Agronomic analysis of the forage yield, nutritional value, species compatibility, and winter survival rates of sainfoin (Onobrychis viciifolia Scop.) and grasses mixtures
Bibliographic record
Abstract
Sainfoin (Onobrychis viciifolia Scop.) is a highly palatable perennial forage legume that is gaining renewed interest in western Canada since it does not cause frothy bloat in grazing ruminants. It is adapted to western Canadian growing conditions and yields similar to other forage legumes, but slightly less than alfalfa. Despite its nutritional and environmental benefits, sainfoin use in western Canada is limited due to agronomic restrictions compared to alfalfa, and high seed cost. This three-year research study evaluated two sainfoin cultivars, Melrose and AAC Mountainview, as monocultures and in mixtures with three grass species, crested wheatgrass (Agropyron cristatum L.) cv. AC Goliath, meadow bromegrass (Bromus riparius Rehm.) cv. Armada, and hybrid bromegrass (Bromus riparius x Bromus inermis) cv. AC Knowles, under different harvest regimes to assess reduced seeding rate of sainfoin and determine agronomic performance of sainfoin-grass mixtures in different soil zones. A common industry mixture, Beaver alfalfa (Medicago sativa L.)-Armada meadow bromegrass was included for comparison. The sainfoin-grass mixtures compared favorably to the common mixture, with acceptable winter survival, forage yields, species compatibility, and nutritive value for use in the western Canadian beef industry. Melrose in mixtures with crested wheatgrass cv. AC Goliath at a 30:70 seeding rate performed well in the Dark Brown soil zone. Melrose or AAC Mountainview in mixtures with crested wheatgrass cv. AC Goliath at a 30:70 seeding rate performed well in the Black soil zone. Melrose or AAC Mountainview in mixtures with crested wheatgrass cv. AC Goliath at the 50:50 seeding rate performed well in the Brown soil zone. Melrose and AAC Mountainview in mixtures with crested wheatgrass at the 70:30 seeding ratio often had the greatest nutritional quality. However, the nutritional value of all the sainfoin-grass mixtures was similar within each experimental site. To reduce seed cost, seeding rate of sainfoin monocultures could be reduced by at least 50% while maintaining forage yields. Melrose at 50% of the current recommended seeding rate performed well in the Dark Brown soil zone, Melrose or AAC Mountainview at 25% of the current recommended seeding performed well in the Black soil zone, and Melrose or AAC Mountainview at 50% of the current recommended seeding rate performed well in the Brown soil zone. Near infrared reflectance spectroscopy was used to successfully predict legume proportion and crude protein in sainfoin-grass mixtures with high accuracy. Calibration equations developed for neutral detergent fiber predictions had medium to high accuracy, but poor accuracy for acid detergent fiber predictions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.032 | 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".