Identification of quantitative trait loci for seedling root traits from Tibetan semi-wild wheat (<i>Triticum aestivum</i> subsp. <i>tibetanum</i>)
Bibliographic record
Abstract
As a primitive hexaploid wheat resource distributed only in Tibet, Tibetan semi-wild wheat (Triticum aestivum subsp. tibetanum Shao) possesses unique characteristics that could be exploited in wheat breeding programs. Its good root system could offer a stable platform for above-ground components. To detect possible excellent locus for root traits from Tibetan semi-wild wheat, we identified QTLs for root traits using a recombinant inbred line population derived from a cross between Tibetan semi-wild wheat Q1028 and Zhengmai 9023. A total of 15 QTLs on eight chromosomes were detected, including four major QTLs, QMrl.sau-7B, QTrl.sau-4B, QAd.sau-7A, and QSa.sau-4B. The phenotypic variation explained by each of these QTLs ranges from 5.67% to 16.68%. Positive alleles of six QTLs were derived from Q1028. Several novel QTLs for root traits were identified. In addition, significant correlations were detected amongst root traits and agronomic traits. Taken together, these results suggest that Tibetan semi-wild wheat and the newly identified novel QTLs could be useful in future breeding programs.
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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 | 0.000 | 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 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".