Differential ruminal degradation of alfalfa proteins
Bibliographic record
Abstract
Alfalfa (Medicago sativa L.) has high crude protein that is rapidly and extensively degraded in the rumen. Our objective was to develop a protocol where individual proteins could be characterized for their ruminal degradation. Proteins from individual genotypes of three alfalfa cultivars were characterized using fluorescence 2D difference gel electrophoresis combined with MALDI-TOF mass spectrometry for protein identification. Twenty-six proteins were characterized, representing between 33 and 41% of the total protein among genotypes. Variation for protein degradation was observed among proteins after 45 and 120 min of incubation in the rumen of a Holstein steer (P < 0.001). After 45 min of ruminal incubation, nine proteins averaged 75% or more remaining, 12 had 50% or less remaining, and five were intermediate. After 120 min of ruminal incubation, four proteins averaged greater than 80%, seven between 80 and 50%, and 15 less than 50% remaining. Although all proteins were degraded over time, the rate and amount of degradation was dramatically different among them. The rate of digestion differed (P = 0.05) for 3 and 10 proteins among genotypes after 45 and 120 min, respectively. Individual proteins characterized ranged in mass from 41 to 0.29% of the total mass of protein characterized. Total content of those proteins that differed for rate of digestion ranged from 7 to 1%. The results demonstrate that individual proteins can be characterized for their ruminal degradation. The ability to separate proteins based ruminal degradation suggests there is potential to select for protein that degrades more slowly and possibly escapes the rumen.Key words: Alfalfa, protein, rumen, digestion
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".