QTL mapping of seed-quality traits in sunflower recombinant inbred lines under different water regimes
Why this work is in the frame
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Bibliographic record
Abstract
The objectives of the present research were to determine the effects of water stress on seed-quality traits and to map QTLs controlling the studied traits under two different water treatments in a population of sunflower recombinant inbred lines (RILs). Two experiments were conducted in greenhouse and field conditions, each with well-watered and water-stressed treatments. The experiments consisted of a split-plot design (water treatment and RIL) with three blocks. Analyses of variance showed significant variation among genotypes, and a water treatment x genotype interaction was also observed for most of the traits. Two to 15 QTLs were found, depending on trait and growth conditions, and the percentage of phenotypic variance explained by the QTLs ranged from 5% to 31%. Several QTLs for oil content overlapped with QTLs for palmitic and stearic acid contents in all four conditions. An overlapping region on linkage group 3 (QTLs 2.OC.3.1 and 4.SA.3.1) was linked to an SSR marker (ORS657). A principal component analysis was performed on four fatty acid traits. Two principal components, P1 and P2, were used for QTL analysis. This method improved the ability to identify chromosomal regions affecting the fatty acids. We also detected the principal-component QTLs that did not overlap with the fatty acid QTLs. The results highlight genomic regions of interest in marker-based breeding programmes for increasing oil content in sunflower.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it