Identification of quantitative trait loci for seed isoflavone concentration in soybean (<i>Glycine max</i>) against soybean cyst nematode stress
Bibliographic record
Abstract
Abstract Isoflavones are plant secondary metabolites produced in soybean ( Glycine max ), which provide plant defense against pathogens and are beneficial to human health. Soybean cyst nematode (SCN) is a major yield‐limiting pest in most soybean‐producing area across the world. Traits, seed isoflavones and SCN resistance are quantitative in nature, and their phenotypic evaluations are expensive. Quantitative trait loci (QTL) underlying the two traits will be helpful to develop SCN‐resistant lines with elevated isoflavones using marker‐assisted‐selection (MAS). This study aims to identify isoflavones and SCN‐related QTL in a soybean population consisting of 109 RILs, which was developed from a cross between two commercial soybean cultivars viz. ‘RCAT1004’ and ‘DH4202’ and grown in four non‐SCN and SCN‐infested fields during 2015 and 2016. While single marker ANOVA identified 10 QTL for isoflavones and five for SCN ( p < 0.01), simple interval and multiple QTL mappings identified four QTL associated with isoflavones (LOD ≥ 2.2). These results contribute to a better understanding of the genetics of the two traits and provide molecular markers that can be used in MAS to facilitate developing SCN‐resistant soybeans with increased isoflavones.
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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".