Effects of Leymus chinensis replacement with whole-crop wheat hay on blood parameters, fatty acid composition, and microbiomes of Holstein bulls
Bibliographic record
Abstract
This study investigated the replacement of Leymus chinensis (LC) with whole-crop wheat hay (WCWH) in the diets of Holstein bulls in the fattening stage and examined the potential effects on blood parameters, fatty acids in rumen fluid and serum, and the rumen microbiomes. In this study, 12 Holstein bulls in the fattening period (body weight = 485.0 ± 40.8 kg) were assigned to 1 of 4 dietary treatments using a 4 × 4 Latin square design. Each experimental period consisted of a 17-d adaptation period and a 5-d collection period. The dietary treatments consisted of 4 proportions of WCWH (0, 33, 67, and 100%) as a substitute for LC (designated as WCWH0, WCWH33, WCWH67, and WCWH100, respectively). On d 18 and 22 of each experiment period, blood and rumen content samples were collected for analysis, respectively. Real-time quantitative PCR was used to analyze the rumen microbiomes. The results from this study revealed no differences in the saturated, monounsaturated, and polyunsaturated long-chain fatty acid proportions of rumen liquid among the treatments. It was observed in the present trial that rumen microbiotal flora were not significantly different in the bulls fed LC compared with the bulls fed WCWH. Additionally, blood sample analysis demonstrated that the concentration of urea nitrogen in the WCWH100 group was higher than that observed in the other groups. Meanwhile, no differences were detected for other serum parameters. There were no differences in the proportions of serum saturated, monounsaturated, and polyunsaturated long-chain fatty acids among the treatments. In conclusion, our data revealed that LC can be replaced with WCWH in the diet of Holstein bulls in the fattening stage with no negative effects on the blood indicators, fatty acids, and microbiomes.
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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) | 0.001 | 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 | 0.001 |
| 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".