Screening and characterization of cultivar with M-type amylopectin in Japanese upland rice
Bibliographic record
Abstract
Asian rice (Oryza sativa L.) cultivars were recently classified into L-type, S-type, and intermediate M-type (rich, poor and middle intermediate-chain) on the basis of the fine structure of amylopectin in their grains. We selected 4 cultivars with M-type amylopectin from 174 local Japanese nonwaxy upland rice cultivars by scoring the disintegration of starch granules in alkaline solution and measuring the pasting temperature (PT) of their rice flours. Analyzed amylopectin fine structure, these cultivars exhibited intermediate characteristics between those of S-type Koshihikari and L-type IRAT109. Moreover, compared hardness of dumpling cakes after cooled for 3 h and 24 h. The hardness was in the order L-type > M-type > S-type, each other. On the other hand, the amylopectin chain ratio (ACR) was negatively correlated with the hardness of dumpling cakes both after cooled for 3 h and 24 h. Therefore, we concluded that the 4 cultivars—Chikanarijyun1, Hokkaiakage, Kairyo13, and Mogamichikanari1—had M-type amylopectin, and Japanese local upland rice has wide genetic diversity about starch mutation.
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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) | 0.000 | 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 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".