Forage quality of seeded native grasses in the fall season on the Canadian Prairie Provinces
Bibliographic record
Abstract
There is renewed interest in re-seeding native grasses in the prairie region of western Canada but there is limited information on their forage quality for fall grazing. We evaluated forage quality in early fall of nine native and one introduced grass species for 2 to 4 yr at five locations. The neutral detergent fiber (NDF) was high due to the advanced growth stage of the plants but varied among grass species at all sites . Western wheatgrass, Pascopyrum smithii, exhibited the lowest NDF and highest in vitro organic matter digestibility (IVOMD). Northern wheatgrass, Elymus lanceolatus, exhibited the highest crude protein while western wheatgrass ranked second highest for crude protein. Indiangrass, Sorghastrum nutans, exhibited the highest P and Ca concentrations, while green needle grass, Nasella viridula, and mammoth wildrye, Leymus racemosus, exhibited the lowest concentrations. Acid detergent fiber (ADF) was not highly correlated to IVOMD, presumably due to the mature phenological stage at sampling. Western wheatgrass forage was nutritionally adequate to maintain a dry beef cow during the second trimester of pregnancy. Other species did not “cure on the stem” as had been previously reported and would require supplementary energy and protein to be utilized for fall pastures. Key words: Forage quality, fiber, protein, P, C4 grasses, C3 grasses
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".