On-farm soybean cultivar evaluation for suitability to organic production in southern Manitoba
Bibliographic record
Abstract
Lack of technical knowledge and proper soybean cultivars are barriers for organic farmers to take advantage of increased organic soybean demand in Manitoba from domestic and international markets. The objective of the present study was to evaluate the performance of 12 early season non-GM food grade soybean cultivars under organic management in southern Manitoba. Cultivars were seeded on four organic farms and one transition to organic farm in southern Manitoba in 2014 and 2015. The mean cultivar yield ranged from 1384 to 1807 kg ha-1, with a mean of 1536 kg ha-1. Cultivars ‘Savanna’ and ‘Toma’ were high performers, but exhibited low stability across sites. Partial Least Squares Regression Analysis indicated that soybean mature height, and biomass at R5 positively contributed to final grain yield. Early height positively contributed to biomass at R5 but negatively affected final grain yield. Soil nitrate content negatively contributed to final grain yield. Weed competitiveness was of particular interest in this study. Contrary to previous reports, cultivars that exhibited early season vigour often resulted in lower yields, biomass accumulation, and increased weed presence as compared to other cultivars.
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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 | 0.001 | 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".