Response of lactating dairy cows to dietary protein from canola meal or distillers’ grains on dry matter intake, milk production, milk composition, and amino acid status
Bibliographic record
Abstract
Acharya I. P., Schingoethe D. J., Kalscheur K. F. and Casper D. P. 2015. Response of lactating dairy cows to dietary protein from canola meal or distillers’ grains on dry matter intake, milk production, milk composition, and amino acid status. Can. J. Anim. Sci. 95: 267–279. A study was conducted to determine the response of feeding two different crude protein (CP) concentrations [low protein (LP, 14.3% CP) and high protein (HP, 16.3% CP)] and sources of protein [canola meal (CM) and high-protein dried distillers’ grains (HPDDG)] on dry matter intake, milk production and composition, and amino acid (AA) status of high producing dairy cows. Sixteen Holstein cows were used in a replicated 4×4 Latin square having a 2×2 factorial arrangement of treatments. All diets contained 55% forage (50% alfalfa hay and 50% corn silage) and 45% concentrate. Diets were formulated to contain LP with CM, LP with HPDDG, HP with CM and HP with HPDDG. Experimental feeding periods were 4 wk with data collected during weeks 3 and 4 of each period. Dry matter intake (24.6 vs. 25.9 kg d−1 for LP and HP, respectively) was increased for cows fed the higher CP diets, milk yield was greater for cows fed HP diets (34.0 vs. 36.4 kg d−1), and milk fat percentage was greater for cows fed HP compared with LP, but were similar between dietary protein sources. Feed efficiency calculated as fat-corrected milk and energy-corrected milk was greater for cows fed HP than LP, but was similar between sources. Dietary metabolizable protein of CM diets was utilized more efficiently than from HPDDG diets for milk protein production. Mammary gland extraction efficiency of essential AA indicated that Met was the first limiting AA for CM-based diets while Lys was first limiting for HPDDG-based diets. In summary, canola meal and distillers’ grains are both good quality protein supplements for lactating cows.
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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 | 0.001 |
| 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 | 0.001 |
| 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".