Accuracy and precision of diets fed to close-up cows on dairy farms and its association with early lactation performance
Bibliographic record
Abstract
Ensuring a consistent ration is critical for maximizing lactating cow performance, but this is not known for dry cows.The objectives of this cohort observational study were to: (1) characterize close-up dry cow diets fed on commercial farms in Ontario, Canada, (2) describe the accuracy of the nutrient composition between the formulated close-up diet and the diet offered to the cows, (3) describe the precision of the close-up diets across time, and (4) explore potential associations of that accuracy and precision with blood metabolic parameters and milk yield of cows in early lactation.Forty freestall dairy farms were visited once every 4 wk, for a total of 6 visits to each farm, from April to October 2022.At each visit, samples of the close-up diet were collected and analyzed for DM content and chemical composition.Close-up diet formulations were also obtained by each farm's nutritionists.During each visit, fresh cows (0 to 14 DIM) had blood samples taken for blood metabolites.The same cows were also monitored for milk yield up to 120 DIM.Multivariable models were used to analyze associations between variability (in relation to the formulated diet and across time) of nutrients in the close-up diet, as measured by CV, and outcomes in fresh cows.Corn silage (67.6% of farms) and straw (24.3% of farms) were the predominant primary forage sources used in the closeup dry cow diets.Soybean meal (37.8% of farms) and canola meal (18.9% of farms) were the main ingredients used as primary concentrate sources.Overall, the diets offered did not accurately represent the formulated diets.With the exception of NE L , the CV for the other nutrients were all greater than 5%.Diet variability, both between fed and formulated diets and from visit to visit during the close-up period, was associated with metabolic markers and dairy cow production.Lower variability in NFC between the fed and formulated diets was associated with better liver health index scores.Visit-to-visit variability in fat percent and NFC percent were associated with blood BHB concentrations, and NFC percent variability was associated with blood glucose levels.Serum nonesterified fatty acids concentrations were associated with visit-to-visit variability in DM percent and CP percent.These results underscore the importance of maintaining consistency between diet formulations and feeding practices over time to optimize early lactation dairy herd performance and health, granted that these diets are correctly formulated to meet the nutritional needs of cows in the close-up period and applied with recommended feeding practices.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".