A comprehensive integration of factors affecting vitamin B12 concentration in milk of Holstein cows: Genetic variability, milk productivity, animal characteristics, and feeding management
Bibliographic record
Abstract
Daily vitamin B12 (VB12) requirements of humans can naturally be fulfilled by animal product consumption, especially products from ruminants because of bacteria dwelling in their rumen. Indeed, only bacteria can synthesize this vitamin. Milk is hence an excellent source of VB12. This cross-sectional study was undertaken to unravel factors, such as genetic variation, diet and cow characteristics, and milk production, explaining the large variation in milk B12 concentration among cows by using an integrative approach. Milk samples from 2 consecutive milkings were collected from 3,533 Canadian Holstein cows (1,239 first, 932 s, and 1,362 third and more lactations) located in 99 herds with various feeding management. For genetic variation analysis purpose, pedigrees were traced back for 3 complete generations for each sire and dam. A total of 10,021 identities were used in the subsequent genetic analyses. Milk VB12 averaged 4.2 ng/mL with a range between 0.7 and 9.0 ng/mL. Dietary fiber (NDF from forage, dietary NDF, ADF, and lignin) increased and dietary components related to energy (non-fiber carbohydrate, starch, net energy of lactation, and percentage of concentrate) decreased VB12 in milk. Milk VB12 varied with days in milk, with a similar pattern as milk fat and protein concentration lactation curves. Milk VB12 increased as age at calving increased. When disregarding the herd variance, heritability value was 0.37, meaning that milk VB12 can be modified by genetic selection. The final model including factors related to the diet, animal characteristics and milk productivity, and genetic variation explained 79% (pseudo-R2) of the milk VB12 variation. When excluding the random effect of the cow, i.e., excluding the animal and genetic relationships, the pseudo-R2 dropped to 43%, reinforcing the importance of genetic variation in explaining milk VB12 variation. To our knowledge, the present study is the most comprehensive evaluation of factors affecting milk VB12 variation including the greatest number of cows from various lactation stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".