81 Genetic relationships among feed intake, growth, and body weight in Holstein calves.
Bibliographic record
Abstract
Abstract Ensuring high feed intake and growth rates early in life has been positively associated with improved calf wellbeing and milk production in dairy cattle. Genetic selection for these early-life traits could produce calves that achieve high growth rates without increasing feed resources, reducing operational costs and environmental impact. However, feed efficiency is a composite trait with contributions from underlying genetic relationships among feed intake and energy sink traits. The objective of this study was to estimate genetic parameters for calf feed efficiency related traits in the pre-weaning and peri-weaning period, including metabolizable energy intake (MEI), average daily gain (ADG), and metabolic body weight (MBW). In total, 4,662 weekly average records for feed intake, ADG, and MBW from 938 Holstein dairy calves from 2016 to 2024 were provided by the Ontario Dairy Research Centre. MEI was calculated from the metabolizable energy content in the milk replacer and concentrated feed to capture the nutrient utilisation of both diets fed to calves in the pre-weaning and peri-weaning periods. Average MEI was 5.50 ± 1.62 Mcal for the pre-weaning period and 5.78 ± 1.43 Mcal for the peri-weaning period. Average MBW was 19.82 ± 2.16 kg0.75 for the pre-weaning period and 28.46 ± 2.27 kg0.75 for the peri-weaning period. Average ADG was 0.83 ± 0.21 kg/day in the pre-weaning period and 0.93 ± 0.16 kg/day in the peri-weaning period. A three-trait repeated records model for both time periods was fit in ASREML 4.2. Heritability estimates for pre-weaning MEI, ADG, and MBW were 0.32 ± 0.02, 0.20 ± 0.04, and 0.54 ± 0.06, respectively. Repeatability estimates for pre-weaning MEI, ADG, and MBW were 0.52 ± 0.02, 0.36 ± 0.02, and 0.88 ± 0.01, respectively. Strong positive genetic correlations were estimated between MEI and MBW (0.72 ± 0.06), MEI and ADG (0.86 ± 0.06), and MBW and ADG (0.76 ± 0.06) for the pre-weaning period. Heritability estimates for peri-weaning MEI, ADG, and MBW were 0.36 ± 0.02, 0.20 ± 0.04, and 0.51 ± 0.07 respectively. Repeatability estimates for peri-weaning MEI, ADG, and MBW were 0.68 ± 0.02, 0.36 ± 0.02, and 0.88 ± 0.01, respectively. Genetic correlations between all studied traits were lower in the peri-weaning period (0.44 ± 0.11 (MEI-MBW), 0.43 ± 0.12 (MEI-ADG), and 0.72 ± 0.06 (ADG-MBW)) in comparison to the pre-weaning period. These results highlight the opportunity for genetic selection as a strategy to improve early-life feed efficiency in Canadian dairy cattle. Estimates from this analysis will be used to derive genetic parameters for residual metabolizable energy intake as a measure of calf feed efficiency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".