Canola Genotypes and Harvest Methods Affect Seedbank Addition
Bibliographic record
Abstract
Seed loss in canola [ Brassica napus L., B. rapa L., and B. juncea (L.) Czern. & Coss.], which includes seed shatter and seeds in unopened dropped pods, leads to yield reductions and seed dispersal into the soil seedbank. The volunteer canola can then become a weed in the subsequent crops and cause yield losses. The objective of this study was to evaluate canola genotypes, harvest methods, and commercial pod sealant products to reduce canola seedbank addition. Field trials were conducted at Saskatoon, SK, Canada, in 2010 and 2011. The effect of harvest methods (untreated direct harvested [DH], Pod Ceal treated DH, Pod‐Stik‐treated DH, and windrowed) on seed loss in four B. napus genotypes (5440, 45H26, 5020, 4362), and a canola quality B. juncea (8571) were evaluated. Results showed that there were differences in seedbank addition among the canola genotypes in each year. The B. napus Genotypes 5440 and 45H26 were found to have lesser seedbank addition than other genotypes. Neither of the two pod sealant products reduced seed loss in canola. The windrowed canola had higher seedbank addition than the DH canola. This study indicated that direct harvesting can be a viable option for canola in western Canada and canola seedbank addition could be minimized by growing genotypes with improved shattering tolerance.
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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".