Comparison of Chemical Composition and Rumen Degradation Kinetics of Three Forages: Whole Plant Barley, Whole Plant Foxtail Millet and Grass-Legume Hay
Bibliographic record
Abstract
The objective of this study was to determine the chemical composition and in situ rumen degradability of whole plant barley (Hordeum vulgare), whole plant foxtail millet (Setaria italica) and smooth bromegrass (Bromus inermis Leyss)-alfalfa (Medicago sativa L.) (grass-legume) hay, collected during a companion field grazing study. Relative to grass-legume hay, barley and millet were higher (P = 0.05) in crude protein (CP) and soluble CP, and lower (P = 0.02) in neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin, neutral detergent insoluble CP, and acid detergent insoluble crude protein. The potentially undegradable fraction of CP averaged 32% lower for barley and millet, compared to grass-legume hay, while CP soluble fraction was 36 and 64% higher (P < 0.05) for barley and millet, respectively, than for grass-legume hay. Millet had the highest NDF degradability (P = 0.03) and grass-legume hay the least. Barley and millet had greater (P = 0.02) effective degradability of dry matter (DM), CP, and NDF than grass-legume hay. Millet had the highest (P = 0.01) degradable and lowest undegradable fractions of DM and NDF, and lowest soluble fraction of NDF and rate of CP degradation (P < 0.05). Results indicate that whole plant barley and millet have greater nutritive value than grass-legume hay and may be suitable annual forages for extensive grazing.
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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) | 0.000 | 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 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".