Seasonal patterns of forage quality in six native forb species
Bibliographic record
Abstract
The forage value of native forbs is rarely considered in pasture mixtures, even though such species can make up a substantial proportion of the diet of cattle on native rangelands. Incorporating non-leguminous forbs into pasture grazing systems can provide additional ecosystem services such as pollination habitat, and ideally those forbs would also provide some forage value. We therefore assessed the seasonal variation in protein and fiber [neutral detergent fiber (NDF) and acid detergent fiber (ADF)] content of six common western Canadian native forb and sub-shrub species: yarrow (Achillea millefolium), smooth aster (Symphyotricum laeve), prairie crocus (Pulsatilla patens), prairie rose (Rosa arkansana), Canada goldenrod (Solidago canadensis), and American vetch (Vicia americana). The legume V. americana displayed the highest protein followed by S. canadensis and S. laeve. V. americana also has the highest fiber concentration through the growing season. S. canadensis and S. laeve had lower fiber content; thus, making them a good choice for addition in seed mixes to meet the energy and nutrient requirements of cattle. Forb protein and fiber content showed opposite trends during the growing season. Crude protein decreased while NDF and ADF increased as a general pattern tied to physiological stage and degree of senescence. The promising nutritional profile of some forb species suggests that these species should be considered in pasture mixes.
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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 | 0.000 |
| 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".