Sainfoin production in western Canada: A review of agronomic potential and environmental benefits
Bibliographic record
Abstract
Abstract Sainfoin (Onobrychis viciifolia) is a forage legume of renewed interest in western Canada, with equally weighted advantages and disadvantages. In agronomic attributes, sainfoin is, at best, equal in yield, crude protein content and persistence to alfalfa (Medicago sativa). Sainfoin is equally or more palatable than alfalfa to ruminants, with comparable levels of animal productivity per unit forage consumed. The advantages it has compared to alfalfa include the following: (a) mitigation of frothy bloat; (b) reduced ammonia emissions (more faecal nitrogen (N) and less urinary N); (c) equal or better N retention by ruminants; and (d) anthelmintic protection from intestinal parasites. These advantages may be attributed to the presence of condensed tannins (CT), in legumes such as sainfoin. Emphasis on agronomic characteristics in breeding programmes appears to have led to the inadvertent reduction in the efficacy ofCTcharacteristics. Persistence of sainfoin appears to be dependent on minimal pressure from competing plants, harvest or grazing, and good growth conditions from mid‐summer into fall, allowing for adequate root reserves for survival. It is possible that judicious use of glyphosate in late season might lessen competition in that critical period as sainfoin is more glyphosate‐tolerant than alfalfa. Otherwise, sainfoin may be best considered a short‐lived forage and best adapted for early season harvest or grazing to eliminate the risk of bloat.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".