Effect of the amount of concentrate offered in an automated milking system on dry matter intake, milk yield, milk composition, ruminal digestion, and behavior of primiparous Holstein cows fed isocaloric diets
Bibliographic record
Abstract
The objective of this study was to determine if the quantity of concentrate provided in an automated milking system (AMS) affects dry matter intake (DMI), attendance to the AMS, milk and milk component yield, feeding behavior, cow activity, and ruminal fermentation of lactating dairy cows fed isocaloric diets. Eight ruminally cannulated primiparous Holstein cows were used in a replicated 4 × 4 Latin square design with 28-d periods. Cows were housed in a freestall facility with a guided-traffic (feed-first) flow barn design. Treatments included 0.5, 2.0, 3.5, or 5.0 kg/d of dry matter of pellet in the AMS with an equivalent reduction of the same pellet in the partial mixed ration (PMR). Days 21 to 24 of each treatment period were used for DMI, milking performance (visits, yield, and composition), behavior, and ruminal pH determination, and d 25 to 28 were used for ruminal short-chain fatty acid and ammonia concentrations as well as total-tract digestibility. As imposed, consumption of AMS pellet linearly increased, equating to 0.50, 2.00, 3.49, and 4.93 kg of dry matter/d for the 0.5, 2.0, 3.5, and 5.0 kg/d treatments, respectively. Correspondingly, the standard deviation in AMS pellet intake among days linearly increased from 0.06 to 0.85 kg of dry matter/d as the quantity of concentrate in the AMS increased from 0.5 to 5.0 kg. The PMR DMI decreased linearly with increasing AMS concentrate allocation, but total DMI (PMR + AMS) was not affected (25.3 kg/d). As the AMS concentrate allocation increased, the selection against particles retained on an 18-mm sieve linearly increased and selection against particles retained on the pan decreased. Milking frequency (3.22 milkings/d), milk yield (37.5 kg/d), milk fat yield (1.43 kg/d), and milk protein yield (1.22 kg/d) were not affected; however, milk urea nitrogen concentration decreased linearly with increasing AMS concentrate. Ruminal pH averaged 6.18 and was not affected by AMS concentrate. Total ruminal short-chain fatty acid concentration was greatest when 3.5 kg of concentrate was allocated in the AMS and ruminal ammonia decreased linearly with increasing AMS concentrate. Time spent lying, the number of lying bouts, and average bout duration were not affected by treatment. These data indicate that increasing the quantity of concentrate in the AMS increases daily variability in AMS concentrate intake while decreasing PMR intake without affecting voluntary visits to the AMS and milk or milk component yield. As such, under isocaloric dietary settings, increasing the supply of pellet in the AMS is not likely to affect voluntary visits to the AMS, milk and milk component yields, or ruminal fermentation.
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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 | 0.001 | 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".