Effects of the forage to concentrate ratio on B-vitamin concentrations in different ruminal fractions of dairy cows
Bibliographic record
Abstract
Two studies were undertaken to verify the effect of the forage to concentrate ratio of the diet on B-vitamin concentrations in ruminal contents. In Study 1, eight primiparous and eight multiparous cows were used in a cross-over design, and concentrations of biotin, folates and vitamin B 12 were determined in ruminal fluid and plasma of cows fed a high-forage (HF; 58:42 forage to concentrate ratio; DM basis) or a low-forage (LF; 37:63 forage to concentrate ratio; DM basis) diet. In Study 2, six ruminally cannulated lactating cows were used in a cross-over design to evaluate the effects of forage to concentrate ratio (HF = 60:40; LF = 40:60; DM basis) on concentrations of seven B-vitamins in the particle-free fluid and in both liquid- and solid-associated bacteria. Results showed that B-vitamins were present mainly in the bacterial fractions of the ruminal content, while only limited amounts were found in the surrounding fluid. A change in the forage to concentrate ratio had a greater effect on vitamin concentration in the bacteria associated with the solid fraction than in those present in the liquid portion of the rumen. The most noticeable effects of a low forage diet were an increase in riboflavin, but a decrease in true vitamin B 12 concentrations in solid-associated bacteria as well as a decrease in biotin concentration in particle-free fluid. In conclusion, it appears that ruminal B-vitamin concentration is altered by changes in the forage to concentrate ratio, which suggests that the supply of vitamins to dairy cows is influenced by diet composition. Key words: B-vitamins, dairy cow, ruminal fractions, forage to concentrate ratio
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".