Population-specific quantitative trait loci mapping for functional stay-green trait in rice (<i>Oryza sativa</i>L.)
Bibliographic record
Abstract
The functional stay-green trait gives leaves a longer duration of greenness and photosynthetic capacity during the grain-filling period. We developed two independent recombinant inbred line populations from the intra- and intersubspecific crosses of Oryza sativa L. subsp. japonica 'Suweon490' (japonica) × O. sativa subsp. japonica 'SNU-SG1' (japonica) and O. sativa subsp. indica 'Andabyeo' (indica) × O. sativa subsp. japonica 'SNU-SG1' (japonica), respectively. The common parental line 'SNU-SG1' was the functional source for the stay-green trait. Quantitative trait locus (QTL) mapping based on simple sequence repeat markers identified a total of six QTLs associated with two stay-green traits across two populations. The two traits were cumulative chlorophyll content (SPAD value) of flag leaf (CSFL) and total cumulative SPAD value of the four upper leaves (TCS). Four QTLs, tcs4, csfl6, csfl9 (or tcs9), and csfl12, located on chromosomes 4, 6, 9, and 12, respectively, were detected simultaneously in both populations. The remaining two QTLs, csfl2 (or tcs2) and tcs5, on chromosomes 2 and 5, respectively, were found to be population specific. Moreover, the functional stay-green trait of 'SNU-SG1' positively correlated with grain yield performance. Two yield QTLs, yld6 and yld9, on chromosomes 6 and 9 found in both populations were positioned at the same locations with the csfl6 and tcs9 QTLs for stay-green traits. Thus, the identified chromosomal regions can be promising targets of marker-assisted introgression of the functional stay-green trait into breeding materials for improvement of rice yield.
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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".