Effect of propylene glycol supplementation on microbial protein production in transition dairy cows
Bibliographic record
Abstract
Limited research suggests that propylene glycol (PG) supplementation can have inhibitory effects on ruminal microbes. Our hypothesis was that PG supplementation would reduce microbial protein production. The objective of this study was to determine the effect of PG supplementation on microbial protein production in transition dairy cows. Sixteen pregnant cows (seven primiparous and nine multiparous) were paired based on expected calving dates and then randomly assigned within each pair to either a basal diet (control) or basal diet plus 624 g d-1 of PG. Diets were fed twice daily for ad libitum intake, and PG was fed in equal amounts as a top dress from day -7 to day 45 (transition period). Sample collection was carried out at three time intervals starting at day -14 ± 5, day 15 and day 38 relative to calving, with the first collection period (day -14 ± 5) being the pretreatment period. Propylene glycol supplementation had no effect on total urine purine derivatives (PD; allantoin + uric acid) excretion; consequently, microbial N supply, estimated using total urinary PD excretion, was not affected by PG supplementation. There was an increase in urine total PD excretion and, thus, estimated microbial N supply, with time relative to calving. Microbial efficiency did not change with time relative to calving and, therefore, the increase in dry matter intake during the post-partum period led to the increase in estimated microbial N supply. Results from this study indicate that supplementing PG over the transition period had no effect on microbial protein production in the rumen.Key words: Transition dairy cow, propylene glycol, microbial protein production
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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 | 0.000 |
| 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) | 0.001 | 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".