338 Effect of Calcium Oxide Treatment of Barley Straw on In Vitro & In Situ Digestibility.
Bibliographic record
Abstract
Improving the nutritional value of low quality forages is one strategy to lower beef cattle feed costs. These experiments examined the extent to which calcium oxide (CaO) can improve the digestibility of barley straw, compared to barley and corn silage. Barley straw was hydrated to 50% moisture and CaO was added at 5% of DM. Dry matter and NDF digestibility were measured in vitro and in situ. Cannulated heifers (4) were fed a wheat-based diet with either barley silage or barley straw. The in vitro study utilized inoculum, combined by diet, to incubate forage samples for 30h. In situ degradation of forages was measured by incubating bags in the rumen for 9 time points up to 240h, followed by kinetic analysis. CaO treatment reduced the NDF content of barley straw by 15.1%. CaO did not improve (P=0.99) the in vitro NDFD of straw. CaO improved (P<0.01) in vitro true DMD of barley straw from 48.4% to 55.8% but was still lower than that of barley or corn silage. CaO improved the in situ digestibility of barley straw. CaO increased (P=0.03) the DM potentially degradable fraction of straw, but it was still lower than barley and corn silage. Effective rumen degradability (ERD) of CaO straw was also improved (P<0.01), but remained lower than silages. Feeding a grain diet with straw as opposed to silage improved (p<0.01) kd of forages. A similar response occurred in vitro, where inoculum from heifers fed the grain-straw diet tended to have higher NDFD (P=0.07) and TDMD (P=0.06). CaO improved the in vitro and in situ DMD of barley straw, but no effect was observed on in vitroNDFD, likely because of the reduced NDF content of the original substrate. CaO treatment improved ERD but it did not exceed the value of barley or corn silage.
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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 | 0.000 |
| 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".