Farm-level nutritional factors associated with milk production and milking behavior on Canadian farms with automated milking systems
Bibliographic record
Abstract
The objective of this study was to describe the nutritional strategies used on Canadian dairy farms with automated milking systems (AMS), both at the feed bunk and the concentrate offered at the AMS, as well as to determine what dietary components and nutrients, as formulated, were associated with milk production and milking behaviors on those farms. Formulated diets (including ingredients and nutrient content) and AMS data were collected from April 1, 2019, until September 30, 2020, on 160 AMS farms (eastern Canada [East] = 8, Ontario [ON] = 76, Quebec [QC] = 22, and western Canada [West] = 54). Both partial mixed ration (PMR) and AMS concentrate samples were collected from May 1 to September 30, 2019, on 169 farms (East = 12, ON = 63, QC = 42, West = 52). We collected AMS milking data for 154 herds. For each farm (n = 161), milk recording data were collected and summarized by farm to calculate average milk yield and components. Multivariable regression models were used to associate herd-level formulated nutrient composition and feeding management practices with milk production and milking behavior. Milk yield (mean ± SD = 37.0 ± 0.3 kg/d) was positively associated with the PMR ether extract (EE) concentration (+0.97 kg/d per percentage point [p.p.] increase) and with farms that fed barley silage as their major forage source (n = 16; +2.18 kg/d) as compared with haylage (n = 42), whereas farms that fed corn silage (n = 96; +1.23 kg/d) tended to produce more milk than farms that fed haylage. Greater milk fat content (4.09 ± 0.28%) was associated with a greater PMR-to-AMS concentrate ratio (+0.02 p.p. per unit increase) and total diet net energy for lactation (+0.046 p.p. per 0.1 Mcal/kg increase), but a lesser percentage of NFC of the PMR (-0.016 p.p. per p.p. increase of NFC percentage). Milk protein content (3.38 ± 0.14%) was positively associated with the forage percentage of the PMR (+0.003 p.p. per p.p. increase of forage percentage) and the total diet starch percentage (+0.009 p.p. per p.p. increase of starch percentage), but was negatively associated with farms feeding corn silage (-0.1 p.p. compared with haylage) as their major forage. Greater milking frequency (2.77 ± 0.40 milkings/d) was observed on farms with free-flow cow traffic systems (+0.62 milkings/d) and was positively associated with feed push-up frequency (+0.013 milkings/d per additional feed push-up), but negatively associated with PMR NFC content and forage percentage of the total ration (-0.017 milkings/d per p.p. increase of forage percentage). Lastly, greater milking refusal frequency (1.49 ± 0.82 refusals/d) was observed on farms with free-flow cow traffic systems (+0.84 refusals/d) and farms feeding barley silage (+0.58 refusals/d) than with guided flow and farms feeding either corn silage or haylage, respectively. These data give insight into the ingredients, nutrient formulations and type of diets fed on AMS dairy farms across Canada and the association of those factors with milk production and milking behaviors.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".