Identification and dissection of single seed weight QTLs by analysis of seed yield components in soybean
Bibliographic record
Abstract
Single seed weight (SSW), or seed size, is a seed yield components (SYC) in soybean, and it is suggested that the genetic factors regulating SSW are involved in the control of other SYCs. The quantitative trait loci (QTLs) for SSW and their effects on the other SYCs were investigated using a recombinant inbred line population derived from typical small- and large-seeded cultivars that were cultivated in two different environments. QTL analysis detected four environmentally stable QTLs for SSW, two of which coincided with the defined loci, qSw17-1 and Ln. The effects of the other loci, qSw12-1 and qSw13-1, were confirmed by analyzing residual heterozygous line progenies derived from the recombinant population. These four QTL regions were also involved in the control of an additional SYC, namely the large-seeded allele at each locus that reduced either the number of pods per plant or the number of ovules per pod. These results suggest the presence of at least two different regulatory mechanisms for SSW. Isolation of genes responsible for these QTLs provides an important tool in the understanding and utilization of SSW diversity for soybean breeding.
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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".