Effects of Soybean Small Peptides on Rumen Fermentation and on Intestinal and Total Tract Digestion of Luxi Yellow Cattle
Bibliographic record
Abstract
Four Luxi beef cattle (400±10 kg) fitted with ruminal, duodenal and ileal cannulas were used in a 4×4 Latin square to assess the effects of soybean small peptide (SSP) infusion on rumen fermentation, diet digestion and flow of nutrient in the gastrointestinal tract. The ruminal infusion of SSP was 0 (control), 100, 200 and 300 g/d. Ruminal SSP infusion linearly (p<0.01) and quadratically (p<0.01) increased microbial protein synthesis and rumen ammonia-N concentration. Concentrations of total volatile fatty acid were linearly increased (p = 0.029) by infusion SSP. Rumen samples were obtained for analysis of microbial ecology by real-time PCR. Populations of rumen Butyrivibrio fibrisolvens, Streptococcus bovis, Ciliate protozoa, Ruminococcus flavefaciens, and Prevotella ruminicola were expressed as a proportion of total Rumen bacterial 16S ribosomal deoxyribonucleic acid (rDNA). Butyrivibrio fibrisolvens populations which related to total bacterial 16S rDNA were increased (p<0.05), while Streptococcus bovis populations were linearly (p = 0.049) and quadratically (p = 0.020) decreased by infusion of SSP. Apparent rumen digestibility of DM and NDF were (Q, p<0.05; L, p<0.05) increased with infusion SSP. Total tract digestion of DM, OM and NDF were linearly (p<0.01) and quadratically (p<0.01) increased by infusing SSP. The flow of total amino acids (AA), essential amino acids (EAA) and individual amino acids were linearly (p<0.01) and quadratically (p<0.01) increased with infusion SSP. The digestibility of Lysine was quadratically (p = 0.033) increased and apparent degradability of Arginine was linearly (p = 0.032) and quadratically (p = 0.042) increased with infusion SSP. The results indicated that infusion SSP could improve nutrient digestion, ruminal fermentation and AA availability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".