A review of the genetic, physiological, and agronomic factors influencing secondary dormancy levels and seed vigour in <i>Brassica napus</i> L.
Bibliographic record
Abstract
Dormancy in canola ( Brassica napus L.) is a complicated process due to many overlapping and interacting factors affecting the absolute dormancy levels. It is unknown if seed dormancy plays a role in the poor stand establishment of planted canola but given that germination and dormancy are two ends of the same continuum, it has been suggested that dormancy may be a culprit of poor establishment. This review synthesizes literature pertaining to secondary dormancy in B. napus and the interaction of genetic, physiological, environmental, and agronomic factors. Seed germination and vigour and the interaction with dormancy are also addressed. The persistence of volunteer canola seed in the soil seedbank is a result of the induction of canola seed into secondary dormancy under adverse environmental conditions such as low temperature or low light. Genetics is a major influencing factor on absolute secondary dormancy (∼50%) in canola. Plant hormones abscisic acid and gibberellic acid and their interactions also influence dormancy with highly dormant genotypes having increased abscisic acid concentration in the seed. Seed sugars, seed storage proteins, glucosinolate content, and growth habit are all additional factors affecting absolute dormancy in B. napus. Furthermore, maternal environmental conditions affect dormancy levels. In addition to genetic, physiological, and environmental factors, farming practices such as harvest timing, and tillage regimes can influence secondary dormancy of canola seed that has entered the seedbank unintentionally. Given the documented high heritability of secondary dormancy, it is feasible to reduce secondary dormancy in canola cultivars; however, consideration of all interacting factors must be given.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".