Dietary ratios of maize silage to lucerne hay affect feed intake, chewing activity and milk production of dairy cows
Bibliographic record
Abstract
The present study investigated the effects of substitution of chopped lucerne hay (LH) for maize silage on feed intake, rumen pH and fermentation, digestibility, milk production and feed efficiency of dairy cows. Fifteen Holstein dairy cows in early lactation (37 ± 10 days in milk) were randomly assigned to three dietary treatments in a completely randomised design. The experiment lasted for 80 days, with 10 days of adaptation and 70 days of data collection. Treatment diets consisted of 60% concentrate and 40% forage, comprising 30 : 10 (MS30), 20 : 20 (MS20) or 10 : 30 (MS10) of maize silage (MS) to LH ratio (MS : LH). Cows were fed ad libitum as total mixed ration. Water was added daily to adjust the moisture content of the feed to be similar across diets. Decreasing the ratio of MS : LH resulted in linear and quadratic decreases of DM intake and physically effective neutral detergent fibre, without affecting apparent digestibility in the total digestive tract. Decreasing MS : LH also linearly reduced total chewing time and tended to reduced chewing index (min/kg DM intake), but had limited effects on rumen pH and fermentation characteristics. Increasing the substitution of LH for MS decreased milk production (33.1, 31.7, and 29.8 kg/day for MS30, MS20, and MS10, respectively), and tended (P = 0.06) to decrease 4% fat-corrected milk and fat yield. However, milk content of protein (2.70%, 2.77% and 2.77%) and fat improved, and tended to improve by decreasing the MS : LH ratio, respectively. The efficiency of milk production, expressed as either milk yield/kg DM intake or 4% fat-corrected milk/kg DM intake, was not affected by the treatments. Results indicated that under the current feeding conditions, decreasing the ratio of MS : LH was not recommended to maintain milk production and DM intake.
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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".