonia‐N. Westerwolds ryegrass silage contained more neutral‐detergent fibre (NDF). In a 12‐week experiment, voluntary intake by Hereford steers was not influenced when the proportion of the two silages was changed from 1 to 0 in 0·25 increments. However, liveweight gain and feed efficiency increased linearly (P < 0·001) as the proportion of ryegrass silage fed was increased. When preconditioned to either of the two silages, steers showed a significant preference for ryegrass over lucerne (P < 0·05). When conditioned to a mixture of both silages, no preference was elicited. It is suggested that extensive solubilization and deamination of protein in the lucerne silage may have caused the preference for Westerwolds ryegrass silage and the higher liveweight gains on diets containing higher proportions of Westerwolds ryegrass silage.
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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) | 0.001 | 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".