Cross-Canada comparison of the productivity of fodder galega (<i>Galega orientalis</i> Lam.) with traditional herbage legumes
Bibliographic record
Abstract
A study was conducted across Canada to compare the herbage productivity of fodder galega (Galega orientalis Lam.) to that of traditional forage legumes, in order to assess its agricultural potential. Trials were established at latitudes ranging from 45 to 56°N with longitudes from 52°W (St. John's, Newfoundland) to 120°W (Dawson Creek, British Columbia). Herbage productivity was monitored for a maximum of 3 production years. The establishment characteristics of Gale fodder galega were comparable to those of Apica and Beaver alfalfa (Medicago sativa L.) and Altaswede red clover (Trifolium pratense L.), and somewhat superior to those of Dawn Alsike clover (T. hybridum L.) and Leo trefoil (Lotus corniculatus L.). Anik alfalfa (M. falcata L.) was far less uniform and vigorous in its establishment than any of the other species. The average annual dry matter yield of fodder galega ranked third among the seven legumes when averaged over the nine sites; it produced 5545 (SE 95) kg ha−1 compared to 3931 (SE 72) kg ha−1 for Dawn alsike clover, the lowest-yielding crop, and 6673 (SE 114) kg ha−1 for Apica alfalfa, the highest-yielding. The cumulative dry matter yields indicated that Gale galega is at least as well adapted across Canada as the other legumes, except possibly at Saskatoon where the M. sativa alfalfas were far superior to all the other legumes in their ability to establish and thrive. The performance characteristics of Gale fodder galega indicate that it has considerable agricultural potential as an additional, perennial, herbage legume for many regions of Canada, except in the semi-arid continental climate of the central Prairies where its growth may be limited by high air temperature and/or insufficient soil moisture. Key words: Fodder galega, Galega orientalis Lam., goat's rue, herbage production, forage legume
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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 | 0.001 |
| 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 | 0.001 | 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".