Effects of milk replacer feeding rate and fat content on Jersey calf nutrient digestion and performance to 4 months of age
Bibliographic record
Abstract
This study evaluated effects of milk replacer (MR) feeding rate and fat concentration in MR on total-tract digestion (TTD) and growth performance in Jersey calves. Jersey heifer calves (n = 100, 2 blocks of 50; initially 30 ± 3.0 kg of body weight; 4-11 d of age) were randomly assigned to 1 of 4 treatments in a 2 × 2 factorial arrangement of MR feeding rate [454 g for 42 d, and 227 g for 7 d (MOD); or 454 g for 7 d, 681 g for 35 d, and 341 g for 7 d (HI), as-fed basis] and MR fat content (17 or 24% fat as-fed basis). Milk replacers (24% crude protein as-fed basis) were reconstituted to 14% solids and fed in 2 equal feedings for 42 d, and then mornings only for 7 d. Textured calf starter (21% crude protein, 40% starch, dry matter basis) and water were offered for ad libitum consumption. From d 57 to 112, calf starter was mixed with 5% chopped grass hay. Calves were housed individually to d 56 and housed in groups (4-5 calves/pen) from d 57 to 112. Estimates of TTD were measured in 5 calves/treatment (block 1) at wk 3 of the study using acid-insoluble ash as an indigestible marker. From 0 to 56 d, calf starter intake (CSI) was greater for MOD vs. HI and 17 versus 24% fat; average daily gain was greater for HI versus MOD; and hip width change was greater for 17 versus 24% fat. Estimates of organic matter TTD were greater for HI versus MOD, but neutral detergent fiber TTD was greater for MOD versus HI and for 17 versus 24% fat. From 57 to 112 d, hip height change was greater for MOD versus HI, and hip width change was greater for 17 versus 24% fat. In this study, feeding Jersey calves more MR improved preweaning average daily gain, but had a negative effect on CSI and likely rumen development, as neutral detergent fiber TTD was reduced at 3 wk and frame growth was reduced from d 57 to 112. This resulted in similar final calf body weights between MR feeding rates at the end of the study. No benefits were observed for feeding more fat in MR as CSI or for NDF digestibility, and frame growth was reduced.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".