Use of Rutabaga (Brassica napus var. napobrassica) for the Improvement of Canadian Spring Canola (Brassica napus)
Bibliographic record
Abstract
Spring-type oilseed Brassica napus L., commonly known as canola, has become the cornerstone of agricultural production in Western Canada, with the total acreage seeded increasing in each production year over the past two decades. However, the narrow genetic base of spring B. napus canola coupled with the ever-increasing acres planted have led to the emergence of clubroot disease, caused by Plasmodiophora brassicae, in the canola production areas. Brassica napus var. napobrassica, or rutabaga, is a biennial fodder-type Brassica species that has the potential to not only serve as a source of genetic diversity for B. napus, but also to provide strong resistance to P. brassicae pathotypes prevalent in the canola fields in Western Canada. An F2-derived population of Rutabaga-BF × A07-26NR and a three-way cross-derived population of (A07-45NR × Rutabaga-BF) × A07-26NR were evaluated for different agronomic and seed quality traits, including resistance to P. brassicae pathotypes prevalent in Western Canada. The three-way cross and F¬2-derived populations both produced families that exceeded the checks for agronomic and seed quality traits for both the 2013 and 2014 yield trial experiments. The three-way cross-derived population produced several families with stable, non-segregating resistance to P. brassicae pathotype 3, as well as newly emerging pathotypes found in northern Alberta. Genetic diversity analysis showed that both the three-way cross and F2-derived populations produced families of canola-quality B. napus plants with spring growth habit that were genetically similar to the parent Rutabaga-BF, indicating that rutabaga is a viable germplasm source for broadening the narrow genetic base of spring-type B. napus.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".