Estimation of Combining Ability and Gene Action for Improvement Drought Tolerance in Bread Wheat (Triticum aestivum L.) Using GGE Biplot Techniques
Bibliographic record
Abstract
Study of combining ability and gene action for drought tolerance in wheat were carried out using Genotype-by-Environment (GGE) biplot techniques. Eight-parental diallel crosses, excluding reciprocals, were grown in a randomized complete block design with three replications under two different water regimes (irrigated and rainfed) in the Agricultural Research Institute of Sararood, Kermanshah, Iran. Significant differences were found for yield potential (Yp), stress yield (Ys), stress tolerance index (STI), water use efficiency (WUE) and evapotranspiration efficiency (ETE). GGE biplot analysis showed that the parent A, A, A and B were the best general combiners with two additive genes (A1 and A2), for improvement of Y, STI, WUE and ETE under drought conditions, respectively. Parents A and C also exhibited positive GCA for all the studied traits. The crosses (A, D and H) × (C, E, F and G), (A, C and F) × (B, E, H and G), (A, C and E) × (B, G, H and F) and (A, C, G and D) × (F, B, E and H) for Y, STI, WUE and ETE were identified as heterotic groups with different dominant tolerance genes (D1 and D2), respectively. The polygon view of the biplot indicated that combining of A × G and A × C produced the best drought tolerance hybrids for all the traits through integrated the four tolerance genes (A1, A2, D1, and D2).
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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 | 0.001 |
| 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".