Differences in Carbohydrate Composition and Digestion In Vitro of Selected Barley Cultivars as Influenced by Pearling and Cooking
Bibliographic record
Abstract
ABSTRACT Among common cereals, barley is a low glycemic index food. In an attempt to better understand this character, the nutritional properties of glycemic carbohydrates and dietary fiber concentrations of nine cultivars were evaluated. The cultivars were selected based on botanical variations and commercial value to investigate the impact of pearling and cooking on nutritional properties. Each cultivar was pearled into four fractions ranging from hull removal only to hull, bran, germ, and crease removal. The study showed that botanical class and degree of pearling significantly affect the carbohydrate composition and digestion indices of barley. Waxy starch cultivars had less total starch and more rapidly digestible starch (RDS), rapidly available glucose (RAG), and β‐glucan than the other nonwaxy cultivars. Regardless of the barley type, the less pearled kernels had significantly lower total starch and higher total low molecular weight sugars, insoluble, and total fiber. However, β‐glucan content was fairly comparable in the whole grain and pearled fractions. Cooking had a significant effect on nutritional properties of Celebrity and AC Klinck cultivars. The only consistent significant difference between raw and cooked barley was resistant starch (RS), which increased after cooking regardless of cultivar or fraction. The study showed that barley cultivar and carbohydrate composition significantly affected starch digestion with some cultivar fractions holding a promise for the development of low glycemic index foods.
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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 | 0.000 | 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 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".