Preweaned heifer management on US dairy operations: Part VI. Factors associated with average daily gain in preweaned dairy heifer calves
Bibliographic record
Abstract
The study objective was to evaluate average daily gain (ADG) in dairy heifer calves based on health, feeding, management practices, and environmental factors. This study included 102 operations in 13 states that participated in the calf component of the National Animal Health Monitoring System's Dairy 2014 study. This 18-mo longitudinal study included 1,410 Holstein heifer calves monitored from birth to weaning. The mean ADG from birth to final weight was 0.74 kg/d. Backward elimination model selection in Proc Mixed after univariate screening determined factors that significantly affected ADG. The final model included dam lactation number, singleton versus twin birth, bedding type, Giardia and Cryptosporidium fecal shedding, disease events, a categorized average temperature-humidity index for the preweaning period (pTHI), amount of protein in the liquid diet (kg/d), milk pasteurization, direct-fed microbials, and the interaction between milk pasteurization and direct-fed microbials. After controlling for other independent variables in the model, calves born to first-lactation dams gained less (0.60 kg/d) than calves from second- (0.65 kg/d) or third- or greater-lactation (0.64 kg/d) dams. Singleton calves gained 0.07 kg/d more than twins. Calves bedded with sand or no bedding gained less (0.49 kg/d) than calves on all other bedding types. Calves negative for Cryptosporidium or Giardia at the time of sampling gained 0.03 or 0.02 kg/d more, respectively, than calves that were positive for Cryptosporidium or Giardia. Calves with no disease events gained 0.07 kg/d more than calves with one or more disease events. Calves experiencing an average pTHI <50 gained more (0.67 kg/d) than calves experiencing an average pTHI from 50 to 69 (0.62 kg/d), or ≥70 (0.59 kg/d). Within the range of observed kilograms of protein fed per day in the liquid diet, every additional 0.1 kg of protein fed per day equated to 0.02 kg/d of gain. Calves fed milk replacer with a direct-fed microbial gained less (0.44 kg/d) than calves fed milk replacer without a direct-fed microbial (0.60 kg/d) and calves fed pasteurized or unpasteurized milk regardless of direct-fed microbial use. These results highlight the importance of feeding a quantity and quality of a liquid diet to achieve optimal growth, keeping calves free of disease, the type or status of bedding, and mitigating the effects of temperature and humidity on preweaning ADG.
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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 | 0.000 | 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".