Differences in Starch Granule Composition and Structure Influence In Vitro Enzymatic Hydrolysis of Grain Meal and Extracted Starch in Two Classes of Canadian Wheat (<i>Triticum aestivum</i> L.)
Bibliographic record
Abstract
ABSTRACT Starch granule composition and amylopectin structure affect starch digestibility, an important factor influencing wheat grain utilization for human food consumption. Six bread wheat cultivars with four belonging to the Canada Western Red Spring (CWRS) and two Canada Prairie Spring Red (CPSR) market classes were analyzed for the relationship between their grain constituents and in vitro enzymatic hydrolysis of starch. CPSR cultivars had higher starch and amylose concentrations compared with CWRS cultivars, which had a higher protein concentration. Starch granule size distribution did not differ among the genotypes, except AC Foremost, which had significantly (P < 0.05) higher volume percent of B‐type starch granules (≈15%) and lower volume percent of A‐type starch granules (≈9%) compared with other cultivars. Fluorophore‐assisted capillary electrophoresis revealed a lower content of R‐IV (DP 15–18, ≈6%) and a higher content of R‐VII (DP 37–45, ≈7%) chains in the CPSR cultivars compared with the CWRS cultivars. Starch in vitro enzymatic hydrolysis showed that compared with CWRS cultivars, the two CPSR cultivars had reduced amounts of readily digestible starch and higher amounts of slowly digestible starch and resistant starch. Consequently, the two CPSR cultivars also showed lower hydrolysis indexes in grain meal as well as extracted starch. CPSR cultivars, with higher starch and amylose concentrations, as well as a higher content of long chains of amylopectin, showed a reduced starch in vitro enzymatic hydrolysis rate.
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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".