Effect of maize silage to grass silage ratio and feed particle size on protein synthesis and amino acid profile in different microbial fractions in a semi-continuous rumen simulation
Bibliographic record
Abstract
The objective was to investigate the effect of variation in forage source and feed particle size of a diet, including interactions, on the amount and the composition of microbial crude protein (CP) in a semi-continuous culture system (Rusitec). Different microbial CP fractions were compared. Five diets with mean forage proportion of 0.88 and different maize silage to grass silage ratios (100 : 0, 79 : 21, 52 : 48, 24 : 76 and 0 : 100) were used. Diets were ground through sieves with a pore size of either 1 or 4 mm, matching the particle size of fine (F) and coarse (C), respectively. Diets were characterised by increasing concentrations of CP and fibre fractions, and decreasing concentrations of starch with ascending inclusion rates of grass silage. Microbial mass was isolated from feed residues after incubation from the liquid phase of the fermenter and from the liquid effluent. The amount of synthesised microbial CP was determined on the basis of 15N balance. It increased quite linearly by the stepwise replacement of maize silage by grass silage, and was higher in C treatments compared to F treatments. Efficiency of microbial CP synthesis (EMPS) was improved from 29 to 43 mg microbial N/g degraded organic matter (OM) by increasing the proportion of grass silage in the diet, but was unaffected by particle size. The N content as well as the profiles of amino acids of the three microbial fractions was affected by diet composition and particle size. The ratio of solid- to liquid-associated microbes was affected by diet composition and feed particle size. The amount and EMPS seemed to be improved by degradation of OM from grass silage and an increasing availability of N. Moreover, the results of this study indicated a shift in the composition of the microbial community caused by variation in forage composition and feed particle size.
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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 | 0.000 | 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".