Gradually weaning goat kids may improve weight gains while reducing weaning stress and increasing creep feed intakes
Bibliographic record
Abstract
Most dairy goat farms rear kids on ad libitum milk replacer; calf research suggests this improves growth and welfare, but solid feed intakes are problematic. Weaning can be gradual (incremental milk reduction) or abrupt (sudden, complete milk removal, which evidence suggests reduces welfare). Three treatments were created: abrupt weaning (AW: ad libitum milk until weaning) and gradual weaning [milk ad libitum until day 35, then milk unavailable 3.5 h/day until day 45 when milk removal was a 7 h/day block (gradual weaning 1: GW1) or two 3.5 h/day blocks (gradual weaning 2; GW2)]; complete milk removal occurred at day 56 for all. Experiment 1 investigated on-farm feasibility, behavior, and average daily gain (ADG). Experiment 2 investigated feed intakes, behavior, and ADG for AW and GW2. Experiment 1 had 261 kids (nine pens of 25–32), CCTV recorded 6 h/day, and group-level scan sampling recorded target behaviors. Kruskal–Wallis tests showed GW2 kids spent more time feeding on solids during weaning ( p = 0.001) and displayed lower levels of ‘frustrated suckling motivation’ PostWean ( p = 0.008). However, feeding competition differed PreWeaning ( p = 0.007). ADG data from 159 female kids analyzed by a general linear model (fixed factor: treatment; covariate: day 34 weight) found GW2 had the highest ADG from day 35–45 ( p ≤ 0.001) and no differences from day 45 to 56, and AW had the highest ADG PostWean (day 56–60). Experiment 2 had two AW pens (9 kids/pen) and two GW2 pens (8 and 9 kids/pen). A computerized feeder recorded milk intakes from day 22 to 56. Pen-level solid feed/water intakes were recorded from day 14–70. General linear models (fixed factor: treatment; covariate: PreWean value) found GW2 kids had higher ADG ( p = 0.046) and lower milk intake ( p = 0.032) from day 45–55, and PostWean (day 56–70) trended toward GW2 higher ADG ( p = 0.074). Mann–Whitney U tests showed pen-level feed intake differences: AW had higher creep and straw throughout, GW2 showed higher creep during weaning (day 35–55), and higher water PostWean (>56 d). Behavioral observations suggest that gradually weaned kids may have enhanced welfare. Pen-level gradual weaning is feasible and, while weight gain results were mixed, it reduced milk intake, increased creep intake, and therefore combined with behavioral evidence can be recommended.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".