Comparison of barley silages with varying digestible fiber content to corn silage on rumen fermentation characteristics and microbial protein synthesis using RUSITEC
Bibliographic record
Abstract
The objectives of this study were to assess the magnitude of differences among barley silages with different in vitro neutral detergent fiber digestibility (ivNDFD) in comparison with corn silage in (1) predicted carbohydrate digestibility, (2) rumen fermentation characteristics, and (3) microbial protein synthesis using rumen simulation technique (RUSITEC). The experiment was carried out in a completely randomized block design with four treatments. The four whole-plant silages utilized in this study were CS-TMR = corn silage (30 h ivNDFD = 32%), HNDFD-TMR = barley silage with high ivNDFD (30 h ivNDFD = 37%), INDFD-TMR = barley silage with intermediate ivNDFD (30 h ivNDFD = 28%), and LNDFD-TMR = barley silage with low ivNDFD (30 h ivNDFD = 26%). Results from RUSITEC showed that nutrient disappearance, rumen fermentation characteristics, and microbial protein synthesis did not differ among diets that contained different varieties of barley silage (P > 0.1). However, CS-TMR tended to have a higher microbial protein yield than all barley silage diets (P = 0.06). These results show higher ivNDFD of barley silage may not necessarily correspond with greater impact on rumen fermentation and microbial protein synthesis. However, feeding the corn silage had higher microbial protein synthesis in the RUSITEC and might enhance the dairy cattle performance compared with barley silage.
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 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) | 0.000 | 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) | 0.001 | 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".