Stockpiling Potential of Perennial Forage Species Adapted to the Canadian Western Prairie Parkland
Bibliographic record
Abstract
Stockpiling perennial forages for fall and winter grazing is not generally practiced on the Prairie Parkland of Canada. The objective was to determine forage species with most potential for stockpiling in this short‐season region. The research was conducted for 3 yr at Lacombe, AB. Plots of adapted forage grasses and alfalfa ( Medicago sativa L.) were clipped in early July. Regrowth forage mass was determined in mid‐September, mid‐October, and the following April. Forage quality measurements included in vitro digestible organic matter (IVDOM), crude protein, water‐soluble carbohydrates (WSC), and acid (ADF) and neutral (NDF) detergent fiber. Overwinter yield losses were lower with grasses (3–35%) than alfalfa (43%). Meadow bromegrass ( Bromus riparius Rhem.) had stable stockpiled yields over both dry (5130 kg ha −1 ) and wet (5450 kg ha −1 ) years and retained nutritive value well into winter and spring. Timothy ( Phleum pratense L.) provided greatest stockpiled yields in years of above‐average rainfall (9700 kg ha −1 ), but protein levels (<70 g kg −1 ) may be lower than desired in some years. Kentucky bluegrass ( Poa pratensis L.) and creeping red fescue ( Festuca rubra L.) had relatively low stockpiled yields (3160–5020 kg ha −1 ). However, quackgrass [ Elytrigia repens (L.) Nevski] yielded well under good rainfall conditions (6180 kg ha −1 ), and dry matter loss (16%) was below average. Spring NDF (644 g kg −1 ) and IVDOM (495 g kg −1 ) concentrations of creeping red fescue were lowest and highest among species, respectively. Creeping red fescue and meadow bromegrass have the best chance of meeting cow nutritive requirements during winter and spring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".