Associations between herd-level feeding management practices, feed sorting, and milk production in freestall dairy farms
Bibliographic record
Abstract
The challenges associated with group-housed dairy cows include within-herd variability in nutrient consumption and milk production, which may be related to feeding management. The objective of this observational study was to examine the association of herd-level feeding management factors, feed sorting, and milk production. Twenty-two freestall herds with an average lactating herd size of 162±118 cows, feeding total mixed rations, were each studied for 7 consecutive days in summer and winter. In cases of multiple feeding groups within a herd, the highest producing group of cows with an even distribution of days in milk and parity was selected for this study. The average group size studied was 83±31 cows. The average study group consisted of cows 187±47 days in milk, with a parity of 2.3±0.6, consuming 24.3±2.6kg of dry matter, with an average group-level yield of 34.3±6kg of milk/d, 3.7±0.3% milk fat, and 3.2±0.18% milk protein. Milk production parameters, including yield, fat, and protein, were recorded through regular Dairy Herd Improvement milk testing. A survey of feeding management practices and barn characteristics was administered on each farm. The amounts of feed offered and refused were recorded and sampled daily to assess dry matter intake (DMI) and particle size distribution. Feeding twice per day compared with once per day was associated with an average increase of 1.42kg of DMI, 2.0kg of milk yield, and less sorting against long ration particles (>19mm). Every 2% group-level selective refusal (sorting) of long particles was associated with 1kg/d of reduction in milk yield. A 10cm/cow increase in feed bunk space was associated with a 0.06-percentage-point increase in group-average milk fat and a 13% decrease in group-average somatic cell count. These results support that herd-level management practices to promote feed access, such as increased feeding frequency and bunk space, may improve DMI and promote more balanced nutrient intake and greater milk production.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".