Quantitative Trait Locus Analysis for Grain Size Related Traits of Rice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Grain shape and size, which are characterized by grain length, grain width, grain thickness, and length to width ratio, are the key determinants of grain weight. In this study, a 188-individual F 2 population, which derived from a cross between large grain Indica cultivar Nangyangzhan and medium grain Indica cultivar Ce253, were used to analyze grain size related QTLs with 110 molecular markers. Inclusive Composite Interval Mapping (ICIM), was applied to genome-wide detection of QTLs underlying grain size related traits. For grain length, 4 QTLs were detected on chromosome 1, 3, 4, and 9, respectively. qGL-3 , a major effect QTL, explained 27.60% phenotypic variation of grain length. Four QTLs for grain width were detected on chromosome 2, 3, and 5. Among them, qGW-5a was major QTL for grain width, which explained 21.30% of phenotypic variation. Five QTLs for length to width ratio, which were distributed on chromosome 2, 3, 5, and 12, were identified. The range of their phenotypic contribution varied from 8.60% to 16.86%. For TGW QTLs, only two were identified on chromosome 5 and 6, respectively, with which 13.26% and 9.04% phenotypic contribution. In our results, qGL-4 and qGL-9 for grain length were novel loci. They have not seen reported in literature previously. Our results shed new light on further fine mapping and understanding the molecular genetic mechanism of novel grain size QTLs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it