Effects of citric acid supplementation on rumen fermentation, urinary excretion of purine derivatives and feed digestibility in steers
Bibliographic record
Abstract
Abstract BACKGROUND: An increase feed efficiency and rate of gain were observed from addition of sodium citrate to the diet of fatting lamb. It is suggested that the small amounts of citric acid (CA) may have a catalytic effect on rumen microbial metabolism which would result in a potential means of increasing feed efficiency. The objective was to evaluate the effects of CA supplementation on rumen fermentation, ruminal microbial production by measuring urinary excretion of purine derivatives, and digestibility in the total tract of steers. RESULTS: Ruminal pH linearly (P = 0.01) decreased, whereas total volatile fatty acid concentration linearly (P = 0.01) increased with increasing CA supplementation. Ratio of acetate to propionate linearly (P = 0.01) increased due to the increase in acetate production. Urinary excretion of purine derivatives was quadratically (P = 0.02) changed, with the lowest for control, medium for low CA and highest for medium and high CA supplementation. Similarly, digestibilities of nutrients in the total tract were also linearly and quadratically increased with increasing dosages of CA. CONCLUSION: Supplementation of CA increased rumen acetate concentration and thus increased ratio of acetate to propionate. Urinary excretion of purine derivatives and total digestibility were improved. In the experimental conditions of this trial, the optimum citric acid dose was about 200 g citric acid per steer per day. Copyright © 2009 Society of Chemical Industry
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".