Resistant Starch Content Is Related to Granule Size in Barley
Bibliographic record
Abstract
Physical properties of resistant starch (RS) were examined in a range of barley genotypes to determine the contribution of starch and seed physical characteristics to the RS component. Thirty‐three barley genotypes were studied, which varied significantly in their RS, amylose, and starch contents and grain yield. From 33 genotypes, 13 exhibiting high RS were selected for detailed physicochemical analysis of starch. In high‐RS varieties, granule size and number were unimodal, compared with normal starches from a reference genotype, which showed a bimodal distribution. Principal component analysis (PCA) showed that a higher content of granules <15 µm was positively correlated with RS and amylose content, whereas the proportion of granules 15–45 µm was negatively correlated with the RS and amylose contents. Physical fractionation of starches by centrifugation into different population sizes demonstrated that size alone is not an accurate indicator of the population of A‐type and B‐type granules within a given genotype. PCA also showed that large 15–45 µm granules were positively correlated with seed thickness and that thousand grain weight was positively correlated with seed width. High‐RS and high‐amylose genotypes showed variation in overall yield and starch content, with some genotypes showing yield comparable to the reference genotype. Analysis of amylopectin chain length distribution showed that high amylose or RS content was not associated with a higher proportion of amylopectin long chains when compared with either waxy or reference (normal) barley genotypes. This study highlights useful markers for screening barley genotypes with favorable starch characteristics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".