Protein dietary efficiency and methane emission in cattle fed soybean meal treated with tannins
Bibliographic record
Abstract
Adding tannins to the dietary protein source will cause complexation between the tannin and protein, which may increase dietary ruminal undegraded protein. Thus, this study aimed to evaluate the effects of replacing soybean meal (SM) with soybean meal treated with tannin (SMT) on the intake, partial and total nutrient digestibility, and protein dietary efficiency of young cattle fed a high-concentrate diet. Five Nellore bulls with bodyweights of 290 ± 11.2 kg were fitted with ruminal and abomasal cannulas and were used in the study. The experimental diets included 7.5% SM, with a proportion of that SM (0%, 33%, 66% or 100%) replaced with SMT. Another treatment (SMT+urea) with only 2.5% SM treated with tannins was tested. The intake of ether extract and the intake of neutral detergent fibre ash and protein were the only parameters related to feed intake that were affected by the replacement of SM with SMT. Ruminal and intestinal digestibility each showed a linear effect on crude protein, which decreased with ruminal digestibility and increased with intestinal digestibility. The intake of ruminal undegraded protein and metabolisable protein showed a positive linear correlation with the amount of SMT in the diet. SMT substitution showed no effect on methane emission. The replacement of traditional SM with SM treated with 2.5% tannins (85% condensed tannins and 15% hydrolysable tannins) for cattle that were fed high-concentrate diets showed increased amounts of metabolisable protein and decreased nitrogen loss per unit of crude protein, without changing the methane emission.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".