Using organic acids to control subacute ruminal acidosis and fermentation in feedlot cattle fed a high-grain diet1,2
Bibliographic record
Abstract
The objective of this study was to determine whether supplementing organic acids can prevent incidences of subacute ruminal acidosis (SARA) in beef heifers fed a diet consisting of 8% barley silage and 92% barley grain-based concentrate (DM basis). Ten ruminally cannulated Hereford crossbred heifers (484 ± 25 kg BW) were used in a replicated 5 × 5 Latin square design with 14-d periods including 10 d for dietary adaptation and 4 d for measurements. Dietary treatments included no supplementation (Control), low fumaric acid (61 g/d), high fumaric acid (125 g/d), low malic acid (59 g/d), and high malic acid (134 g/d). Organic acid supplementation had no effect on DMI ( = 0.77). Similarly, no effects were observed on mean ( = 0.74), minimum ( = 0.64), and maximum ( = 0.27) ruminal pH measured continuously for 48 h. Moreover, area under the curve for pH thresholds 6.2 ( = 0.97), 5.8 ( = 0.66), 5.5 ( = 0.55), and 5.2 ( = 0.93) was similar for all treatments. However, malic acid supplementation lowered the amount of time that ruminal pH was <6.2 compared with the Control ( = 0.02) and fumaric acid treatments ( < 0.01). No effects were observed on total VFA concentrations with organic acid supplementation ( = 0.98) compared with the Control, but greater total VFA concentrations were observed with fumaric acid compared with the malic acid treatments ( = 0.02). The population of total culturable bacteria 3 h after feeding was reduced with supplemental malic acid compared with the Control ( = 0.03) and fumaric acid treatments ( = 0.03). However, no effects were observed with organic acid supplementation on lactic acid-utilizing bacteria ( = 0.59). In conclusion, under the conditions of the present study, organic acid supplementation did not have any significant effects on ruminal fermentation parameters compared with the Control and were not effective in preventing SARA in beef cattle fed high-grain diets.
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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 | 0.001 | 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".