Comparison of Certified and Farm‐Saved Seed on Yield and Quality Characteristics of Canola
Bibliographic record
Abstract
Relatively high seed prices and low canola (Brassica napus L.) grain prices created a controversy over using farm‐saved seed from hybrids. Agronomic implications of saving seed from a canola crop were investigated by planting certified seed and saved‐seed of an open‐pollinated and a hybrid canola cultivar at eight site‐years in Saskatchewan and Alberta, Canada. In one series of experiments cultivars and seed rates were compared, while in another experiment seed treatments and use of sized seed were investigated. Results tend to agree with similar studies with other crops where agronomic performance was unaffected when farm‐saved seed from open‐pollinated crops was used, but declined when this practice was used with hybrid cultivars. Using farm‐saved seed from hybrid canola (HY‐FSS) compared with hybrid certified seed (HYC) reduced plant population density by 16 to 18% at the time of crop maturity and yield by an average of 12%, delayed maturity by 2 d, reduced seed oil content by 5 g kg−1, and resulted in a small increase in incidence of green seed. Yield and quality loss associated with using HY‐FSS could not be recovered by using increased seeding rates or by sizing and planting only large seed. The inability to use the most effective combined insecticide plus fungicide seed protectant treatments with farm‐saved seed resulted in a 20% yield loss compared with treated certified hybrid seed. Our study demonstrates the production risks of growing HY‐FSS on plant density, yield, maturity, and seed oil content.
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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 | 0.000 |
| 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".