166 Effects of genetic and non-genetic factors on bovine milk cholesterol content
Bibliographic record
Abstract
Dairy products are rich in cholesterol (CHL); therefore, monitoring CHL levels in cow milk may become an important factor. This study aimed to (a) determine the factors that influence milk CHL content, (b) estimate (co) variances and heritability for milk cholesterol, and (c) estimate genetic correlations between milk CHL and other production traits. Milk samples were collected from 2,907 cows from 38 commercial herds in Quebec. Milk CHL content was determined by gas chromatography and expressed as mg of CHL in 100 g of total fat (CHL_fat) or in 100 mg of milk (CHL_milk). Test-day milk (Milk), fat (Fat) and protein (Prot) yields, fat (Fat%) and protein (Prot%) percentages, and somatic cell counts (SCC) were also determined. A total of 2,418 cows were retained for analysis after editing for registration status, cow, sire/dam identification, breed, age at calving, and stage of lactation. Linear mixed models with fixed effects of test date, parity, age at calving, and stage of lactation and random effects of herd-year-season of calving and residual were run to test the significance of fixed effects on CHL. Univariate models were used to estimate (co) variances and heritability; meanwhile bivariate models were used to compute phenotypic and genetic correlations. The mean values of CHL_fat and CHL_milk were 274.60 ± 74.66 mg and 11.27 ± 0.74 mg, respectively. Cholesterol content was significantly affected by stage of lactation but not by parity and age at calving, regardless of the scale of expression (P < 0.05). Heritability estimates for CHL_fat and CHL_milk were 0.09 ± 0.04 and 0.18 ± 0.05, respectively. Phenotypic and genetic correlations between CHL_fat and CHL_milk were 0.85 ± 0.01 and 0.33 ± 0.17, respectively. CHL_fat had no significant genetic correlations with Milk, Fat, and Prot% (−0.17 to −0.37) and close to zero genetic correlation with Prot and Fat%. CHL_milk also had low nonsignificant genetic correlations with Fat (0.33) and Prot (−0.39) but moderate and significant genetic correlations with Milk (0.58) and Prot% (0.47) and high genetic correlation with Fat% (0.81). CHL_fat and CHL_milk also had no significant genetic correlations with SCC. This is the first study to estimate genetic parameters for milk CHL content. Further studies on response to selection and genomics are required to assess the possibility of genetically selecting cows with desired CHL content.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".