Dietary preference in dairy calves for feed ingredients high in energy and protein
Bibliographic record
Abstract
In 3 experiments, we assessed preference of recently weaned dairy calves for (1) 8 high-energy feed types [barley meal, corn meal, corn gluten feed (CGF), oat meal, rice meal, sorghum meal, wheat meal, and wheat middlings meal]; (2) 6 high-protein feed types [corn gluten meal (CGM), wheat distillers dried grains, rapeseed meal, soybean meal (SBM), sunflower meal, and pea meal]; and (3) 4 mixtures (50:50) of the highest- and lowest-ranked high-energy and high-protein feeds, to assess whether calves maintain preference for feed ingredients that are included in a mixture. In all experiments, pairwise preference tests were conducted between all feed types (28 different pairwise preference tests in experiment 1, 15 tests in experiment 2, and 6 tests in experiment 3). Each pairwise preference test was conducted by offering ad libitum access to both feed types for 6h. All tests were repeated with 20 Holstein calves. Before this study, calves were offered milk replacer at a rate of 4 L/d and a pelleted starter feed ad libitum. After weaning at 62 d of age, each calf was involved in a pairwise preference test at 3 and 5d postweaning. A preference ratio was calculated for each calf in each test as (intake of feed type A)/(intake of feed type A + intake of feed type B). Preference for feed types was ranked across tests in each experiment using pairwise comparison charts. In experiment 1, the highest-ranked high-energy feed type was wheat meal and the lowest ranked were rice meal and CGF. In experiment 2, the highest-ranked high-protein feed type was SBM and the lowest ranked was CGM. According to the preference rankings from experiments 1 and 2, experiment 3 evaluated (50:50) mixtures of SBM + wheat meal, SBM + CGF, CGM + wheat meal, and CGM + CGF. The mixture of SBM + wheat meal was highest ranked, CGM + CGF was lowest ranked, and the mixtures containing one high-ranked and one low-ranked feed ingredient (SBM + CGF and CGM + wheat meal) were ranked equally. The results of this study indicate that young calves exhibit clear preferences for certain high-energy and high-protein feeds that may be considered highly palatable. Further, preference ranking of feed types provided as 50:50 mixtures was consistent with ranking of individual feed types, suggesting that palatability of mixed starter rations can be improved by inclusion of a preferred feed type.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".