Response of lactating dairy cows to degree of steam‐flaked barley grain in low‐forage diets
Bibliographic record
Abstract
This study was conducted to investigate the effects of processing method (grinding vs. steam flaking) and increasing densities of steam-flaked barley grain on dry matter intake (DMI), rumen pH and fermentation characteristics, digestibility of dry matter in the total digestive tract (DDTT), and milk production of dairy cows. Eight multiparous mid-lactation Holstein cows averaging 103 ± 24 DIM, 44.5 ± 4.7 kg milk/day and weighing 611 ± 43 kg at the start of the experiment were used in a replicated 4 × 4 Latin square design with 21-day periods. Cows were fed diets consisting of (DM basis) 23.8% corn silage, 13.5% chopped alfalfa hay and 62.7% concentrate. The dietary treatments were either ground barley (GB) using a hammer mill or steam-flaked barley (SFB) - varying density at 390, 340 or 290 g/l. Processing method (GB vs. SFB) did not affect DMI (23.6 kg/day on average), DDTT (71.0% on average), milk yield (43.4 kg/day on average), milk components, rumen pH and molar proportions of acetate, propionate, butyrate and sorting activity. Ruminal isovalerate concentration tended (p = 0.06) to be higher for cows fed GB than those fed SFB-based diets. Decreasing the density of SFB from 390, 340 to 290 g/l tended to linearly increase DMI (p = 0.09), decrease total solids percentage of milk (p = 0.10) and linearly decreased milk urea nitrogen (12.8, 12.4 and 12.1 mg/dl; p = 0.04); also, the sorting index (SI) of the particles retained on the 19.0-mm sieve without affecting the SI of the particles retained on 8.0-mm, 1.18-mm or passed through 1.18-mm sieve (p = 0.05). These results indicated the limited effects of processing method (grinding vs. steam flaking) and densities of SFB (390, 290 or 290 g/l) on cows' performance and feed utilization for dairy cows fed low-forage diets. Therefore, both processing methods could be recommended under current feeding conditions of dairy cows.
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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) | 0.000 | 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".