Leaf and Stem Mass Characteristics of Cool‐Season Grasses Grown in the Canadian Parkland
Bibliographic record
Abstract
Grasses adapted to both hay and pasture are lacking in the prairie parkland. ‘Regar’ meadow bromegrass (Bromus riparius Rhem.), ‘Manchar’ smooth bromegrass (B. inermis Leyss.), S9044 (a smooth–meadow bromegrass cross), common meadow foxtail (Alopercurus pratensis L.), and ‘Kay’ orchardgrass (Dactylis glomerata L.) were evaluated for traits useful in dual purpose grass species at early (late May), late (late June), and regrowth (early September) harvests. Herbage, leaf, and stem nutritive value; mass; and leaf/stem ratio were determined. Differences among species were related more to herbage mass and morphology than to leaf and stem quality. Early harvest orchardgrass herbage mass was low at 55% of meadow foxtail (2.9 Mg ha−1). However, stem content of meadow foxtail represented 60% of early herbage mass, limiting its potential. Regrowth mass of meadow bromegrass, S9044, and orchardgrass exceeded 2.5 Mg ha−1, whereas smooth bromegrass and meadow foxtail were as low as 2.1 Mg ha−1. Regrowth leaf mass of the former species exceeded 1.9 Mg ha−1. Late herbage mass of smooth bromegrass was always greater than the other species. Leaf acid detergent fiber (ADF) of S9044 and smooth bromegrass was lower (range 189–242 g kg−1) than meadow bromegrass (range 217–284 g kg−1). By contrast, late and regrowth harvest stem ADF of meadow bromegrass was lower (range 237–360 g kg−1) than S9044 (range 257–366 g kg−1). Variation among Bromus types for late and regrowth yield, and leaf fiber may influence management strategies.
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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 | 0.001 | 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".