Nutritional practices on Manitoba dairy farms
Bibliographic record
Abstract
A survey was conducted on 40 randomly selected dairy farms across Manitoba to document nutritional practices and diet compositions, and study relationships between diet composition and milk production. Samples from all feeds, diets, and the bulk milk tank were collected and analyzed. Inclusion rates of feed ingredients were recorded. Production data were obtained from Western Canada Dairy Herd Improvement Services (WCDHIS). Component feeding and total mixed ration (TMR) feeding were used in 37.5 and 62.5% of herds, respectively. Only 24% of TMR-fed herds used two or more TMR. The medians of dietary contents of crude protein (CP), rumen degradable protein (RDP), rumen undegradable protein (RUP), and neutral detergent fibre (NDF), and milk urea nitrogen (MUN) were 18.3% dry matter (DM), 12.2% DM, 5.7% DM, 34.8% DM, and 15.6 mg dL-1, respectively. On average, diets contained 6.2% more net energy for lactation (NEl), 35.9% more RDP, 15.8% less RUP, 74.6% more calcium (Ca), 51.9% more phosphorous (P), 44.9% more potassium (K), 116.1% more magnesium (Mg), and 4.2% more sodium (Na) than the estimated requirements based on the average milk production and estimated DM intake of the cows on each farm. In 25% of TMR-fed herds, TMR was coarser than recommended. Milk yield, and milk fat percentage were affected by breed, but were not affected by feeding practice (TMR or component feeding), diet composition, and physically effective NDF (peNDF) determined as the percent age of feed particles retained by the 8- and 19-mm screens of the Penn State Particle Separator multiplied by dietary NDF. Milk protein percentage was positively correlated to RUP. MUN was positively correlated to RDP, RUP, NDF, and days in milk (DIM). Reductions in dietary CP, RDP, Ca, P, Mg, and K could reduce nutrient excretions to the environment without reducing milk production and health. Increasing dietary RUP content could improve milk production on Manitoba dairy farms. Key words: Dairy cattle, milk production, protein, fibre, minerals, particle size.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".