Dissecting the genetic basis for the effect of rice chalkiness, amylose content, protein content, and rapid viscosity analyzer profile characteristics on the eating quality of cooked rice using the chromosome segment substitution line population across eight environments
Bibliographic record
Abstract
Quantitative trait locus (QTL) mapping and stability analysis were carried out for 16 rice (Oryza sativa L.) quality traits across eight environments, by using a set of chromosome segment substitution lines with 'Asominori' as genetic background. The 16 quality traits include percentage of grain with chalkiness (PGWC), area of chalky endosperm (ACE), amylose content (AC), protein content (PC), peak viscosity, hot paste viscosity, cool paste viscosity, breakdown viscosity (BDV), setback viscosity (SBV), consistency viscosity, cooked-rice luster (LT), scent, tenderness (TD), viscosity, elasticity, and the integrated values of organleptic evaluation (IVOE). A total of 132 additive effect QTLs are detected for the 16 quality straits in the eight environments. Among these QTLs, 56 loci were detected repeatedly in at least three environments. Interestingly, several QTL clusters were observed for multiple quality traits. Especially, one QTL cluster near the G1149 marker on chromosome 8 includes nine QTLs: qPGWC-8, qACE-8, qAC-8, qPC-8a, qBDV-8a, qSBV-8b, qLT-8a, qTD-8a, and qIVOE-8a, which control PGWC, ACE, AC, PC, BDV, SBV, LT, TD, and IVOE, respectively. Moreover, this QTL cluster shows high stability and repeatability in all eight environments. In addition, one QTL cluster was located near the C2340 marker on chromosome 1 and another was detected near the XNpb67 marker on chromosome 2; each cluster contained five loci. Near the C563 marker on chromosome 3, one QTL cluster with four loci was found. Also, there were nine QTL clusters that each had two or three loci; however, their repeatability in different environments was relatively lower, and the genetic contribution rate was relatively smaller. Considering the correlations among all of the 16 quality traits with QTL cluster distributions, we can conclude that the stable and major QTL cluster on chromosome 8 is the main genetic basis for the effect of rice chalkiness, AC, PC, and rapid viscosity analyzer profile characteristics on the eating quality of cooked rice. Consequently, this QTL cluster is a novel gene resource for controlling rice high-quality traits and should be of great significance for research on formation mechanism and molecule improvement of rice quality.
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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 | 0.001 | 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 | 0.001 | 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".