Influence of grain type and oil concentration of dried corn distillers’ grain with solubles on ruminal fermentation and in vitro gas production in cattle fed high-concentrate diets
Bibliographic record
Abstract
To determine the effects of grain type (rolled-corn vs. rolled-barley) and dried corn distillers’ grains with solubles (DDGS) oil concentration (low = 4.5% vs. moderate = 7.9%) on ruminal pH, ammonia (NH 3 ) and volatile fatty acid (VFA) concentrations, in vitro enteric methane (CH 4 ) and carbon dioxide (CO 2 ) production, and digestive enzyme activity, eight ruminally cannulated Holstein steers (715 ± 61.4 kg) were used in a 4 × 8 Latin rectangle with a 2 × 2 factorial arrangement of treatments. Diets were offered for ad libitum intake. Experimental periods were 24 d with 7 d of diet adaptation, 7 d of sample collection, and a 10 d transition between periods. No differences were observed for ruminal NH 3 , total VFA concentration, pH, or in vitro concentration of CH 4 or CO 2 after 24 h of incubation among treatments. The lag time for in vitro gas production and degradation was greater (P = 0.03) from steers fed diets containing rolled-corn than rolled-barley. There were grain type × DDGS interactions (P ≤ 0.02) observed for α-amylase and trypsin activity (U L −1 ruminal fluid). Maltase activity (U L −1 ruminal fluid) was greater (P ≤ 0.01) in steers fed diets containing rolled-corn than rolled-barley and in steers fed diets containing low- compared with moderate-oil DDGS. These results indicate that, although ruminal enzyme activity was influenced, feeding different grain types (rolled-corn vs. rolled-barley) or DDGS with differing oil concentration (moderate vs. low) did not negatively influence ruminal fermentation or in vitro CH 4 production.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".