Genetic control and identification of QTLs associated with visual quality traits of field pea (<i>Pisum sativum</i> L.)
Bibliographic record
Abstract
Visual quality of field pea (Pisum sativum L.) is one of the most important determinants of the market value of the harvested crop. Seed coat color, seed shape, and seed dimpling are the major components of visual seed quality of field pea and are considered as important breeding objectives. The objectives of this research were to study the genetics and to identify quantitative trait loci (QTLs) associated with seed coat color, seed shape, and seed dimpling of green and yellow field peas. Two recombinant inbred line populations (RILs) consisting of 120 and 90 lines of F(5)-derived F(7) (F(5:7)) yellow pea (P. sativum 'Alfetta' × P. sativum 'CDC Bronco') and green pea (P. sativum 'Orb' × P. sativum 'CDC Striker'), respectively, were evaluated over two years at two locations in Saskatchewan, Canada. Quantitative inheritance with polygenic control and transgressive segregation were observed for all visual quality traits studied. All 90 RILs of the green pea population and 92 selected RILs from the yellow pea population were screened using AFLP and SSR markers and two linkage maps were developed. Nine QTLs controlling yellow seed lightness, 3 for yellow seed greenness, 15 for seed shape, and 9 for seed dimpling were detected. Among them, five QTLs located on LG II, LG IV, and LG VII were consistent in at least two environments. The QTLs and their associated markers will be useful tools to assist pea breeding programs attempting to pyramid positive alleles for the traits.
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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) | 0.000 | 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".