Chemical composition and ruminal nutrient degradabilities of fresh and ensiled Kura clover (<i>Trifolium ambiguum</i> M.B.)
Bibliographic record
Abstract
Kura clover is a perennial rhizomatous forage legume mainly used for grazing in permanent pastures. A study was conducted to determine the ensiling potential of Kura clover by comparing the chemical composition and ruminal nutrient degradabilities of fresh and ensiled forage of two cultivars (Cossack and Endura). Ensiling characteristics were determined by ensiling forages in mini-silos for 50 d. Ruminal nutrient degradabilities of fresh and ensiled forages were determined by the nylon bag technique using two lactating cows fitted with ruminal cannulas. Results showed that silages of both cultivars were well preserved as indicated by low pH and high lactic acid concentration. Cultivar had little effect on the chemical composition of Kura clover silage. However, ensiling increased (P < 0.05) soluble protein and non-protein nitrogen (NPN) and reduced (P < 0.05) neutral and acid detergent insoluble protein fractions. Ensiling increased NPN and reduced true protein by 87 and 29%, respectively. Results of the in situ study indicated that cultivar had no effect on effective ruminal degradability of dry matter (DM), crude protein (CP), an d neutral detergent fiber (NDF). Relative to fresh forage, ensiled Kura clover had similar effective ruminal degradability of DM (712 g kg-1 of DM) and NDF (417 g kg-1 of NDF) but a higher (P < 0.05) effective ruminal degradability of CP (806 vs. 725 g kg-1 of CP). It was concluded that Kura clover may be preserved as silage with minimal alterations in forage quality. These findings will increase the acceptability of Kura clover by widening possible utilizations. Key words: Forage quality, Kura clover (Trifolium ambiguum M.B.), protein fractions, ruminal degradability, 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) | 0.000 | 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".