Effects of Green Tea (Camellia sinensis) Waste Silage and Polyethylene Glycol on Ruminal Fermentation and Blood Components in Cattle
Bibliographic record
Abstract
The effects of green tea (Camellia sinensis) waste silage and supplemental polyethylene glycol (PEG) on rumen fermentation and blood components were studied in cattle. Six Holstein steers were fed three diets in a 33 Latin square design, replicated twice. One diet was a control with no added silage, and the other two diets were supplemented (20% of the dry matter) with green tea waste silage either with (PEG) or without PEG (tea). Most of the fermentation parameters including major volatile fatty acids (VFA) were not affected by the diet treatments. The concentrations of high density lipoprotein cholesterol in the PEG group and urea nitrogen in the tea and PEG groups were greater than those in the control before morning feeding. The plasma 6-hydroxy-2,5,7,8tetramethylchroman-2-carboxylic acid equivalent concentration was not different before morning feeding, but 3 h after morning feeding, its concentrations in both the tea and PEG groups were higher than in the control. Although the concentration of plasma vitamin A in the animals was not affected by feeding green tea waste silage, the concentrations of plasma vitamin E were significantly higher in the tea and PEG groups than in the control, both before and 3 h after morning feeding. The results from the present study suggest that feeding diets containing 20% of the dietary dry matter as green tea waste silage to Holstein steers has no negative impact on their ruminal fermentation, and increases their plasma antioxidative activity and concentration of vitamin E.
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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".