Assessment of seed shattering resistance and yield loss in five oilseed crops
Bibliographic record
Abstract
Use of appropriate harvest management can minimize the yield loss of crucifer crops due to seed and pod shattering. This study determined the difference among five canola/mustard species in the degree of resistance to seed shattering and yield losses. Sinapis alba yellow mustard AC Base, Brassica juncea canola Amulet, Brassica juncea mustard Cutlass, Brassica rapa canola Hysyn, and Brassica napus canola InVigor 2663 were grown at Star City, Scott and Swift Current, SK, from 2004 to 2006. Seed yield was highest for napus canola (2146 kg ha -1 ), followed by juncea mustard (1971 kg ha -1 ) and juncea and rapa canola, while alba mustard (1547 kg ha -1 ) was the lowest. Straight combining compared with swathing resulted in 13% greater seed yield for juncea canola and juncea mustard, and 7% greater for rapa canola, while napus canola did not show yield difference between the two operation regimes. Under high shattering conditions, juncea mustard shed about 400 pods m -2 , significantly greater than the four other species. Rapa canola had the lowest number of shed pods. Juncea mustard and napus canola had largest yield loss (about 7% of the total seed yield) during straight combining, followed by alba mustard (5%), and rapa and juncea canola (< 4%). Selection of shattering resistant species and use of straight combining can minimize seed yield losses in the production of crucifer oilseed crops. Key words: Brassica napus, Brassica rapa, Brassica juncea, Sinapis alba, swathing, straight–combine
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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".