Genetic Analysis of Yield Components in the PI 438489B by ‘Hamilton’ Recombinant Inbred Line (RIL) Population of Soybean [Glycine max (L.) Merr.]
Bibliographic record
Abstract
Yield is a multi-factorial trait determined by several genetic traits and highly correlated with important agronomic traits in many crops including soybean. [Glycine max (L.)]. Plant height, seed and pod numbers, and seed weight are all components of yield and polygenic in nature. The objective of this study was to identify quantitative trait loci (QTL) for days to germination, days to flowering, plant height, pod number, seed number, 100-seed weight, and total seed weight in soybean using the using the PI 438489B by ‘Hamilton’ recombinant inbred line (RIL) population (PIxH, n=50). A total of 18 QTL were found on 10 different chromosomes. Three QTL for days to germination (qDG001-qDG003) have been identified on chromosomes 5b, 6, and 13b. Two QTL (qDF001 and qDF002) have been identified on chromosomes 9 and 13b, respectively. On QTL for plant height (qPH001) have been identified on chromosome 6. Four QTL for pod number (qPN001-qPN004) had been identified on chromosomes 2, 6, and 8 (2 QTL), respectively. Two QTL for seed number (qSN001 and qSN002) have been identified on chromosomes 5b and 11b, respectively. Five QTL for 100-seed weight (qSW001 to qSW005) have been identified on chromosomes 5a, 6, 8, 9, and 11c, respectively. Two QTL for total seed weight (qTSW001 and qTSW002) have been identified on chromosomes 5b and 17c, respectively. The QTL identified here may be introduced in breeding programs to develop soybean cultivars with high yield potential.
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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".