Effect of Harvest Timing on Dormancy Induction in Canola Seeds
Bibliographic record
Abstract
Seedbank persistence in canola seeds is related to their potential to develop secondary dormancy. This can result in volunteer weed problems many years after canola production. The potential to be induced into secondary dormancy is controlled by both the canola genetics and the environment of the mother plant. However, the effect of time of harvesting on secondary dormancy potential is not known. The objective of this study was to determine the effect of harvest timing on potential to develop seed dormancy in canola. Six harvest samples were collected weekly from two canola genotypes (5440 and 5020) starting from 10 to 20% seed color change on the main stem until they were fully ripened. Freshly harvested seeds of 5440 and 5020 showed 13 and 16% primary dormancy at 32 and 33 d after flowering (DAF), respectively, but dormancy decreased with harvest timings and no dormancy was observed when seeds were fully mature (78 DAF). After dormancy induction, 10% of 5440 seeds were dormant at 32 DAF, but 94% of seeds were dormant at 78 DAF. Similarly, 70% of 5020 seeds were dormant at 33 DAF, but 90% of seeds were dormant at 68 DAF. Thus, seeds had lower potential to secondary dormancy at early development but have a high potential to secondary dormancy induction at full maturity. This study suggests that windrowing these canola genotypes at the recommended time (60% seed color change on the main stem) may reduce ability of the seed to develop secondary dormancy and thus reduce the persistence of seeds in the soil seedbank.
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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 | 0.000 | 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 | 0.001 |
| 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".