Recurrent selection for increased protein content in yellow mustard (Sinapis alba L.)
Bibliographic record
Abstract
Increasing protein content is an important objective in breeding high protein oilseed yellow mustard (Sinapis alba L). The objectives of this research were to increase meal protein content, study population variation during three cycles of selection for increased meal protein content, and quantify the relationships of protein with oil and 1000-seed weight. Recurrent selection was employed with half-sib family evaluation in replicated field trials. Meal protein content increased by an average of 1 % per cycle. The correlation between meal protein and seed oil content was negative (r= -0.49 to -0.58). The population shifts, with selection, reflected successful increase of average meal protein content, and an increased frequency of genotypes with high meal protein content. Furthermore, simultaneous selection for meal protein and seed oil content was possible. The correlation between meal protein content and seed weight was positive (r= 0.29-0.39) and thus selecting for increased meal protein content posed no risk of decreasing seed weight in this yellow mustard germplasm.
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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 | 0.000 |
| 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".