Application of <i>Aegilops tauschii</i>–<i>Triticum aestivum</i> recombinant inbred lines for grain protein content quantitative trait loci detection and wheat improvement
Bibliographic record
Abstract
Grain protein content (GPC) is an important nutritional quality trait of wheat. Aegilops tauschii Coss. is a progenitor of common wheat and has been shown to have high GPC. The objective of this study was to identify quantitative trait loci (QTL) for GPC using A. tauschii–Triticum aestivum L. recombinant lines. An advanced BC2F6 population (112 lines) containing A. tauschii segments was developed using synthetic octaploid wheat (hexaploid wheat Zhoumai 18 × A. tauschii T093), which displayed significant phenotype variances. Two quality traits, GPC and wet gluten, and four yield-related traits, thousand kernel weight, spikelet number per plant, grain number per spike, and grain weight per spike, were evaluated. The results show that the mean GPCs of these lines were significantly higher than those of Zhoumai 18. Correlation and mapping analyses indicated that quality traits were weakly negatively correlated with yield traits. Furthermore, 16 A. tauschii-derived QTL for GPC were detected in the recombinant inbred lines, and four stable QTL that have no significant negative effects on yield and are located within the same marker interval were detected in both environments. Additionally, high-protein, high-yield lines 150228 and 150368 with stable QTL were obtained, and both can be directly utilised for fine mapping of the GPC genes and molecular marker–assisted selection to achieve synergistic improvement of wheat yield and protein content.
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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) | 0.001 | 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 | 0.001 |
| 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".