Severity of rolling reconstituted high-moisture barley on ensiling characteristics and in vitro ruminal fermentation
Bibliographic record
Abstract
Barley grain sources with variable kernel sizes makes adequate and consistent processing of kernels challenging. This study evaluated how the severity of processing for reconstituted high-moisture (65% on DM basis) barley (RHB) affects ensiling characteristics and in vitro ruminal fermentation. Three independent sources of light (<630 g/500 mL) and heavy (>670 g/500 mL) barley were blended to create 4 sources of variable kernel sized barley (646 g/500 mL). Reconstituted high-moisture barley rolled using a 1.40-mm gap width for finely processed RHB (RHBF), a 1.86-mm gap width for medium processed RHB (RHBM), or a 2.31-mm gap width for coarsely processed RHB (RHBC) was ensiled for 1 or 5 mo with dry rolled barley (DRB; roller gap width 1.86 mm) used as a control. The 1-mo RHB and the DRB were further evaluated using the rumen in vitro simulation technique (RUSITEC) to investigate the effects of severity of processing for RHB on ruminal fermentation, and gas, methane, and microbial protein production. Using a randomized complete block design (n = 4), 16 fermenters from 2 RUSITEC apparatuses were used to assess the 4 sources and 4 processing treatments. The addition of water increased kernel width before rolling and resulted in increased kernel length, width, and thickness for RHB relative to DRB. Increasing processing severity for RHB linearly increased kernel width. The percentage of fine particles (<1.18 mm) was greater for DRB than RHBF, but did not differ by processing severity for RHB. Dry matter, OM, and starch disappearance were not different between DRB and RHBF, but linearly increased with increasing processing severity for RHB. Fermenter pH tended to be less for DRB relative to RHBF. In conclusion, the reduction in fine particles with the addition of water for RHB may prevent a decline in fermenter pH and when processed to achieve the same processing index using a smaller roller gap width, yielded similar DM and OM disappearance suggesting a lesser risk for low ruminal pH without compromising digestibility.
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".