The Use of Wild Relatives of Safflower to Increase Genetic Diversity for Fatty Acid Composition and Drought Tolerance
Bibliographic record
Abstract
Wild relatives of safflower (Carthamus tinctorius L.) may contribute genes to improve cultivated species under water stress conditions. This study was conducted to increase genetic diversity of safflower for agromorphological traits and fatty acid profiles using interspecific hybridization. Three species—C. tinctorius, C. palaestinus Eig., and C. oxyacanthus M. Bieb.—were used to develop three segregating populations of C. tinctorius × C. palaestinus (TP), C. oxyacanthus × C. palaestinus (OP), and C. oxyacanthus × C. palaestinus (TO). Seventy‐three lines, along with the three parental species, were evaluated for agromorphological traits under water stress and nonstress conditions in F3 and F4 generations during 2 yr. Fatty acid analysis of interspecific progenies showed occurrence of transgressive segregation. The results showed that mean values of seed yield for TP and TO progenies, where C. tinctorius was one of their parents, were higher than mean value of seed yield for OP that derived from the two wild species. High genetic variation was observed for seed yield, capitulum diameter, and phenological traits in interspecific populations under both moisture conditions. Indirect selection for flowering and seed yield components under water deficit conditions was most efficient to improve seed yield. Results indicated that gene introgression from wild relatives of safflower into the cultivated gene pool increased genetic variation for the measured traits and allowed identifying superior genotypes for future breeding programs.
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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".