Intake and Digestibility of Sheep-fed Alfalfa Haylage Supplemented with Corn
Bibliographic record
Abstract
The objective of this study was to determine the effect of dry corn (DC) and fermented corn (FC) supplemented to alfalfa haylage (AH) (Medicago sativa L.) on feed intake, digestibility, and nitrogen (N) balance in wether sheep. The study consisted of five feeding treatments incorporating AH alone and AH supplemented with 5 or 10 g of DC (DC5 and DC10, respectively) or FC (FC5 and FC10, respectively) kg−1 body weight (BW) d−1 to Suffolk wethers. The DC5 and FC5 treatments were higher in acid detergent fibre (ADF) intake (P < 0.001), neutral detergent fibre (NDF) intake (P < 0.001), and N intake (P < 0.05) compared with the DC10 and FC10 treatments. Both energy sources (DC and FC) and supplemental levels (5 and 10 g kg−1 BW d−1) increased (P < 0.05) the digestibility of dry matter (DM) and organic matter (OM), and the digestibility of OM in DM (D value), and decreased the digestibility of ADF (P < 0.05). The DC10 and FC10 treatments had higher D values (P < 0.05) and reduced ADF digestibility values (P < 0.05) compared with the DC5 and FC5 treatments. The FC supplemented treatments had reduced N balances compared with DC treatments (P < 0.001). It was concluded that DC was a better supplement to AH than FC in terms of NDF intake, crude protein (CP) digestibility, and N balance. The main effect of increasing the level of starch supplementation to the diet was a reduced N and fibre intake, as well as N and fibre digestibility, but an increased D value.
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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".