Condensed Tannins in Sainfoin: Composition, Concentration, and Effects on Nutritive and Feeding Value of Sainfoin Forage
Bibliographic record
Abstract
ABSTRACT Legume forage is the most economical source of nutrients for ruminants. Sainfoin (Onobrychis viciifolia Scop.) is high nutritive forage growing worldwide and possesses polyphenolics including condensed tannins (CT) that contribute to some of its superior nutritional properties such as improved protein utilization, bloat‐free, and anthelmintic characteristics. This review attempts to capture the latest research in characterizing the impact of polyphenolics on the feeding value of sainfoin with an emphasis on CT. Sainfoin contains a diverse array of polyphenolics and its CT content declines as the plant matures, with an increase in the degree of polymerization and a decreasing proportion of prodelphinidins, resulting in a reduction in biological activity. This forage is best to be utilized between bud to flowering stage to balance the biological activity of CT and biomass yield. Incorporation of sainfoin into alfalfa (Medicago sativa L.) pasture has been effective in reducing alfalfa pasture bloat due to the presence of CT. New sainfoin populations suitable for survival in high‐performance grazing systems have been developed and have demonstrated superior anti bloat activity due to the increased grazing persistence. Fresh sainfoin is the best feed for cattle for maximum effect of CT, but if it needs to be preserved then hay would be better than silage in terms of preservation of the biological activity of CT. Although greater CT content is desirable for this forage in terms of antibloat and antiparasitic activity, sainfoin with CT concentration at about 50 g kg−1 dry matter (DM) offer the best feed value.
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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 | 0.001 | 0.001 |
| 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".