Detection of quantitative trait loci for paste viscosity characteristics based on the doubled haploid progeny from a cross between two Chinese wheat varieties
Bibliographic record
Abstract
In order to understand the genetic basis of starch pasting viscosity characteristics (the RVA profile, which is produced by the Rapid Visco Analyser) of wheat grain samples, a doubled haploid (DH) population (Huapei 3 × Yumai 57; Yumai 57 is superior to Huapei 3 for RVA profile parameters) and a linkage map consisting of 324 marker loci were used to search QTL. This program was based on mixed linear models and allowed simultaneous mapping of additive effect QTL, epistatic QTL, and QTL × environment interactions (QE). Mapping analysis produced a total of 35 QTL for 6 RVA profile parameters with a single QTL explaining 0.91-21.34% of phenotypic variations. The 35 QTL were distributed on 15 chromosomes. The QBd-4A had the most significant additive effect, accounting for 21.34% of the phenotypic variance. Two QTL clusters for RVA profile parameters were located on chromosomes 2A and 4A, respectively. The information obtained in this study should be useful for manipulating the QTL for RVA profiles parameters by molecular assisted selection (MAS) in wheat breeding programs.Key words: Doubled haploid population, paste viscosity characteristics, rapid visco analyser, quantitative trait loci, wheat (Triticum aestivum L.)
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".