Selection criteria for assessing drought tolerance in a segregating population of flax (Linum usitatissimum L.)
Bibliographic record
Abstract
Using plant genotypes adaptable to water-deficit stress is an optimal strategy in sustainable agriculture. This study was conducted to assess the selection criteria for identifying high yielding drought-tolerant F2-derived F3 flax families from a cross between Iranian genotype KO37 and the Canadian genotype SP1066. One hundred and nineteen F2:3 lines were evaluated under drought stress and non-stress conditions using an 11 × 11 lattice design with three replications. Sixteen drought tolerance indices adjusted based on grain yield under drought stress and non-stress conditions were calculated. The presence of high variability for grain yield and irrigation water use efficiency in parental lines and F2:3 families under both conditions indicated that the F2:3 population or its advanced generations can be used in selection programs to increase drought tolerance and also to identify quantitative trait loci and genes related to grain yield and drought tolerance in flax. The results of biplots based on the PC1 and PC2 and triplot analysis based on the stress tolerance index and grain yield in both stress and non-stress conditions introduced 13 families as the most promising families for drought tolerance, and therefore, their advanced generations can be used in future breeding programs to improve drought tolerance in flax.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".