Effect of particle size and partial replacement of alfalfa hay by soya bean hulls on nutrient intake, total tract digestibility and rumen degradability of diets by Holstein steers
Bibliographic record
Abstract
This study examined the effect of alfalfa hay (AH) particle size and the replacement of soya bean hull (SH) for AH within the diet of restricted fed Holstein steers on dry matter intake (DMI), total tract digestion, ruminal digestion, ruminal pH and ammonia nitrogen content, and faecal pH. Four rumen-cannulated Holstein steers averaging 353 ± 9.6 kg of BW were assigned to a 4 × 4 Latin square experiment with four periods and a 2 × 2 factorial arrangement of treatments. Factor A was AH particle size (fine vs. coarse) and factor B was diet SH content (0% vs. 10%; substituted for AH). Steers were fed at 1% of body weight of TMR containing 400 g/kg forage and 600 g/kg concentrate. Chopping of AH to fine particles decreased (p = 0.01) amount of dietary materials retained on the medium sieve (8 mm). The inclusion of SH significantly increased (p = 0.01) materials retained on the 1.18-mm sieve and tended to decrease (p = 0.07) materials on 19-mm sieves. The inclusion of SH increased (p = 0.01) ether extract (EE) intake and increased (p = 0.07) DMI. Inclusion of SH increased (p = 0.01) EE digestion and decreased (p < 0.01) faecal pH. Neither AH particle size nor SH inclusion in diets affected (p > 0.10) the in situ ruminal degradability coefficients of DM ('a', 'b', 'c' or 'a+b'). No interaction of AH×SH was seen on nutrient intake, digestibility and in situ ruminal degradability of Holstein steers.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".