Genetic control and QTL analysis of cotyledon bleaching resistance in green field pea (<i>Pisum sativum</i>L.)
Bibliographic record
Abstract
Resistance to bleaching is an important factor for quality grading of Canadian green field pea and an important selection criterion in green pea improvement. This research was conducted to determine the genetic control of bleaching resistance in green peas using 90 recombinant inbred lines (RILs) derived from a cross between cultivars Orb and CDC Striker. These lines were evaluated under field conditions for two years in two locations in Saskatchewan, Canada. Harvested whole seeds and cotyledons were evaluated for greenness using the Hunter Lab colorimeter before and after exposure to a high light intensity accelerated bleaching treatment. The RILs were genotyped using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) molecular markers. Heritability estimates for whole seed and cotyledon greenness were moderate (0.72 and 0.69, respectively) and increased when assessed after exposing whole seeds and cotyledons to accelerated bleaching conditions (0.83 and 0.82, respectively). The genetic linkage map constructed based on a total of 224 AFLP and SSR markers spanned over 890 cM of the pea genome. Multiple QTL mapping detected major QTLs on LG IV and LG V as well as location- and year-specific QTLs on LG II and LG III associated with green cotyledon bleaching resistance in field pea. The results demonstrated the importance of the seed coat in protecting the cotyledons from bleaching.
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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".