Characterization of agronomic and quality traits and HSW-G5 compositions from the progenies of common wheat (Triticum aestivum L.) with different protein content
Bibliographic record
Abstract
High molecular weight glutenin subunits (HMW-GS) play an essential role in wheat processing quality. In this study, we evaluated the genetic pattern with HMW-GS composition between generations and examined whether agronomic and quality traits were correlated with each other. A wheat (Triticum aestivum L.) cultivar with high protein content and 2 cultivars with low protein content were subjected to a reciprocal cross. Sixteen agronomic and 4 quality characteristics were investigated. A total of 216 seeds from each F2 generation were chosen randomly and analyzed for HMW-GS composition using sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Agronomic and quality characteristics were not significantly different between reciprocal crosses, indicating no cytoplasmic effect on the characteristics studied. The separation ratio of 2 HMW-GS loci was 9:3:3:1, indicating no linkage between any 2 loci. The novel HMW-GS N was detected in cultivar R145, which did not follow the Mendelian segregation ratio. A Glu-A1a(1) band was not detected in 1 individual from Tian8901xR145. Average grain weight per spike was significantly correlated with quality characteristics and may be a suitable criterion for selecting high protein content in wheat 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".