Bibliographic record
Abstract
Rahman, M. and McVetty, P. B. E. 2011. A review of Brassica seed color. Can. J. Plant Sci. 91: 437-446. Canola oil has excellent fatty acid composition and low saturated fat levels, and canola meal has protein with excellent amino acid composition. Canola seed quality can be further improved by the development of higher oil, higher protein and lower fiber content germplasm through the development of yellow seeded lines. While there is no naturally occurring yellow seeded B. napus, yellow seeded mutants that have arisen in nature can be readily indentified in Brassica rapa, B. juncea and B. carinata species. Brassica napus is widely cultivated in Asia, Australia, Europe and North America. Yellow seed in Brassica species is associated with seed that has higher oil and protein content and lower fiber content. Because of these seed quality advantages of yellow seeded lines, plant breeders around the world have been attempting to develop yellow seeded B. napus genotypes using crosses involving naturally occurring yellow seeded Brassica species. Seed color in B. rapa is controlled by two genes. Two duplicate genes are responsible for seed color in B. juncea. In B. carinata, one repressor gene represses the seed color gene resulting in yellow seed, while the absence of the repressor gene results in brown seed. Several yellow seeded B. napus genotypes have been developed and in most cases three genes are reported as being are responsible for seed color. Numerous different molecular markers for seed color genes in B. rapa, B. juncea and B. napus have been developed for use in marker-assisted selection in plant-breeding programs. These molecular markers can also be used to clone the Brassica seed color gene(s) and then create transgenic yellow seeded B. napus genotypes. This review summarizes past and current research on Brassica seed color breeding, genetics and genomics/biotechnology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".