Assessment of rumen bacteria in dairy cows with varied milk protein yield
Bibliographic record
Abstract
The present study was conducted to assess rumen bacteria in lactating cows with different milk protein yield, aiming to understand the role of rumen bacteria in this trait. Cows with high milk protein yield (high milk yield and high milk protein content, HH; n = 20) and low milk protein yield (low milk yield and low milk protein content, LL; n = 20) were selected from 374 mid-lactation Holstein dairy cows fed a high-grain diet. Measurement of the rumen fermentation products showed that the concentrations of ruminal total volatile fatty acids, propionate, butyrate, and valerate and the proportion of isobutyrate were higher in the HH cows than in the LL cows. Amplicon sequencing analysis of the rumen bacterial community revealed that the richness (Chao 1 index) of rumen microbiota was higher in the LL cows than in the HH cows. Among the 10 predominant bacterial phyla (relative abundance being >0.10%, present in >60% of animals within each group), the relative abundance of Proteobacteria was 1.36-fold higher in the HH cows than in the LL cows. At the genus level, the relative abundance of Succinivibrio was significantly higher and that of Clostridium tended to be higher in the LL cows than in the HH cows. Sharpea was 2.28-fold enriched in the HH cows compared with the LL cows. Different relationships between the relative abundances of rumen microbial taxa and volatile fatty acid concentrations were observed in the HH and the LL animals, respectively. Succinivibrio and Prevotella were positively correlated with acetate, propionate, and valerate in the LL cows, whereas Sharpea was positively correlated with propionate and valerate concentrations in the HH cows. Collectively, our results revealed that rumen bacterial richness and the relative abundances of several bacterial taxa significantly differed between dairy cows with high and low milk protein yields, suggesting the potential roles of rumen microbiota contributing to milk protein yield in dairy cows.
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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 | 0.001 | 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".