Chemical composition and ruminal nutrient degradability of fresh and ensiled amaranth forage
Bibliographic record
Abstract
BACKGROUND: Amaranth is a crop with potential as a source of forage for ruminants that has not been well characterized. A study was conducted to determine the impact of ensiling on the nutritional quality and ruminal degradability of forage from two amaranth cultivars adapted to North America (i.e. Plainsman and D136). In particular, quantification and some microscopic characterization of oxalate found in amaranth were performed as it is an antiquality compound of concern. RESULTS: There were limited interactions between cultivars and ensiling for most variables. Differences in chemical composition between amaranth cultivars were also limited. Ensiling reduced non-structural carbohydrate and true protein contents. The proportion of acid detergent protein was high in fresh and ensiled forages of both cultivars (average of 177 g kg(-1) crude protein). Total oxalate content averaged 30 and 25 g kg(-1) in fresh and ensiled forages respectively. Ensiling reduced soluble oxalate content. Crystals observed in amaranth were calcium oxalate druses found mostly in idioblast cells in leaf mesophyll and parenchyma of primary and secondary veins. In situ ruminal degradability data indicated that both fresh and ensiled amaranth are highly degradable in the rumen. CONCLUSION: This study confirms that amaranth is a suitable forage for ruminant animals. Its chemical composition is comparable, for most variables, to that of other commonly used forage species.
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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".